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THIS IS THE MOMENT TO CHOOSE PROGRESS OVER STANDING STILL

Visitors information

Floor plan

Exhibitor List

Program Wednesday

Program Thursday

#1 IN DATA & AI FOR TECH AND BUSINESS 9 & 10 September 2026 | Jaarbeurs Utrecht | data-expo.nl

Van AI-experiment naar aantoonbare waarde Waarde uit AI staat of valt met Data, Context en Vertrouwen.

DATA

CONTEXT

TRUST

WAARDE

SESSIE

Bĳwonen: de onboarding van je AI-collega “Van pilot naar volwaardig teamlid” Thomas Klopstra CBEE Remarkable

Sayed Nasibdar Gen25

Donderdag 10 september 12:45 - 13:15 uur Lezingzaal 6, Jaarbeurs Utrecht

DOE DE AGENTIC AUDIT

Laat je inspireren op de stand en ontdek in de agentic audit welke processen klaar zĳn voor een AI-collega.

Bezoek stand 124

TABLE OF CONTENTS 5 6 9

Floor plan + partners Exhibitor List Women @ Data Expo

12 Interview (Joep Steenbeek, City of Amsterdam) 17 Interview (Brander.company) 28 Interview (Jessica Ruland, TicketSwap) 36 Interview (Chris Boonstra, CBEE Remarkable) 52 Interview (Martin Woodward, Randstad & Tjerrie Smit, Nationale-Nederlanden) 31 Blogs from our newsletter 32 Blog AI in Practice: From Silver Bullet to Sustainable Impact 41 Blog Data-driven work isn’t just an IT issue 55 Video series In conversation with… WEDNESDAY 9 SEPTEMBER 10 Program Wednesday 14 Keynote Wednesday 18 Lecture program hall 1 19 Lecture program hall 2 20 Lecture program hall 3 21 Lecture program hall 4 23 Lecture program hall 5 24 Lecture program hall 6 25 Lecture program hall 7 26 Lecture program hall 8 27 Roundtable sessions THURSDAY 10 SEPTEMBER 34 Program Thursday 38 Keynote Thursday 42 Lecture program hall 1 43 Lecture program hall 2 44 Lecture program hall 3 45 Lecture program hall 4 47 Lecture program hall 5 48 Lecture program hall 6 49 Lecture program hall 7 50 Lecture program hall 8 51 Roundtable sessions

PODCAST DE DATALOOG

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LEARN MORE ABOUT: Product development with AI Data quality Problem solving DataOps in practice Digitalization Listen to roundtable discussions, in-depth interviews, and stories from experts with hands-on experience.

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“We naturally want to ensure that we can stand on our own two feet when it comes to this kind of technology. And that we can also seize the opportunities it presents in terms of employment.” Alexandra van Huffelen State Secretary for Digital Affairs LISTEN TO THE EPISODES IN COLLABORATION WITH DATA EXPO

OPENING HOURS Wednesday 9 September 2026 10:00 - 17:00 hour Thursday 10 September 2026 10:00 - 17:00 hour Data Expo is a production of:

De Dataloog is a Dutch podcast where data scientists, consultants, technology companies, and researchers discuss various topics in the field of data. They also have various podcasts in English.

Organisatie Groep Zuid bv Ambachtweg 52 5731 AG Mierlo +31 (0) 40 280 95 00 info@data-expo.nl www.data-expo.nl This publication has been compiled with the greatest care. Nevertheless, (printing) errors or omissions may occur. OGZ accepts no liability for this.

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

DATA EXPO CONNECT APP

Get the most out of your exhibition visit with Data Expo Connect. The free networking app, designed to enhance your exhibition experience. “Networking has never been this easy!” Here’s what you can do with the app:

Schedule meetings with all other app users

View the full program and create your own personal schedule

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Check the floor plan to easily navigate the exhibition hall

Swipe & Match: business tinder, connect based on professional interests

FLOOR PLAN

GOLD PARTNER | BOOTH 128

KEYNOTE

TOILET

FLOOR PL AN DATA EXPO 9 & 10 SEPTEMBER 2026

PLATINUM PARTNER BOOTH 124

GOLD PARTNER | BOOTH 11

22 21

LECTURE HALL 3

19 20

23 25

ROUNDTABLE

120 116

121

125 128

124

152 150

154 156 155

GOLD PARTNER | BOOTH 50

LECTURE HALL 5

GOLD PARTNER | BOOTH 54

LECTURE HALL 4

14 13 12

LECTURE HALL 2

30 31

60 57

76 77 80

115

145 144

LECTURE HALL 1

55 51

138

CATERING

140 139

LECTURE HALL 7

SILVER PARTNER | BOOTH 80

GOLD PARTNER | BOOTH 76

SILVER PARTNER | BOOTH 150

143

164 165

142

GOLD PARTNER | BOOTH 140

LECTURE HALL 6

GOLD PARTNER | BOOTH 82

162

GOLD PARTNER | BOOTH 176

ENTRY

INFO

TOILET

95 92

114 132

136 133 131

175 174 176

PASSAGE TO CYBERSEC

SILVER PARTNER | BOOTH 89

178

SILVER PARTNER | BOOTH 145

177

SILVER PARTNER | BOOTH 95

LECTURE HALL 8

SILVER PARTNER | BOOTH 1

134

172 171

SILVER PARTNER | BOOTH 35

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

EXHIBITOR LIST A

PLATINUM PARTNER

GOLD PARTNER

Deeploy www.deeploy.ai

Dexes www.dexes.nl

162

124

Digital Power www.digital-power.com

ABN AMRO Bank N.V. www.abnamro.com

128

CBEE Remarkable www.cbeeremarkable.nl

124

DTX | Dutch Technology eXperts www.dtx.nl

ADC www.adc-consulting.com

Certinia www.certinia.com

Dutch Cloud Community www.dutchcloudcommunity.nl

AI4ALL www.aifourall.org

Circle One www.circleone.nl

143

Dutch Women In Tech www.dwit.work

AIStudio www.aistudio.nl

Coface www.coface.nl

Algemene Inlichtingenen Veiligheidsdienst www.aivd.nl

Company.info www.companyinfo.nl Conscia Nederland B.V. www.conscia.com

Dux Group www.duxgroup.nl

Considerati www.considerati.com

174

SILVER PARTNER

Alteryx www.alteryx.com

150

Cribl www.cribl.io

Amsterdam Data Academy www.amsterdamdataacademy.com

CrossModel www.crossmodel.io

144

AppsWare www.appsware.io

121

Cyso www.cyso.com

133

Autoriteit Consument & Markt www.acm.nl

120

DAMA-NL www.dama-nl.org

Autoriteit Persoonsgegevens www.autoriteitpersoonsgegevens.nl

120

Avepoint Benelux www.avepoint.com

116

Data + Women Netherlands 5 www.usergroups.tableau.com/data-womenamsterdam

BaseTide www.basetide.com

138

BearingPoint www.bearingpoint.com

BIT www.bit.nl

3 GOLD PARTNER

Data Expo Exhibitor Hub www.data-expo.nl/en/exhibitors

Data Kitchen B.V. www.datakitchen.nl

138

e d r m consultancy EDRM Consultancy bv www.edrm-consultancy.nl

152

Edsson Software www.edsson.com

154

Eli5 www.eli5.io

93 SILVER PARTNER

Enable-U www.enable-u.nl

Eriklabs www.eriklabs.io

121

Databaas www.databaas.eu

172

Evolane www.evolane.eu

Databricks www.databricks.com

Exasol www.exasol.com

175

Dataddo www.dataddo.com

GOLD PARTNER

Datadirigent www.masteringdata.academy

Bravinci www.bravinci.com

175

Dataintegratie.nl www.dataintegratie.nl

125

DataPebbles www.datapebbles.com

document en records management

E-mergo www.e-mergo.nl

Brander.company www.brander.company

CAS Software AG www.cas-crm.com

DataTako www.datatako.com

GOLD PARTNER

Datashift www.datashift.eu

Datastudent www.datastudent.nl

177

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Fivetran + dbt Labs www.fivetran.com

Follo www.folloagency.com

Functional Analytics www.functionalanalytics.nl

165

Gen25 www.nl.gen25.com

124

SILVER PARTNER

GOLD PARTNER

HAVELSAN www.havelsan.com

176

HPE www.hpe.com

iamSARA.io www.iamsara.io IMPROVEN www.improven.nl

Oracle Nederland www.oracle.com

OutSystems www.outsystems.com

136

SILVER PARTNER

PIANO www.piano.io

145

Premium www.premium.nl

138

GOLD PARTNER

Informatica from Salesforce www.informatica.com/salesforce.html

InSpark www.inspark.nl

International Data Spaces Association www.internationaldataspaces.org

IntoDQ2 www.intodq2.com

139

License Partners Cloud Solutions www.lpcs.nl

171

Localign www.localign.com

134

Previder www.previder.nl

140

ProductFlight www.productflight.io

156

Proxy Platform www.platform.proxy.nl

Qaitbay www.qaitbay.com

RepliKate - Numaga www.numaga.ai

Q R

155

Rockfeather www.rockfeather.com

SILVER PARTNER

115

Rotterdam Women in Tech www.rotterdamwomenintech.nl Magic Software www.magicsoftware.nl

Ministerie van Justitie en Veiligheid www.werkenbijjenv.nl

Mobilee www.mobilee.nl

Nemko Digital www.digital.nemko.com

Nippur www.nippur.nl

132

Openindex www.openindex.io

RoundNode www.roundnode.com Salesforce www.salesforce.com

5 178

124

Scrape IT www.scrape-it.com

SeederDeBoer www.seederdeboer.nl

Spreash® www.spreash.com

142

SILVER PARTNER

Strategy www.software.strategy.com

Strategy Alliance www.strategy-alliance.com

SUSE www.suse.com

SemanTag.ai www.semantag.ai Sentius www.sentius.nl

114

TimeXtender www.timextender.com

TMC Data Science & IoT www.tmc-employeneurship.com

Uniserver www.uniserver.nl

U V

Victa www.victabi.com

3 140

VX Company Consultancy Services www.werkenbij.vxcompany.com

WE Make Trouble www.wemaketrouble.biz

Women @ Data Expo www.data-expo.nl/en/free-ticket/women-at-data-expo

Women in AI www.womeninai.co

Women in AIndhoven

Women in Tech Netherlands 5 www.women-in-tech.org/women-in-technetherlands 5

Xebia www.xebia.com

Yellowfin www.yellowfinbi.com Yonego Agency B.V. www.yonego.com

GOLD PARTNER

Systemation www.systemation.nl

Women’s Coding Club www.womenscodingclub.nl

GOLD PARTNER

Optimizely www.optimizely.com

131

SILVER PARTNER

LexisNexis www.lexisnexis.com

Soverin www.soverin.com

Siemens www.mendix.com/whats-new

SMT - Data zonder gedoe www.smtware.com

Zoho www.zoho.com

X Y

175 164

Zwarte Vrouwen voor Technologie (ZVVT) www.zvvt.nl

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

48 5 7

Women @ Data Expo - booth 5

BETTER TOGETHER SMARTER THROUGH DIVERSITY

New this edition: Women @ Data Expo! A concept, and a booth, where ten communities that support women who make an impact in the tech world through their knowledge, skills and character present themselves. Visit booth #5 and discover everything about the importance of diversity in the workplace. Women @ Data Expo has its own stage at the booth, where women from various communities will give short talks. We’ve highlighted a few.

WEDNESDAY 9 SEPTEMBER

THURSDAY 10 SEPTEMBER

12.40 - 13.00

10.40 - 11.00

Discover hidden fraud risks in audited AI systems and learn practical ways to identify vulnerabilities before losses occur.

Seven practical principles for ensuring that your data and AI projects are built with integrity, transparency, effectiveness and inclusively.

Vuyo Gwayi

Caroline Williams

14.20 - 14.40

13.40 - 14.00

Discover how AI, NLP and Power BI transform community conversations into privacy-conscious insights for smarter initiatives and stronger engagement.

Learn how a simple CRM structures partner processes, improves ownership, and provides financial insight from initial request through receipt.

Mona Daylamian

Monique Telgt

14.40 - 15.00

14.00 - 14.20

Beyond the technical stack lies the human layer—why designing for user diversity is key to data adoption.

Explore how a startup data engineer transformed repetitive work into a modular, multi-tenant data platform, sharing lessons and architectural decisions.

Rachel Costa

Lotte Govers

So your system passed the audit, why is it still a fraud risk ?

From Community Conversations to Community Intelligence

The Missing Layer in Your Data Stack and AI Strategy: The Human

Principles of Data Feminism - Making Data Work for Everyone

From contact request to structured follow-up: CRM for the partner process

From Zero to Platform: Building a Modular Multi-Tenant Data Platform

VISIT BOOTH #5 AND JOIN THE WOMEN @ DATA EXPO COMMUNITY.

Zwarte vrouwen voor technologie

“ The goal is for women to

integrate into the work community.” YO

U MAKE

TROUBLE

PACT

WE MAKE

Lotte Govers Data Platform Engineer, Women’s Coding Club

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

WEDNESDAY 9 SEPTEMBER 2026 Keynote Page 14-15

Hall 1

Hall 2

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10.15 - 10.45 Digital autonomy for the public sector: not a big bang, but a realistic path

10.45 - 11.30 Winners or losers, what is it going to be for Europe? Constantijn van Oranje (Techleap) Anastasia Kuskova (beSirius)

Tjebbe de Winter (CYSO) Michel Veenhuis (xxllnc) André Lino (xxllnc)

11.00 - 11.30 Building with AI Agents: Lessons from Agentic Product Development and Engineering Transformation

Hall 3 Page 20

Frans Feldberg (Vrije Universiteit Amsterdam SBE)

Yuval Temam (Radboud University) 10.45 - 11.15 Hoe Glaspoort met Databricks de afhankelijkheid van BIrapportages doorbrak Stefan Hulsbos (Digital Power) Raymon Veldman (Glaspoort)

10.45 - 11.15 Grip op AI, data en dashboards 11.00 - 11.30 When AI Teaches AI: How RTL Classifies the News

Stijn Bergmans (Follo)

12.45 - 13.15 Experimentation, accelerated: what AI changes about the way we test

12.30 - 13.00 Intelligence at every turn Oracle & Oracle Red Bull Racing Jacco Landlust (Oracle)

Noortje van Genugten (Albert Heijn)

13.45 - 14.15 How NIBC Built a Highly Governed dbt Practice at Scale

13.30 - 14.00 Waarom 90% van data en AI-projecten mislukt (en wat jij morgen kunt doen) Judith von Reeken (SeederDeBoer)

Martijn van Velzen (NIBC) Tamas Marton (NIBC)

14.30 - 15.15 The Journey to Fully Autonomous Claim Handling: How to Operationalize Agentic AI Tjerrie Smit (NN Group)

14.15 - 14.45 Schaalbare datahuishouding zorgt voor snellere en betere besluitingvorming bij Otolift

Sander Vols (Radboudumc)

Mayank Kumar (FedEx Express)

15.45 - 16.15 De kunst van Data Storytelling 16.00 - 16.30 Van Nederlandse Datakluis naar Upod: de transitie naar first person data

Henny Speelman (Archonit)

15.15 - 15.45 De compliance backlash: wanneer maakt legal innovatie kapot? Isa Nieuwstad (DDMA) Susanna Nijsten (DDMA)

16.00 - 16.30 When Every Drink is Data: The Hyper-Personalised Workplace is Just One Step Away Orfirah Helstone (H2YO Drinks)

Martijn van Dam (Stichting Nederlandse Datakluis) 16.30 - 17.00 Data Sharing: Economic Value Across the Automotive Supply Chain, Built on Trust Mario Holesch (International Data Spaces e. V.)

Zelda Zeegers (Hogeschool Utrecht)

Niek van der Laan (ADC) Willem Jakobs (Yource)

Erik Schaap (IntoDQ2 B.V.)

15.45 - 16.30 Van Fax naar Agentic AI: Wie heeft eigenlijk controle over onze zorgdata?

13.45 - 14.15 Marcel van Munster (Stedin Slaapwandelen in een berekende Netbeheer B.V.) wereld: Autonomie in het AIBram Zentveld (BearingPoint tijdperk B.V.)

14.30 - 15.00 AI That Delivers - Scaling a Trusted Enterprise Conversational Platform at FedEx

15.15 - 15.45 Waarom je Agentic AI-strategie Hanna Mironchyk (Rabobank) valt of staat met metadata Gavin Morgan (Rabobank)

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

12.45 - 13.15 Context alleen is niet genoeg. Je AI heeft bewijs nodig.

13.30 - 14.00 De race tegen het volle stroomnet

14.30 - 15.00 Van roadmap naar realiteit: 2,5 Tijs Rokers (Otolift) jaar bouwen aan een mensgericht Gert Jan Kentie (Enable U) GenAI-contactcenterplatform bij Yource met ADC

15.00 - 15.30 From Data Platform to Data Marketplace: Designing for User Experience

11.30 - 12.00 De weg naar datagedreven klantwaarde: experimenteren, AI en Customer Lifetime Value bij Greenchoice Michiel van der Meij (Greenchoice) Aurélie Lemmens (Erasmus University, RSM)

Alex van Wijnen (Timextender)

Misha Datsenko (Optimizely)

13.15 - 14.00 De menselijke kant van AI: hoe Albert Heijn AI inzet op de winkelvloer

Louis de Roo (E-mergo)

Marius Lupulescu (RTL)

11.30 - 12.00 How Vodafone Germany uses its Customer Data Platform (CDP) as a Context Engine for AI and 11.45 - 12.15 11.45 - 12.15 Activation Transformative Power of Agentic Energie Zuinig Rijden: Analytics Datagedreven innovatie op het Sarah Busson (Digital Power) spoor Jeroen Jaspar (Vodafone) Ashwinth Solomon (Zoho Corporation) Rick Stoop (NS)

12.30 - 13.00 SEO & GEO als Google niet meer bestaat: dit is hoe je vindbaar én gekozen word in Agentic Search & Shopping

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10.15 - 10.45 Responsible AI Challenges in Agentic AI

Snehit Cherian (LexisNexis)

12.00 - 12.45 Voorbij het AI-pilotsyndroom: waarom 85% faalt en hoe jij wél succesvol opschaalt

Hall 4

14.15 - 14.45 Data Act: de ACM over kansen voor Europese Cloud Rex Leijenaar (ACM)

15.00 - 15.30 AI werkt pas als mensen het gebruiken. Hoe krijg je dat voor elkaar? Romaike Middendorp (Zilveren Kruis) Marten Hiensch (Zilveren Kruis)

15.45 - 16.15 Content as a Service at bol: how all bollers can create on brand content at scale with AI Benjamin van Vianen (bol) Joey Man (bol) Mark Schep (Mark Your Data)

16.30 - 17.00 Is uw organisatie klaar voor AI? Begin bij uw data Steven Vlaanderen Oldenzeel (Brander.company)

LECTURE PROGRA M Hall 5 Page 23

Hall 6 Page 24

Hall 7 Page 25

Hall 8 Page 26

10.15 - 10.45 Hoe je een datastrategie maakt die niemand gebruikt

10.15 - 10.45 How KNB is using AI without giving away control of their data

10.15 - 10.45 Synthetische data: nep, maar toch bruikbaar

Joep Steenbeek (Gemeente Amsterdam)

Wouter Siepman (Koninklijke Notariële Beroepsorganisatie) Codrin Kruijne (Bravinci) Michael Doves (Bravinci)

Freek Bomhof (Nederlandse Organisatie voor toegepastnatuurwetenschappelijk onderzoek TNO)

11.00 - 11.30 Van Dorp Vernieuwt - IT voor Morgen

11.00 - 11.30 Van Steekproef naar 100% Scan: Hoe Altrecht GenAI Inzet voor Goede Dossiervoering

10.45 - 11.15 Running AI on your own infrastructure 11.00 - 11.30 560 startups, 1.024 founders, miljarden aan funding: de onzichtbare Nederlandse AI startup sector Willem Blom (DutchStartup.AI)

11.45 - 12.15 Driving AI Transformation: Lessons from scaling Copilot M365 at ING

David Kun (Function Analytics)

11.30 - 12.00 Hello? It’s AI: Smarter Conversations Start Here

Kai Van den Berg (DTX | Dutch Technology eXperts) Ronnie Hollemans (Van Dorp)

Amanda Ferraboli (ABN AMRO) 11.45 - 12.15 Privacy in the Sprint Julia Meuffels (ABN AMRO) Bram Hoovers (Considerati)

Timothy Dieduksman (ING Nederland) Annemarie Quik (ING Nederland)

12.30 - 13.00 Implementing Data Mesh and AI @ Alliander - Building the Grid of the Future Sander de Wildt (Alliander)

Maarten Stolk (Deeploy) Janiek Meppelink (myTomorrows)

14.30 - 15.00 AI4Data: What is an AIaugmented Data Engineer? Petra Heck (Fontys)

15.15 - 15.45 Easy start to data prompting Lukas Michalitsch (De Koffiejongens)

11.45 - 12.15 Navigating through the protein engineering landscape with automated benchmarking Shu Zhao (Xebia Data)

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10.30 - 11.15 The Skills of Tomorrow’s AI Workforce Olivier van Hees (Amsterdam Data Academy)

11.30 - 12.15 De Dataverordening (Data Act) en de AVG: tussen toegankelijkheid en privacy van data Alma Joy Ridderhof (Autoriteit Consument & Markt) Natalia Toeajeva-Elseman (Dutch Data Protection Authority (Autoriteit Persoonsgegevens))

Karel van der Weg (Researcher)

12.20 - 13.05 The Hidden Layer of AI: What Does It Take to Trust AI at Scale?

12.30 - 13.00 12.30 - 13.00 From Strategy to Impact at Scale: Migrating a DWH, Live on Stage Florian Carrier (Alteryx) PGGM’s Data Mesh Journey in Less Than 30 Minutes 12.45 - 13.15 Next Level Data Strategy: Building Your Data Foundation for the AI Era

Remy Van der Vlist (PGGM) Frank Gresnigt (Datashift)

Barry Wildhagen (Informatica from Salesforce)

13.45 - 14.15 Keeping control of AI at scale: Runtime Governance at Healthtech myTomorrows

Kasper van Mens (Altrecht) Jelle Witteveen (Altrecht)

Roundtable sessions

13.30 - 14.00 Context als bedrijfskritische asset: van eigenaarschap tot AI skill Fleur Bake (Spreash B.V.) Amber Hentschke (Voortman Steel Machinery)

13.45 - 14.15 AI-gedreven planning: van handmatig bellen naar één tap — live in twee weken Thierry Bontinck (Iris Group)

14.15 - 14.45 Hoe Schoonenberg marketing en operatie aan elkaar koppelde met data - en waarom dat meer opleverde dan meer campagnebudget Edward Stapel (Yonego Agency B.V.) Remy da Thesta Jacobs de Bok (Schoonenberg)

15.00 - 15.45 Hoe GGN met RegelRob betalingsregelingen sneller, consistenter en socialer beoordeelt Arjen Houweling (GGN BV) Kees Nooijens (GGN BV) Jeandre Knox (GGN BV)

Niels Zeilemaker (Xebia)

13.15 13.45 When the Business Case Isn’t the Law: Building Fraud Risk Intelligence Beyond Compliance

13.15 - 14.00 Integratie als Bedrijfsfunctie: Betrouwbaarheid, Kwaliteit en Ownership

Friso Schutte (SurePay) Sinan Calisir (Xebia)

Stipo Jelec (Magic Software Benelux & Nordics)

14.00 - 14.30 AI That Ships: Field Notes Dmitri Jarnikov (Prosus)

14.30 - 15.00 From Data Chaos to Data Excellence: Creating Scalable, Secure and Valuable Data Products Patrick de Vries (Data Management Architect) Paolo Platter (Witboost)

15:15-15:45 Ideate First: Converging on the Right Problem Before Building Solutions

Dennis Hoogenraad (AvePoint) 14.45 - 15.15 How Erasmus Migrated T-SQL to dbt on Databricks: AI-Assisted Migration with Lakebridge Ellen van Bergen (Erasmus MC) Murat Can Cakir (Xebia)

15.30 - 16.00 Branka Milivojevic (Nederlandse From Data to Opportunity: Uncovering gaps in the market Spoorwegen (NS)) with Multi-Agent AI

16.00 - 16.30 Tussen datastortplaats en goudmijn: grip op ongestructureerde data

16.00 - 16.30 AI-powered credit scoring to bring financial inclusion across emerging markets

16.00 - 16.30 From Tools to Teammates: Agentic AI needs Hybrid Intelligence

Nico Nijenhuis (Coöperatie VGZ UA)

Dario Raffaele (Emata)

Prof. Frank van Harmelen (The Hybrid Intelligence Centre) Prof. Catholijn Jonker (TU Delft)

14.15 - 15.00 AI‑agents: voorbij de hype, met zichtbare grip

15.15 - 16.00 Beyond the Pilot : What Makes AI Projects Actually Work Marie Fenner (Piano)

Soraya Duriez (dsm-firmenich) Michele Marchini (dsmfirmenich)

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

CITY OF AMSTERDAM: VALUE FIRST, DATA SECOND JOEP STEENBEEK Head Data Office | City of Amsterdam Joep Steenbeek works every day on the new data strategy of the Municipality of Amsterdam. It is fundamentally different from the previous one. “ We are moving from data-driven to value-driven,”explains the head of the Data Office ahead of his presentation at Data Expo. “In our new strategy, the end user is central. The primary goal is to add visible value. From there, we build the foundation, not the other way around. I would almost say: more organizations should do this.”

Joep Steenbeek worked for NS for ten years before starting his new job in the capital in September 2024. “Transforming Amsterdam into a more data-driven city,” reads his job description on LinkedIn. “Of course, you can make decisions based on gut feeling, but decision-making improves when you base it on data. That also applies to solutions for various challenges facing the city.” Data as a raw material

The head of Amsterdam’s Data Office studied in Delft. “I trained as an industrial designer,” Steenbeek explains. “Looking back, I’ve always worked somewhere between raw material and end product. Earlier in my career, that was literally the case—I used steel to build cranes; now I use data as a raw material for information products. I really enjoy the world of data. I’m highly motivated, and I love working with smart people on complex projects, especially in the public sector.”

“The old data strategy was full of jargon” 12

Data.amsterdam.nl

How data-driven will the City of Amsterdam be in 2026? According to Steenbeek, the foundation is solid: “We have a strong central data platform, and we work with more than 1,100 different dashboards within the city government. All public datasets can be found at data.amsterdam.nl, ranging from aerial photos to grants. It’s accessed about 4,000 times a day by colleagues and residents. For example, using tree maps, you can see how to avoid certain types of pollen on your route, or where oak processionary caterpillars or Japanese knotweed have been found. The interface is constantly improving; we’re considering making front-end searches easier with AI.” Users will then be able to start a conversation about the city’s data. “The challenge with such a conversational solution, of course, lies in the reliability of the results.”

Faster passport processing

Using a concrete example, Steenbeek explains how data adds value for all Amsterdammers: “After the pandemic, a spike in passport applications was expected because people were unable to travel

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

during the pandemic and let their passports expire.” The city could have used time slots—common practice nowadays—and required citizens to make appointments, but it decided to do things differently. “People could simply drop by to request a renewal, without an appointment. Staffing levels at the service counters and phone lines were based on demand forecasts. As a result, staff were deployed more effectively, while the barrier to access for residents was lowered and their wait times at city hall were reduced.”

From data-driven to value-driven

This is an example of the value-driven approach that Steenbeek advocates.“Value for end users is central to our data strategy. The first question is always where we can add the most visible value. Think of it like a library: you can neatly arrange all the books alphabetically or by color, but what do you do when you know that 80 percent of those books will never be read? We focus on that 20 percent—on what users really need. We don’t start by asking what data we’re still missing, but by asking what social or organizational value we want to achieve. Not

JOEP STEENBEEK WILL SPEAK ABOUT THE CITY OF AMSTERDAM’S NEW DATA STRATEGY. DON’T MISS IT!

Lecture hall 5

only is this better for users, it’s also more cost-effective. Take data definitions, for example. We create those first for the areas where they’re needed most right now.”

“You might go fast alone, but together you go further.” From top-down to bottom-up

The municipality’s new data strategy not only has a different goal; it’s also developed differently. “Previously, the data strategy was full of technical jargon,”says Steenbeek. “When terms like ‘data management’ came up, people within the organization would tune out. It was difficult to get the ideas conceived at the desk across to the rest of the organization.” So the approach was overhauled: the top-down approach gave way to a bottom-up approach: “To build support, we decided to gather information from within the organization and explain everything in clear language.”

Wednesday

10:15 - 10:45

Key issues and dilemmas

That’s quite a challenge, with more than twenty-one thousand employees and fifty organizational units. Steenbeek and his colleagues are actively engaging in discussions with representatives from the various units, product owners from the data teams, and employees: “We’re currently working to define about fifteen key points within the organization when it comes to data. In doing so, we’re drawing on dilemmas, among other things. Risk management or innovation? Foundation or visible value? The pillars of our new strategy stem from these.” According to Steenbeek, these are“really engaging discussions.”“As a central data organization, we naturally have certain assumptions, and sometimes those assumptions simply turn out to be wrong. Meanwhile, we’re also having discussions with other municipalities to learn from one another and discover synergies. Because on your own, you might move fast, but together, you go further.”

Building from the ground up

Developing a data strategy isn’t a linear process, Steenbeek knows. “That’s certainly true of the way we’re doing it now, with feedback coming from all sides. We’re essentially using an agile approach, in which we’re constantly testing and adjusting.” He’s convinced of the value-driven focus and the bottom-up development of Amsterdam’s new data strategy. “I’d almost say that more organizations should do that. How often do you see an architecture diagram with a story woven around it? We start with the end user’s needs. We build from the ground up and focus on what truly delivers value. At Data Expo, I’d love to talk about the challenges and successes, but also about the mistakes I’ve made along the way at the municipality. I think this honest account will be of interest to many organizations.”

“We start with the end user’s needs”

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

WEDNESDAY 9 SEPTEMBER 2026 KEYNOTE PROGRAM Moderator: Justine Wolters

10:45 - 11:30

Constantijn van Oranje Special Envoy

Winners or losers, what is it going to be for Europe? How can the Netherlands and Europe build a future-proof tech ecosystem where AI, data, and entrepreneurship drive growth? In this keynote, Constantijn van Oranje and Anastasia Kuskova discuss opportunities, challenges, and Europe’s global position. Moderated by Justine Wolters, the session explores innovation, talent, investment, and the role of initiatives like Techleap and the AI Hub in strengthening the ecosystem.

Anastasia Kuskova CEO and Co-Founder

12:00 - 12:45

Frans Feldberg Hoogleraar

Voorbij het AI-pilotsyndroom: waarom 85% faalt en hoe jij wél succesvol opschaalt 85% van de AI-initiatieven blijft steken in de pilotfase. De oorzaak: AI wordt behandeld als IT-instrument in plaats van als sociaal-technische transformatie — succes bij opschaling hangt voor 70% af van processen en mensen, niet van technologie. In deze keynote biedt Frans een routekaart van geïsoleerde proofsof-concepts naar succesvolle AI-scaling. Aan de hand van theorie, inspirerende cases en concrete handvatten behandelt hij het waarom, wat en hoe van verantwoord AI opschalen.

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

13:15 - 14:00

Noortje van Genugten Vice President Product

14:30 - 15:15

De menselijke kant van AI: hoe Albert Heijn AI inzet op de winkelvloer AI in retail gaat niet alleen over nieuwe technologie, maar vooral over hoe je het werk in winkels slimmer, eenvoudiger en effectiever maakt. In deze presentatie laat Noortje van Genugten zien hoe Albert Heijn AI inzet om de winkeloperatie van de toekomst vorm te geven: met oplossingen die medewerkers op de winkelvloer helpen bij hun dagelijkse vragen, keuzes en processen. Aan de hand van concrete voorbeelden deelt zij hoe AH AI inzet om echte operationele problemen op te lossen: van het snel beantwoorden van vragen tot het beter organiseren van dagelijkse winkelprocessen. De kern daarbij is mensgericht ontwikkelen: beginnen bij wat medewerkers écht nodig hebben, klein starten, leren van feedback en pas daarna opschalen. De presentatie laat zien hoe AH AI laat groeien van een slimme assistent tot een fundament, waarin mensen en technologie elkaar versterken. Niet AI als doel op zich, maar als middel om medewerkers beter te helpen, klanten beter te bedienen en de operatie elke dag een beetje slimmer te maken.

The Journey to Fully Autonomous Claim Handling: How to Operationalize Agentic AI When customers expect instant results, AI must evolve from answering to acting. In this keynote, Chief Analytics Officer Tjerrie Smit will tell you about the ‘AI Agentic Journey’ NN Group is on. From strategy, data foundations and

Tjerrie Smit

Chief Analytics Officer

15:45 - 16:30

leadership commitment – required to redesign complex processes into fast, smooth customer experiences – to practical lessons learned and first steps to begin with your #1 problem.

Van Fax naar Agentic AI: Wie heeft eigenlijk controle over onze zorgdata? AI maakt meer mogelijk dan ooit, maar vergroot ook de impact van fouten, misbruik en cyberaanvallen. In een Universitair Medisch Centrum (UMC) komen data uit zorg, onderzoek en onderwijs samen. Maar hoe stuur je veilig op miljoenen

Sander Vols

Chief Information Security Officer (CISO)

onbekende databronnen, uiteenlopende AI-toepassingen en een steeds complexer dreigingslandschap? Vanuit de praktijk van het Radboudumc bespreek ik kansen, risico’s, incidenten en waarom zicht op data essentieel is voor AI-governance en cybersecurity.

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Van versnipperde data naar één betrouwbaar stuurbeeld.”

Uw Single Point Of Truth

In veel organisaties leeft data in losse systemen. Elk systeem vertelt een deel van het verhaal, geen enkel systeem vertelt het geheel.

BranderSPOT brengt uw data samen tot één betrouwbare bron waarop u kunt sturen, rapporteren en AI kunt inzetten. Zonder uw bestaande applicaties te vervangen.

BranderBUS haalt data gecontroleerd uit uw bestaande applicaties.

De data komt samen in een gescheiden datawarehouse, los van uw productiesystemen.

Rapportage

Van daaruit ontstaat één stuurbeeld: dashboards, rapportages en AI waarop de directie kan sturen.

Van versnipperde data naar één betrouwbaar stuurbeeld.

Uw Regie Alles blijft binnen uw eigen, beheerde infrastructuur. Uw data blijft van u.

Benieuwd hoe uw stuurbeeld eruitziet?

Ontmoet ons op Data Expo Stand 11 • 9 & 10 september 2026 info@brander.company +31 (0)297 893 096

BranderSPOT, BranderBUS en BranderDWH zijn producten van DATABrander.nl Uw partner in databasebeheer en data-engineering

Interview:

GÉ BRANDER & ERIK RADIX – Brander.company

“We don’t deliver another dashboard. We deliver one number that everyone trusts enough to act on.” At Brander.company, we don’t believe in quick wins. We’d rather build future-proof solutions and long-term partnerships. That’s why, more than seven years after we started, we’re still working with the same clients. What defines us? Open, reliable and proactive. Another thing that’s typically Brander.company: we speak plain language. With a pragmatic approach and in-depth expertise, we deliver solutions tailored to your organisation.

What value do you bring to organisations?

”Many organisations have plenty of data, but not enough control over their numbers. Information is scattered across different systems, and management reports are often compiled manually. That doesn’t just take a lot of time, it also creates dependency on the people who know where the data comes from and how it needs to be combined. On top of that, discussions often start with which figures are actually correct. We automatically bring all that information together into one reliable, up-to-date management view. For us, the real value isn’t more data. It’s more trust, greater speed, and better control over your organisation.”

Who is your ideal customer?

“BranderSPOT is particularly relevant for

small and medium-sized organisations that work with multiple business systems (three or more) and find that the data from those systems doesn’t come together properly. A situation many organisations will recognise? Management meetings that begin with debating the numbers before anyone can actually talk about the business. If you want to keep your existing systems but gain one reliable, up-to-date view of your organisation, we’re the right partner to help you achieve that.”

What makes Brander.company unique?

“What sets us apart is that we don’t start from the assumption that organisations need to replace their existing systems. We work with one trusted number, enabling organisations to improve without large-scale system replacements. We also go beyond a traditional BI project. We don’t just build reports, we create the structural foundation for unlocking, centralising and ensuring the reliability of your underlying data. And we don’t simply build a dashboard for today’s question. We create a solid foundation that allows you to connect new data sources and management insights as your organisation grows.”

What does it take to move from a successful pilot to broad adoption?

“We like to start with a low-threshold proof of concept: a clearly defined period, a limited number of data sources, and one specific reporting or management question.

This allows your organisation to experience— with limited risk—the benefits of automatically bringing data together and managing from one reliable source of truth, without immediately committing to a fullscale implementation. At Data Expo, we’d love to explore together what that first step towards a scalable data environment could look like.”

Which AI development will have the biggest impact on organisations in the coming years?

“AI will become increasingly connected to organisations’ own business data. We’re working towards a secure integration where AI can only access the data that someone is authorised to view based on their role. This will create an entirely new way of working with business data. Employees will simply ask questions in plain language and receive access only to the information that’s relevant to them. Secure, controlled, and available either on-premises or in the cloud.”

Why Data Expo?

“Data Expo is a great opportunity to increase awareness of BranderSPOT and to meet both existing and new relationships in person. We believe it’s important to first understand the challenges organisations face, the ambitions they have, and where reliable management information can truly make a difference. Those conversations are often where the strongest and most lasting partnerships begin.”

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

WEDNESDAY 9 SEPTEMBER 2026 HALL 1

10:15 - 10:45

11:00 - 11:30

11:45 - 12:15

12:30 - 13:00

Digital autonomy for the public sector: not a big bang, but a realistic path

Building with AI Agents: Lessons from Agentic Product Development and Engineering Transformation

Transformative Power of Agentic Analytics

SEO & GEO als Google niet meer bestaat: dit is hoe je vindbaar én gekozen word in Agentic Search & Shopping

Public organisations are responsible for their own data and systems. With vendor lock-in and platform dependency becoming a real risk, it is time to make clear choices. In this session, xxllnc and Cyso show how to take practical first steps today. Using European cloud solutions, open standards, and Haven/ Haven+ certified infrastructure, you build software that works reliably and keeps your options open. Now and in the future.

AI agents are transforming both enterprise software and the way it is built. In this session, Snehit Cherian, CTO of Global Nexis Solutions at LexisNexis, shares lessons from designing agentpowered applications and adopting agentic development practices internally. The talk covers Agentic AI, framework selection, engineering workflows, governance, and the considerations that apply across both contexts.

In a world of growing data complexity and faster decision cycles, traditional analytics is no longer enough. Agentic Analytics enables organizations to move ahead from being reactive to proactive, with autonomous, intelligent, goal-driven decisioning. Join us to explore: • Key data and analytics challenges today • Transformative role of Agentic Analytics • Key tenets for successful Agentic Analytics solution • Live demos of Agentic Analytics

Tjebbe de Winter Founder/CTO

Michel Veenhuis CEO

André Lino CTO

Ashwinth Solomon

CTO

Senior Evangelist - Zoho Analytics

Stijn Bergmans Head of AI Search

13:45 - 14:15

14:30 - 15:00

15:15 - 15:45

16:00 - 16:30

How NIBC Built a Highly Governed dbt Practice at Scale

Van roadmap naar realiteit: 2,5 jaar bouwen aan een mensgericht GenAIcontactcenterplatform bij Yource met ADC

Waarom je Agentic AI-strategie valt of staat met metadata

Van Nederlandse Datakluis naar Upod: de transitie naar first person data

Iedereen praat over Agentic AI. Weinig mensen praten over de reden dat de meeste pilots stranden voor ze productie halen: rommelige data zonder context. In deze sessie laat Erik Schaap zien waarom Data Excellence — met metadata management en dataproducten als fundament — de échte voorwaarden zijn voor betrouwbare AI. Met concrete lessen uit financial services, publieke sector en insurance krijg je handvatten om je organisatie AI-ready te maken. Voor iedereen die verder wil dan mooie woorden alleen.

Kun je als bedrijf nog je eigen succes bepalen? Is gebruikersdata nog een succesfactor, of juist een risico? En maak je nog kans in het AI-tijdperk? Jarenlang draaide alles om cookies en tracking. Maar nu browsers, toezichthouders en AI de spelregels veranderen, is het tijd voor een paradigmawisseling. Martijn van Dam laat zien hoe first person data, via de Datakluis en Upod, bedrijven weer grip geeft op hun eigen succes in het AI-tijdperk.

Most data teams set out to build a welldocumented, well-tested, and cleanly governed data platform — few actually get there. NIBC, a Dutch bank, did. In this session, NIBC’s data team will share how they built a dbt Mesh hub-and-spoke architecture on Databricks — a central Cloud Data Platform hub handling all source ingestion, feeding domain-specific spokes for Finance, Risk, Retail, and Listing — anchored by a banking-specific conceptual data model (parties, products, collateral) shaped directly by regulatory and financial reporting requirements. Powered by Fivetran + dbt Labs

Martijn van Velzen

Associate Director Data Platforms

Snehit Cherian

Wat als Google zoals we het kennen niet meer bestaat? Tien blauwe links en klikken op een resultatenpagina? Dat is verleden tijd. We zoeken meer dan ooit, maar niet meer zelf. AI-agents in ChatGPT, Gemini, Google en Copilot zoeken, vergelijken en kiezen straks namens je klant. Een product kopen, een dienst afsluiten of contact opnemen met een bedrijf: het gebeurt straks allemaal zonder dat die klant ooit jouw website bezoekt. Klassieke zoekresultaten maken plaats voor AI-gegenereerde antwoorden. De klik verdwijnt, maar de keuze wordt vóór die klik gemaakt. De vraag is niet óf dit jouw merk raakt, maar of jij de naam bent die AI aanbeveelt op het moment dat het ertoe doet.

Tamas Marton

Senior Data Platform Engineer

Hoe transformeer je GenAI van een losse pilot tot een schaalbaar platform dat échte businesswaarde levert? Yource en ADC delen hun praktijkverhaal over de bouw van een mensgericht AI-contactcenterplatform voor 4.000 medewerkers. Ontdek hoe een strategische roadmap, vroege use cases (zoals kwaliteitsmonitoring) en een continu veranderend tech-landschap samenkomen. Een sessie over hoe AI medewerkers versterkt in plaats van vervangt, mét een playbook voor een toekomstbestendige architectuur.

Niek van der Laan Lead Engineer GenAI

Willem Jakobs

Director Tech & AI

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Erik Schaap

Senior Data Consultant

Martijn van Dam Initiatiefnemer

LECTURE PROGRA M HALL 2

10:45 - 11:15

11:30 - 12:00

12:45 - 13:15

13:30 - 14:00

Hoe Glaspoort met Databricks de afhankelijkheid van BIrapportages doorbrak

How Vodafone Germany uses its Customer Data Platform (CDP) as a Context Engine for AI and Activation

Experimentation, accelerated: what AI changes about the way we test

Waarom 90% van data en AI-projecten mislukt (en wat jij morgen kunt doen)

Veel organisaties worstelen met een groeiende vraag naar inzichten, terwijl datateams vastlopen in het bouwen van rapportages en dashboards. In deze sessie laten Glaspoort en Digital Power zien hoe AI en Databricks deze dynamiek kunnen doorbreken. De sleutel is Lakebase, de nieuwe OLTP-database van Databricks, die de analytische en operationele wereld samenbrengt op één platform. Ontdek hoe projectmanagers zelfstandig antwoorden uit data halen, terwijl het data team verschuift van rapportbouwer naar enabler van datagedreven besluitvorming. Een praktijkvoorbeeld van hoe je met dezelfde capaciteit meer waarde levert.

Stefan Hulsbos Raymon Veldman Data Engineer

Manager Business Control & IT

This session explores how Vodafone Germany uses a Customer Data Platform (CDP) and real-time streaming to make customer context available when and where decisions happen. With Digital Power as the technical implementation and enablement partner, that context becomes the foundation for smarter activation, better service interactions and AI-enabled use cases such as churn prevention, propensity to buy and next best action.

Sarah Busson

Technical Web Analytics consultant

Jeroen Jaspar Senior Martech & Data Manager

In this session, we explore how AI is automating the repetitive parts of testing, dramatically lowering the bar for teams to run high-quality experiments at scale, and shifting the data analyst’s role from test executor to learning architect.

Misha Datsenko

Senior Product Manager (Experimentation Analytics)

90% van data en AI-projecten mislukt. Niet door slechte modellen of te weinig data, maar door menselijke en organisatorische factoren. In deze sessie leer je hoe je dit voorkomt: van AI-geletterdheid en scherpe strategie tot governance die versnelt in plaats van remt. Je gaat naar huis met concrete inzichten en een helder beeld van wat er nu moet gebeuren in jouw organisatie.

Judith von Reeken Managing Consultant

14:15 - 14:45

15:00 - 15:30

15:45 - 16:15

16:30 - 17:00

Schaalbare datahuis houding zorgt voor snellere en betere besluitingvorming bij Otolift

From Data Platform to Data Marketplace: Designing for User Experience

De kunst van Data Storytelling

Data Sharing: Economic Value Across the Automotive Supply Chain, Built on Trust

Met een modelgedreven aanpak, duidelijke architectuur en aandacht voor datagovernance, datakwaliteit en integratie heeft Otolift in samenwerking met Enable U het fundament gelegd voor eenduidige, betrouwbare en continu beschikbare informatievoorziening. Hiermee kan sturing gegeven worden aan de organisatie, is men niet langer afhankelijk van individuele kennis of losse oplossingen en heeft men een schaalbare en beheersbare datahuishouding die de verdere groei en professionalisering van Otolift ondersteunt.

Tijs Rokers

Gert Jan Kentie

Domain Owner Data, Product Owner & Sales AI and Innovation Manager

We create the marketplace, users make it work. A data marketplace only comes to life when people actually use data products—not when they are simply published. In this session, we share how Rabobank moved from a data platform to a true data marketplace by focusing on user experience. By combining producer and consumer research with measurable signals, we identified friction across the full journey and built an evidence-based roadmap to improve adoption and make the marketplace usable at scale.

Hanna Mironchyk Gavin Morgan Lead Data Management Global Data Platform

Area Lead

Waarom leidt zoveel data nog altijd niet tot actie, zelfs in tijden van AI? In deze sessie ontdek je hoe aandacht, interpretatie en vertrouwen bepalen of inzichten echt leiden tot actie. Je krijgt concrete inzichten om valkuilen in datavisualisatie en storytelling te vermijden, beter aan te sluiten op je doelgroep en ook in tijden van AI kritisch te blijven kijken naar data.

Henny Speelman

Data storytelling expert

How does data sharing create economic value? Using automotive supply chains, Mario Holesch (IDSA) shows how shared delivery, quality and scheduling data across supplier tiers as well as company and national borders drive transparency, resilience and predictability, from the Tier-4 supplier to the OEM, with full data control ensured by the IDS standard. The plus: the Data Space Accelerator opens the door to the Catena-X supplier network with speed, support and remuneration for realized use cases.

Mario Holesch

Senior Consultant & Innovation Manager

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

WEDNESDAY 9 SEPTEMBER 2026 HALL 3

10:15 - 10:45

11:00 - 11:30

11:45 - 12:15

12:30 - 13:00

Responsible AI Challenges in Agentic AI

When AI Teaches AI: How RTL Classifies the News

Intelligence at every turn

As AI evolves from passive tools to autonomous agents, the ethical landscape transforms. This session explores this shift from advising to acting, highlighting risks like automation bias and emergent harm in multi-agent networks. We examine delegation limits, regulatory gaps, and how to build the internal governance and oversight needed to deploy agentic AI with true ethical maturity.

At RTL Nederland, we recently migrated our entire data ingestion platform — pipelines, dbt models, orchestration, and tests — spanning multiple repositories and teams. Rather than doing it all by hand, we brought AI into the workflow as a genuine collaborator: one tool to help us write and transform code, and an autonomous agent to review every pull request across the full stack. This talk walks through what that looked like in practice, where AI genuinely saved us time, where it fell short, and what we learned about building an effective human–AI development workflow for large-scale data engineering projects.

Energie Zuinig Rijden: Datagedreven innovatie op het spoor

Yuval Temam

PhD researcher AI ethics

Data Engineer

Rick Stoop

Oracle Cloud is playing a key role in the outcome of every single Grand Prix that we’ve won this year. Curious how the partnership is playing a key role and how AI/ML is used in order to win races and championships? Join us!

Jacco Landlust

Data engineer

CTO Oracle Nederland

13:45 - 14:15

14:30 - 15:00

15:15 - 15:45

16:00 - 16:30

Slaapwandelen in een berekende wereld: Autonomie in het AItijdperk

AI That Delivers - Scaling a Trusted Enterprise Conversational Platform at FedEx

De compliance backlash: wanneer maakt legal innovatie kapot?

When Every Drink is Data: The Hyper-Personalised Workplace is Just One Step Away

Wie zijn AI-strategie overlaat aan de markt, slaapwandelt in een toekomst die door anderen is ontworpen. Veel boardrooms reageren op AI met het haastig najagen van losse experimenten. Maar AI is geen gewone IT-tool; het herstructureert onze oordeelsvorming fundamenteel. Deze sessie is een pleidooi voor bezinning in een berekende wereld. Hoe wíllen we ons tot deze technologie verhouden? Eis de regie op.

Customer expectations have fundamentally changed, requiring enterprises to deliver intelligent, trusted, and seamless experiences at scale. This session explores the journey of designing and scaling an enterprise conversational platform that combines Generative AI, enterprise knowledge, and intelligent workflows. Learn how trust, governance, RAG, and regulatory compliance was built into the platform, along with key lessons for delivering scalable, responsible AI with measurable business impact.

Zelda Zeegers

Docent-onderzoeker

Marius Lupulescu

Deze presentatie laat zien hoe complexe data “eenvoudig” wordt gemaakt en hoe die wordt ingezet om te ondersteunen bij het Energiezuinig Rijden (EZR)programma binnen NS. Een cruciaal moment in het traject was dat we vlak voor de livegang werden geconfronteerd met een volledig redesign van het initiële dataontwerp. In deze presentatie gaan we niet alleen grondig in op de technische aspecten, maar leggen we ook de nadruk op het ontwikkelen van kwalitatief hoogwaardige oplossingen en het samenwerken onder stevige tijdsdruk.

Oracle & Oracle Red Bull Racing

Mayank Kumar

Strategic Planning Advisor

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Een prikkelende juridische sessie over de balans tussen compliance, risicobeheersing en innovatie. Wanneer beschermen regels organisaties, en wanneer staan ze vernieuwing juist in de weg?

Isa Nieuwstad Legal Counsel

Susanna Nijsten Legal Counsel

Your office fridge, coffee machine, and water cooler generate behavioral data every single day.. and almost no one is collecting it. Every drink choice is a signal: energy levels, stress patterns, focus rhythms. In this talk, Orfirah Helstone shows how the most overlooked touchpoint in your workplace is becoming an intelligence hub and how AI, real-time data, and behavioral science are turning hydration into a window into how your people actually feel at work.

Orfirah Helstone Co-Founder & COO

LECTURE PROGRA M HALL 4

10:45 - 11:15

11:30 - 12:00

12:45 - 13:15

13:30 - 14:00

Grip op AI, data en dashboards

De weg naar datagedreven klantwaarde: experimenteren, AI en Customer Lifetime Value bij Greenchoice

Context alleen is niet genoeg. Je AI heeft bewijs nodig.

De race tegen het volle stroomnet

Steeds meer organisaties worstelen met dezelfde vragen: welke cijfers kloppen nog? Wie is eigenaar van data? Hoe voorkom je dat AI een black box wordt? En hoe combineer je innovatie met compliance zonder alles dicht te regelen? In deze sessie ontdek je hoe management grip houdt op data, dashboards en AI zonder te verzanden in bureaucratie. Praktisch, herkenbaar en gericht op bestuurbaarheid: van governance en datakwaliteit tot KPI’s die écht helpen bij besluitvorming.

Hoe gebruik je data science en AI in experimenten om klantgedrag beter te begrijpen voor betere commerciële keuzes? In deze sessie laten Greenchoice, RSM/Erasmus University en Rockfeather zien hoe experimenten, klantsegmentatie, prijsgevoeligheid en Customer Lifetime Value samenkomen om de waardepropositie van Greenchoice niet alleen slimmer te maken, maar ook om beslissingen beter te onderbouwen. Dit draait niet alleen om analyses, maar om het bouwen van een structurele capability. Powered by Rockfeather

Elke leverancier noemt zich nu de contextlaag. Gartner voorspelt dat organisaties die dit goed regelen tot 2027 tot 80% nauwkeurigere AI-agents krijgen, tegen lagere kosten. De vraag die overblijft: kun je bewijzen dat een cijfer nog klopt, of leg je alleen uit wat het ooit betekende? Ik laat het live zien met open Nederlandse voertuigdata. Een AI-agent krijgt een verkeerd geïnterpreteerd veld voorgelegd, zonder context. Je ziet wat er misgaat. Dan laat ik zien wat er verandert zodra herkomst, actualiteit en kwaliteitscontrole automatisch meekomen uit de pijplijn, met Timextender, in plaats van los bijgehouden in een Excel-sheet die niemand meer opent. Voor het team van twee of drie man dat dit moet regelen zonder eigen governance-afdeling.

De energietransitie versnelt en daarmee wordt het elektriciteitsnet steeds zwaarder belast. De vraag naar elektriciteit groeit sneller dan ooit, én het aanbod van groene stroom ook. De piekbelasting van het net neemt daardoor steeds verder toe. In steeds meer regio’s zien we dat netcapaciteit een beperkende factor wordt en dat keuzes onvermijdelijk zijn. In deze sessie nemen we je mee in de “race tegen het volle stroomnet” een uitdaging waarin techniek, operatie en data samenkomen. De groeiende schaarste in het energienet zorgt voor concrete knelpunten en nieuwe vormen van congestie. Niet alles kan meer tegelijk, waardoor het steeds belangrijker wordt om scherp te bepalen waar je wél op stuurt en hoe je de beschikbare capaciteit zo slim mogelijk benut.

Louis de Roo

Data Strategy Leader

Michiel van der Aurélie Lemmens Hoogleraar Customer Meij Senior Retentie Marketeer

Analytics

Alex van Wijnen

Marcel van Munster

Field CTO at Timextender

Manager Risico, Portfolio & Demand

Bram Zentveld Consultant Data & Analytics

14:15 - 14:45

15:00 - 15:30

15:45 - 16:15

16:30 - 17:00

Data Act: de ACM over kansen voor Europese Cloud

AI werkt pas als mensen het gebruiken. Hoe krijg je dat voor elkaar?

Content as a Service at bol: how all bollers can create on brand content at scale with AI

Is uw organisatie klaar voor AI? Begin bij uw data

Tijdens deze presentatie vertelt de ACM over de kansen die de Europese Data Act met zich meebrengt voor Nederlandse Cloud gebruikers en aanbieders.

Voor iedereen die AI binnen de organisatie niet alleen wil introduceren, maar ook écht wil laten landen in het dagelijks werk.

Organic search is under pressure. At the same time, customers increasingly expect relevant and tailored experiences. As a result, organisations are challenged to create more on-brand content, for more audiences, across more channels than ever before. But budgets and capacity don’t grow at the same pace. In this talk, we share bol’s journey from isolated AI experiments to Content as a Service: bol’s self-service tool that helps teams create on-brand content at scale with AI. We’ll take you through different content types, from on-brand copy and images to complete web pages.

In deze sessie neemt Steven Vlaanderen Oldenzeel u mee in de reis van een versnipperde dataomgeving naar een fundament waarop AI verantwoord kan worden ingezet. Aan de hand van actuele voorbeelden laat hij zien welke vragen organisaties eerst moeten beantwoorden en waarom een heldere datastrategie onmisbaar is.

Mark Schep

Founder at Mark Your Data - Data & AI consultancy for growing companies

Rex Leijenaar

Manager Telecom & Digitaal

Romaike Middendorp

Senior Data en AI consultant

Marten Hiensch Senior AI consultant

Benjamin van Vianen

Manager Scalable Content & Tooling

Joey Man

AI Growth Designer

Steven Vlaanderen Oldenzeel

Chief Marketing Officer / Dynamics 365 Expert

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Catch it in action at booth

#82

Turn big ideas into bigger impact with

Een sterke IT-basis. Veilig, schaalbaar, altijd in control. Previder levert de betrouwbare en toekomstbestendige IT-omgeving die jouw organisatie laat groeien.

Infrastructure

Cloud

Workplace

Security

De data & AI partner voor jouw bedrijf Victa zet data om in heldere inzichten, dashboards en AI-oplossingen waarmee je betere beslissingen neemt en jouw organisatie verder laat groeien.

Data Analytics

Victa en Previder helpen organisaties IT, Data en AI samen te brengen.

Data Management

Data Science & AI

Business Consultancy

Data Expo 2026 Bezoek Previder en Victa op stand 140

LECTURE PROGRA M HALL 5

10:15 - 10:45

11:00 - 11:30

11:45 - 12:15

12:30 - 13:00

Hoe je een datastrategie maakt die niemand gebruikt

560 startups, 1.024 founders, miljarden aan funding: de onzichtbare Nederlandse AI startup sector

Driving AI Transformation: Lessons from scaling Copilot M365 at ING

Implementing Data Mesh and AI @ Alliander Building the Grid of the Future

Een datastrategie maken is geen rechte lijn. In deze sessie deel ik mijn persoonlijke reis bij de Gemeente Amsterdam: de fouten die ik maakte, de lessen die ik leerde en hoe we een strategie ontwikkelden die data, informatie, AI en digitale autonomie samenbrengt. Ik vertel over de strategische dilemma’s van de Gemeente Amsterdam, die hebben geleid tot de pijlers van de nieuwe datastrategie.

Joep Steenbeek

Deze presentatie neemt je mee langs de staat van de Nederlandse AIstartupsector: honderden bedrijven, meer dan duizend founders en miljarden aan funding.

Willem Blom

Hoofd Data Office

Founder

From proof of concept in 2024 to broad rollout in 2026, Microsoft 365 Copilot at ING evolved from an experiment into a new way of working. In this session, we share how we actively drove this AI transformation, translating Copilot into concrete, high-impact use cases. We cover what worked (and what didn’t), how we made adoption measurable, and the change management approaches that helped embed this shift in everyday practice.

Timothy Dieduksman

Annemarie Quik

Sr. Data Strategy & Analytics Consultant

Manager Data Analytics

We show how Alliander combines and executes a forward-looking vision with a modern data and AI architecture. By adopting a Data Mesh approach and the Enterprise Publication Layer (EPL), data is shared as reusable products through a self-service platform with built-in governance. AI is embedded in daily operations, from grid prediction to GenAI, always guided by responsible AI. Together, these presentations show how Alliander is preparing the energy sector for massive change.

Sander de Wildt Data & AI Architect

13:45 - 14:15

14:30 - 15:00

15:15 - 15:45

16:00 - 16:30

Keeping control of AI at scale: Runtime Governance at Healthtech myTomorrows

AI4Data: What is an AI-augmented Data Engineer?

Easy start to data prompting

Tussen datastortplaats en goudmijn: grip op ongestructureerde data

myTomorrows supports patients finding and accessing other options when standard of care no longer suffices, in a sector where AI and regulation are becoming ever more intertwined. General Counsel Janiek Meppelink and Deeploy CEO Maarten Stolk share how a regulated scale-up deploys AI without compromising on compliance. From EU AI Act requirements to governance in practice: concrete lessons for anyone scaling AI in a regulated environment.

Maarten Stolk Janiek Meppelink CEO

General Counsel

The successful applications of LLMtechnology to automate all kinds of manual tasks are manyfold. This is what we call AI augmentation: human workers augmented with GenAI-technology. In this presentation, we zoom in on the AI augmentation of data engineering that can be achieved with existing tools and frameworks. We show examples of how they can be used in practice to optimize your data engineering workflow. We also discuss lessons learned from our own experiences and projects.

Petra Heck

Associate Lector

Data prompting often comes as a fantastic features of enterprise level analytics software, and the golden standard requires rigorous data infrastructure and an in depth semantics layer to get accuracy. Using Claude we challenged whether this setup is necessary and if data prompting is possible without the large overhead.

Lukas Michalitsch Head of Data

Ongestructureerde data groeit explosief, ook in samenwerkomgevingen. Slimme zoektechnologie en generatieve AI maken die informatie waardevoller dan ooit. Maar hoe voorkom je een digitale stortplaats vol doublures, overbodige bestanden en privacyrisico’s? In deze sessie laat Nico Nijenhuis zien hoe VGZ toewerkt naar een beheerde digitale samenwerkomgeving: vindbaar, bruikbaar en verantwoord.

Nico Nijenhuis

Data Governance Specialist

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

WEDNESDAY 9 SEPTEMBER 2026 HALL 6

10:45 - 11:15

11:30 - 12:00

12:45 - 13:15

13:30 - 14:00

Running AI on your own infrastructure

Hello? It’s AI: Smarter Conversations Start Here

Curious about what it really takes to run modern AI without depending on external providers? This session takes a practical look at self-hosting Large Language Models and AI-powered applications. We’ll discuss the current open-source ecosystem, infrastructure choices such as using a Mac, Spark or AMD, inference performance (and the costquality tradeoff), model orchestration, security considerations, and common pitfalls. Rather than focusing on theory or vendor offerings, the session is built around real-world examples—including several applications running on the Infinity platform—to illustrate how these technologies can be deployed and used in production.

Join ABN AMRO as we take you behind the scenes of building a speech-tospeech GenAI voicebot designed to deliver natural, human-like customer interactions. We’ll walk you through the full journey—from defining the use case and designing the architecture to implementing real-time voice capabilities with optimized latency. You’ll also gain insight into the guardrailing strategies that ensure safe and reliable responses, as well as how we measure performance and evaluate real-world outcomes.

Next Level Data Strategy: Building Your Data Foundation for the AI Era

Context als bedrijfskritische asset: van eigenaarschap tot AI skill

Every AI initiative depends on the data underneath it. In this session, Informatica’s Community of Practice Director shows how to move from scattered data efforts to a working data strategy, built live with visitors using an AI-powered facilitation approach. See how Guiding Principles, Business Goals, Use Cases and Data Capabilities come together fast, and how it all connects to real AI value.

Een lijst met masterdata waarvan niemand meer weet welke bron leidend is. Een flowchart die niemand meer snapt, omdat de kennis alleen in het hoofd van de maker zat. Een discussie die elk half jaar terugkeert over wat een “lead” precies is. Herkenbaar? Kennis zit versnipperd in hoofden, documenten en verouderde overzichten. Dat kost tijd, vertrouwen en grip. Spreash® brengt dit samen in één digitale blauwdruk: de actuele waarheid van de organisatie, met definities, processen, metadata, eigenaarschap en systemen.

David Kun

Amanda Ferraboli Julia Meuffels

Data Scientist

Barry Wildhagen

Community of Practice Director

14:15 - 14:45

15:00 - 15:45

16:00 - 16:30

Hoe Schoonenberg marketing en operatie aan elkaar koppelde met data - en waarom dat meer opleverde dan meer campagnebudget

Hoe GGN met RegelRob betalingsregelingen sneller, consistenter en socialer beoordeelt

AI-powered credit scoring to bring financial inclusion across emerging markets

Schoonenberg genereerde met 150 winkels volop leads, maar betaalde Google en Meta om zijn eigen wachtlijsten te verlengen. Door wachttijddata te koppelen aan conversie ontdekten we een harde wetmatigheid: voorbij een bepaalde grens halveert de kans op verkoop. De oplossing was geen beter campagnemanagement, maar een automatisch sturingsmechanisme dat marketingbudget koppelt aan actuele verwerkbaarheid per vestiging. Resultaat: lagere kosten per sale, hogere voorspelbaarheid van omzet.

Edward Stapel Head of Digital Advertising

Data Scientist

Remy da Thesta Jacobs de Bok Senior Digital Marketing Manager

Met RegelRob laat GGN zien dat je met AI sneller, consistenter en socialer regelingen kan beoordelen. Een classifier haalt regelingsverzoeken automatisch uit de datastroom van post, telefoon, e-mail en portal. RegelRob beoordeelt ze vervolgens op contract, vordering, betaalhistorie en dossiercontext. Dit is als advies, niet als beslissing. Alles draait op een eigen AI-computer, voor maximale privacy en regie. Een praktijkcase over Agentic AI, governance, uitlegbaarheid, menselijke controle en sociaal rendement.

Across Sub-Saharan Africa, smallholder farmers feed the continent — yet most remain invisible to the financial system. Too small for banks, too risky without collateral, too dispersed to reach: they are locked out of the credit that could transform their livelihoods. In this talk, Dario shares how Emata is rewriting that story. By embedding lending directly into the agricultural cooperatives and value chains farmers already belong to, Emata turns internal and external data — milk deliveries, satellite data, loan allocation and repayment patterns — into a foundation for trust and fair financing.

Arjen Houweling

IT en Innovatie manager

Kees Nooijens Business Analist

Jeandre Knox Developer

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Dario Raffaele Chief AI Officer

Fleur Bake

Founder/CEO

Amber Hentschke

Enterprise Architect

LECTURE PROGRA M HALL 7

10:15 - 10:45

11:00 - 11:30

11:45 - 12:15

12:30 - 13:00

How KNB is using AI without giving away control of their data

Van Dorp Vernieuwt - IT voor Morgen

Privacy in the Sprint

From Strategy to Impact at Scale: PGGM’s Data Mesh Journey

AI is creating new opportunities for organizations, but also new questions around data control, sovereignty and vendor dependency. The Koninklijke Notariële Beroepsorganisatie (KNB) faced a challenge many organizations recognize: how do you unlock advanced analytics and AI capabilities while retaining control over where your data resides, who can access it, and under which laws it falls? In this session, KNB shares the challenges, decisions and lessons learned from building a modern intelligence platform that supports analytics and AI without compromising on governance, sovereignty, and future flexibility.

Hoe IT, data en AI Van Dorp in staat stelt om te vernieuwen. Ontdek de reis van lokale lijstjes en versnipperde data naar realtime inzicht, AI-agents en een datagedreven organisatie.

Privacy often shows up when a data project is already moving fast and that is usually when it starts to slow things down. This session shows how privacy principles can become part of everyday routines, so teams can avoid last-minute issues and keep projects moving.

PGGM chose Data Mesh as the foundation of its Strategy 2030 to scale trusted, domain-driven data ownership across the organisation. PGGM is operationalising federated data governance, certified datasets, and data products to improve data quality, trust, and decision-making in a complex regulated environment.

Wouter Siepman Business Architect

Kai Van den Berg Codrin Kruijne Consulting Partner (Gen)AI Solutions

Michael Doves Managing Partner

Ronnie Hollemans

Chief AI / Manager Data eXperts

Directeur IT

Bram Hoovers Director Legal

Remy Van der Vlist

Senior Data Governance & Data Quality Officer

Frank Gresnigt Director

13:45 - 14:15

14:30 - 15:00

15:15 - 15:45

16:00 - 16:30

AI-gedreven planning: van handmatig bellen naar één tap — live in twee weken

From Data Chaos to Data Excellence: Creating Scalable, Secure and Valuable Data Products

Ideate First: Converging on the Right Problem Before Building Solutions

From Tools to Teammates: Agentic AI needs Hybrid Intelligence

Data and AI teams are often eager to start building. A new technology emerges, an exciting idea surfaces, and before long a project is underway. Yet many initiatives struggle to deliver the expected value, not because of poor implementation, but because insufficient attention was given to understanding the problem being solved.

The current AI revolution envisions a world of “agentic” workflows, where AI agents collaborate seamlessly to solve complex tasks. However, the focus on autonomy overlooks a critical ingredient: us. We will discuss that the future of agentic AI belongs to Hybrid Intelligence: redefining AI from an isolated tool to a collaborative teammate. Keeping humans in the loop is indispensable: to unlock the implicit, undocumented knowledge that lives only in our minds, to build genuine trust in automated outcomes, and to ensure deep alignment with complex ethical and cultural standards. We will discuss how to design humanAI ecosystems that elevate machine capability while actively preventing human deskilling.

In twee werd een AI-gestuurde OutSystems-app gebouwd die 120 planners elk 30 minuten per week bespaart. De AI Workbench Agent genereert direct een ranked shortlist op basis van beschikbaarheid, afstand en vaardigheden — zonder verstoring van bestaande systemen. Een praktijkverhaal over snelle AI-adoptie, human-in-theloop design en pragmatisch innoveren in een operationele omgeving.

How KPN data was transformed into a strategic business asset using a shift-left approach and an operational model for scalable, reliable, and AI-ready data products. Powered by Systemation

In this session, the Ideate First approach is introduced as a way of exploring opportunities before committing to solutions. It is demonstrated how movement from assumptions to insights can be supported through structured ideation, and how divergent thinking can be used to create a broader understanding of both problems and opportunities before convergence takes place.

Thierry Bontinck IT Manager

Patrick de Vries KPN

Paolo Platter Witboost

Branka Milivojevic AI & Data Advisor

Prof. Frank van Harmelen

Prof. Catholijn Jonker

Principal Investigator Professor of Interacive Intelligence

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

WEDNESDAY 9 SEPTEMBER 2026 HALL 8

10:15 - 10:45

11:00 - 11:30

11:45 - 12:15

12:30 - 13:00

Synthetische data: nep, maar toch bruikbaar

Van Steekproef naar 100% Scan: Hoe Altrecht GenAI Inzet voor Goede Dossiervoering

Navigating through the protein engineering landscape with automated benchmarking

Migrating a DWH, Live on Stage in Less Than 30 Minutes

Het lijkt tegenstrijdig: volledig verzonnen data die toch nuttig is in praktische toepassingen. Er zijn veel situaties waar synthetische data kan worden toegepast. In deze presentatie vertelt Freek Bomhof van TNO welke soorten toepassingen er allemaal zijn. Ook wordt ingegaan op het maken van synthetische data, wat het aanbod is, en hoe je de kwaliteit van de data zo goed mogelijk kunt bepalen.

GGZ-instelling Altrecht laat zien hoe GenAI helpt om datakwaliteit en compliance structureel te verbeteren. Door taalmodellen in te zetten die context en nuance in patiëntdossiers begrijpen, kunnen afwijkingen eerder worden gesignaleerd en wordt dossiervoering consistenter. Zo verschuift de controle van steekproefsgewijs naar continu en draagt AI bij aan first time right registratie en declaratie. Privacy, security en governance zijn hierbij vanaf het begin leidend. Ontdek hoe Altrecht GenAI van experiment naar productie bracht en welke lessen deze aanpak biedt voor andere organisaties in sterk gereguleerde sectoren. Powered by Xebia

Freek Bomhof

Kasper van Mens Jelle Witteveen

program director AI

Sr. Data Scientist

Innovator & Google Cloud Expert

From bioethanol to laundry detergents, the biotech industry is developing enzymes that make everyday processes greener. During enzyme development, we engineer specific mutations to obtain desired properties, nowadays, often with the use of machine learning (ML) methods. However, it has become increasingly difficult to track which models perform best for our property of interest. Together with IFF, the Marks lab and Xebia, we developed a community driven framework that makes benchmarking as simple as a pull request. We present two packages to facilitate that process, proteingym-base and proteingym-benchmark. In proteingymbase we standardize the collection of biochemical data modalities into a single data-science ready archive, while proteingym-benchmark provides the setup for automated model benchmarking.

Shu Zhao AI Engineer

Karel van der Weg IFF

Legacy data warehouse migrations are typically slow, manual, and risky. This talk explores how agentic AI changes that. In this talk we will explain how agents can support a migration end to end, then walk through a live example: migrating a legacy DWH to a modern platform on stage. We’ll show how a readiness step inventories the existing system and flags challenges upfront, and how a migration step then takes that inventory and deploys specialized agents to convert the code, achieving 100% schema and logic migration up to 60% faster than traditional approaches. Alongside the demo, we’ll share examples from real projects to show how this plays out beyond the stage.

Niels Zeilemaker

Global CTO Data & AI

13:15 - 13:45

14:00 - 14:30

14:45 - 15:15

15:30 - 16:00

When the Business Case Isn’t the Law: Building Fraud Risk Intelligence Beyond Compliance

AI That Ships: Field Notes

How Erasmus Migrated T-SQL to dbt on Databricks: AI-Assisted Migration with Lakebridge

From Data to Opportunity: Uncovering gaps in the mar ket with Multi-Agent AI

Verification of Payee (VOP) is the overlay service for credit transfers in which the input beneficiary is checked against the actual account holder. It has been our bread and butter from day one. Every EU bank had to implement VOP, the regulation made the business case for us. When VOP became mandatory, adoption was guaranteed. Fraud prevention isn’t. This session shows how we’re building a Fraud Risk Intelligence platform on top of existing VOP infrastructure, reusing verified account data, adding third-party sources, and using AWS-based ML to turn a compliance layer into real risk intelligence banks choose to adopt.

Most AI work in companies falls into three buckets. Productivity tools that speed up tasks, rebuilds of things you already do, and things that were not possible before AI. Each needs a different budget, a different timeline and a different definition of success, and companies routinely mix them up. That is how a crowded pipeline gets mistaken for transformation. I will go through what each bucket actually returns, what has to change for those returns to show up, and why most of the difficulty turns out to be organisational rather than technical. Field notes from real projects and deployments, not another transformation framework. Powered by Xebia

How do you rewrite ten years of SQL Server logic as dbt models on Databricks? In this session, Erasmus and Xebia show how they built a migration pipeline on Lakebridge, the open-source transpiler from Databricks Labs, running entirely inside Erasmus’ own Databricks workspace. AI translates the views, stored procedures and functions; engineers review every model before it ships. You’ll see the pipeline in action, the actual numbers on cost and speed, and what it takes to apply the same approach to your own migration. This is not about replacing engineers with AI, but about letting them spend their time where it counts.

How do you uncover new commercial opportunities in a market full of products, trends, and data? dsm-firmenich, together with Xebia, developed the Market Insights Analyst: an AI-powered solution that uses multiple AI agents to analyze market and product data to identify promising whitespaces. In this session, dsm-firmenich and Xebia will show how a multi-agent approach can support complex market analysis, connect product portfolios to global trends, and uncover opportunities that might otherwise remain hidden. Discover how an initial AI prototype evolved into a scalable solution for market intelligence — and the key lessons learned along the way about data, technology, adoption and bringing AI into production. Powered by Xebia

Friso Schutte CEO

Sinan Calisir ML Engineer

Dmitri Jarnikov

Senior Director of Data Science

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Ellen van Bergen Murat Can Cakir Data Platform Lead

Senior Data Engineer

Soraya Duriez Michele Marchini

Digital Customer & Consumer Insights Expert

Global Business Insights Director

PROGRA M ROUNDTABLE

10:30 - 11:15

11:30 - 12:15

12:20 - 13:05

13:15 - 14:00

14:15 - 15:00

15:15 - 16:00

The Skills of Tomorrow’s AI Workforce

De Dataverordening (Data Act) en de AVG: tussen toegankelijkheid en privacy van data

The Hidden Layer of AI: What Does It Take to Trust AI at Scale?

Integratie als Bedrijfsfunctie: Betrouwbaarheid, Kwaliteit en Ownership

AI‑agents: voorbij de hype, met zichtbare grip

Beyond the Pilot : What Makes AI Projects Actually Work

What will tomorrow’s AI workforce look like? Each year, as a private training provider, we research the latest developments in Data and AI. This roundtable builds on last year’s findings and connects them with insights from professionals facing these challenges every day. Discover which skills will matter most in the next two years, when to hire versus upskill, and how organisations build future-ready capabilities. For L&D leaders, hiring managers, and decisionmakers shaping their teams.

Hoe geef je toegang tot data en zorg je tegelijkertijd voor zorgvuldige bescherming van persoonsgegevens? In deze rondetafelsessie gaan de ACM en AP met jou in gesprek over de interactie tussen de Data Act en de AVG.

Organizations are investing heavily in AI, yet many struggle to turn promising initiatives into trusted business outcomes. Is the missing piece really the model, or is it the business logic that defines how organizations actually operate? Join this interactive discussion to explore the hidden layer of enterprise AI and exchange experiences with fellow Data and AI leaders.

Waarom blijven organisaties worstelen met datakwaliteit en vertrouwen in data? Tijdens deze sessie bespreken we hoe governance, eigenaarschap en integratie samen de basis vormen voor een solide datafundament.

AI‑agents duiken inmiddels op in Copilot Studio, Power Platform, SaaS‑oplossingen en eigen LLM‑platformen. Ze beloven versnelling in processen en besluitvorming, maar creëren tegelijk een nieuw bestuursthema: wie is verantwoordelijk voor wat deze autonome “digitale collega’s” doen met data, processen en budgetten, en hoe houden we het geheel bestuurbaar zodra het schaal krijgt?

Join Marie Fenner from Piano for a roundtable on what actually makes a data and AI project work. We’ll dig into data, semantics, context, and culture - the parts that get skipped in the slide deck version. Bring your questions, or your own war stories.

Alma Joy Ridderhof

Coördinator Data Economie

Olivier van Hees Founder

Natalia ToeajevaElseman

Senior Inspector and Data Act Coordinator

Florian Carrier

Strategic Solution Consultant

Stipo Jelec

Business Consultant & CISO

Dennis Hoogenraad

Senior Solutions Consultant

Marie Fenner

Global SVP, Analytics

Begin...

...met groeien Start als Developer bij ABN AMRO en begin met groeien. Groeien in je werk is vreugde en frustratie. Tuimelen en vliegen. Kabbelen en pieken. Maar nooit een rechte lijn omhoog. Daarom krijg je er bij ons alle ruimte voor. Ontdek meer op werkenbijabnamro.nl

RIGHT NOW, WE’RE MAINLY FOCUSED ON WHAT WE NEED TO BUILD JESSICA RULAND Lead Product Manager | TicketSwap Yes, Large Language Models (LLMs) have significantly changed Product Management at TicketSwap. At the same time, much has remained the same, emphasizes Jessica Ruland of the ticket marketplace. She criticizes claims that Product Managers are becoming obsolete because the technology will take over their work. According to the Product Lead, human thinking and judgment may be more important now than ever before.

“When I open LinkedIn, I come across one doomsday scenario after another about our field,” Ruland sighs in the run-up to her presentation at Data Expo. “Product Management is dead, I read; engineering is dead, and so on. This creates an irrational fear, because thinking can never be replaced.” Much more support

Ruland has been working in Product Management at TicketSwap, the ticket resale platform, for four years now. At the Jaarbeurs, she’ll discuss the changes in her field brought about by LLMs, using concrete examples from the Amsterdam-based company, which now operates in dozens of countries. “Don’t get me wrong: there really is a shift taking place in the industry. But the core of the Product Management process has remained the same: identifying opportunities, validating them, building, and scaling. We’ve just gained a lot more support. LLMs have made our work faster—and therefore more efficient—not necessarily better.”

“The focus is shifting to Product Discovery” From pull to push

LLMs are accelerating data-driven work at TicketSwap, Ruland explains. “When it comes to analytics and experiments, for example, data is scattered across all sorts of different tools, such as Dovetail and Amplitude. Previously, we had to extract data from those tools to be able to do anything with it. Now we use agents that retrieve exactly the requested data from everywhere, consolidate it, and present it. We’re shifting from a ‘pull’ to a ‘push’ model. For me, the added value lies in what this frees up: since we no longer spend most of our time searching for and consolidating data, we can focus on using it—building hypotheses, making decisions, and applying judgment. We’re also using LLMs for validation and decision-making, partly because the pace of development simply demands it.”

Accelerates execution

LLMs have, above all, drastically changed the development process, Ruland continues: “Engineering now happens primarily in

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

collaboration with Claude Code, which makes execution so much faster. Sometimes, within a week of starting, I already have someone at my desk asking, ‘What’s next?’ So we’re spending less time on the actual building and more on what we need to build. The focus is shifting further and further toward the front end of the process, toward Product Discovery. Continuous validation is becoming even more important.”

New solutions

LLMs aren’t just changing the way Product Managers work, according to Ruland— they’re also enabling new solutions for users. “People who want to sell a ticket used to have to manually search for the event on the right date and so on. Now customers can simply upload a ticket, after which an LLM identifies it and posts the listing online.”

Context and taste

Back to the workplace: Ruland wants to counter the narrative that AI makes jobs obsolete. She explains:“The question of what we should build has therefore become more important: does a solution truly align with what the user needs, what the market demands, and what TicketSwap stands for?

JESSICA RULAND WILL SPEAK ABOUT PRODUCT MANAGEMENT AT TICKETSWAP. DON’T MISS IT!

Lecture hall 7

Making sound decisions on these three points requires judgment. Context and taste come into play here, and you can’t leave that up to technology.” She clarifies this with an example: “A partnership with (competitor, ed.) Ticketmaster was suggested to us, but given the context, we wouldn’t be quick to do that.” Another example: “AI helps categorize certain events, but that’s a delicate balance. For example, we deal with events featuring tribute bands and artists. If we’re not careful, we could end up sending out push notifications saying, ‘2Pac is performing!’” The rapper has been dead for nearly thirty years. When it comes to taste, Ruland is referring to the ability to sense what the right product is at the right time—for the user, the market, and the company’s strategy. “That’s not something you can always back up with data, and that’s exactly why an LLM can’t take over.”

Thursday

15:15 - 15:45

The Product Manager of 2026

What qualities must a good Product Manager of 2026 possess? Ruland pauses to think for a moment and then says: “Asking the right questions—that’s truly decisive these days. When it comes to validation, it’s even more important that you make the right decision.” It all comes down to filtering—separating the wheat from the chaff. “You shouldn’t take everything at face value, and above all, you need to be aware of what you don’t know. The age-old adage ‘garbage in, garbage out’ certainly applies in the age of AI as well.” There’s a risk that companies will rush to build solutions that nobody wants, notes TicketSwap’s Product Lead. “We don’t yet fully understand the damage this could cause in the medium term, but I don’t want to underestimate it.”

Doing more independently

Another consequence of the rise of LLMs is that product managers and designers are increasingly taking on some of the engineers’

roles. “I’m able to do more and more on my own within the process of brainstorming, developing, and validating,” says Ruland. “We’re working on being able to set up experiments on our own, without engineers. That way, we can create the first versions of solutions, build prototypes, and test them. The roles are becoming much more fluid. When you scale up, of course, you absolutely need engineers. I’m convinced that all existing areas of expertise within the product development cycle will remain necessary, even five years from now. The best people have the skills to contribute to the entire cycle.” At Data Expo, Ruland will use concrete examples to illustrate that while much has changed in her field, much has also remained the same.

“LLM’s hebben Product Management sneller gemaakt, niet per se beter”

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

BECOME A SPEAKER AT DATA EXPO!

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DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

HUNGRY FOR MORE DATA & AI INSIGHTS? Why should you treat an AI agent exactly the same as a new employee?

Edge AI keeps sensitive data closer to home

Multi-agent, multi-modal AI: The Rise of Digital Colleagues

One definition of revenue. Even for your AI agent.

The dashboard is green. The debtor isn’t.

A good AI model is not yet a good AI assistant

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AI IN PRACTICE: FROM SILVER BULLET TO SUSTAINABLE IMPACT Based on our hands-on experience at BearingPoint, this article shares what it actually takes to make AI work in large, complex organizations.

The promise

Artificial intelligence (AI) has rapidly evolved to become the most talked-about commodity in enterprise technology. The promise is compelling: smarter decisions, faster processes, unlocked insights from decades of accumulated data. For large and complex organizations, the potential may feel limitless, and in many ways, it can be. But potential and reality are not the same thing. When we discuss the topic with our clients for the first time, the expectation is often that AI is a silver bullet. A single initiative that will compensate for employee shortages, modernize operations, cut costs, and deliver competitive advantages all at once. While that ambition is healthy, it tends to skip the question that matters most: what does it actually take to get there? Rather than adding to the hype, we try to answer that question as practically as we can, based on our own experiences in the field.

Infinite possibilities - right?

Our clients are often excited about AI’s possibilities, but when we ask what they’ve considered using, the answer is almost always Copilot or ChatGPT. That’s understandable. AI entered the mainstream through chatbot interfaces, so it is only natural that this is where our thinking starts and stops. The result? Companies invest in expensive licenses for conversational AI without a clear picture of what their actual use cases look

like and are disappointed when impact does not follow. We recommend flipping the approach. Start by mapping your use cases, not your tools. What are the problems you’re trying to solve, and what does each one actually require? Stay technology-agnostic at this first stage. Some of those problems will turn out to be excellent fits for a solution depending on AI. Others won’t, and believe it or not, that is a good thing. If a problem can be solved without AI in a deterministic manner with strict business rules, structured workflows or traditional automation, that path will give you more stable quality, better auditability, and lower costs. It also forces you to formalize domain logic which is something you should be doing for AI regardless. In the AI world, this is known as ontology building, and it is one of the most valuable foundations you can lay. So what does a strong AI use case actually look like? • Critical organization knowledge is buried across decades of unstructured documents, making it difficult to find and reuse. Using a Retrieval Augmented Generation (RAG) pipeline you can enable employees to ask query and retrieve source-grounded responses to company specific content. Depending on what you need the knowledge for you may need to consider very different interfaces. • Business users depend on BI teams for data access, creating delays between

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

questions and insights. Using AI-powered self-service analytics on structured data users can “talk” to their data to generate reports and explore trends without technical skills. • Processes stall at steps requiring human judgement limiting automation and creating bottlenecks. Using AI to interpret documents, classify inputs, and handle exceptions with a human-in-the-loop (HITL) workflow design boosts efficiency and quality.

Turning a use case into a success: you need strong shoulders to build on

Once you’ve identified the right use cases, the next question is whether your organization is ready to support them. AI demands investment across the board, not just in technology, but in the work you do to improve quality, build trust, and ensure continued usage.

Data readiness - why it’s the bulk of the work

Data readiness is the AI enabler most organizations underestimate. To give an idea of what questions you should be considering: Are you working with a central data platform or are there many separate applications which require custom connectors? Are people from operations updating data records frequently enough to provide timely insights? Are metadata labels assigned correctly and consistently throughout the 20+ year lifetime of the source system?

This blog is contributed by

Our answer is honest. We can dream big together, but we’ll assess the data landscape and tell you what’s achievable now and what requires investment to unlock later. The good news? In most cases we can already take the first steps together with what is within reach. What surprises many organizations is how comparatively little effort is put into configuring the AI itself. Configuring the AI model or agent is rarely the bottleneck. Preparing, structuring, and connecting data so it can be queried efficiently, that is typically the bulk of the work in our sprints. Data pipelines, access governance, metadata enrichment, document ingestion: these aren’t glamorous, but they are the foundation everything else stands on. If you completely skip this step or fail to continue building your foundation as you scale your AI, you are building your solution on quicksand.

Governance – the question nobody asks early enough Our director said it well: AI governance is about safeguarding the quality of output over time. The technology is secondary.

Before go-live, every organization should answer a simple question: who owns this after we leave? Modern platforms offer built-in dashboarding, logging, and evaluation metrics. We can build monitoring and reporting into anything we deliver. But a dashboard without an owner is just a screen nobody watches.

That owner needs more than access, they need influence. The power to flag declining output quality, to advise on retraining or adjustment, to say “this process needs attention” and be heard. Organizations that don’t think about this upfront end up with AI solutions that quietly degrade until someone notices the hard way.

This approach takes time, and that is where the tension lies. The pressure to deliver fast collides with the reality that good AI demands deep understanding of the business. We recommend not rushing this phase. If you do, you risk ending up with just another chatbot, and your users will treat it accordingly.

These are just two of the enablers we encounter most, there are others. But don’t wait for perfect conditions. AI is a capability you build. Find the cross-section of use case and readiness that’s “good enough” to start and let the work teach you where to invest next.

Conclusion

Building your tool

Consider a reporting process at Company X. The tempting approach is a chat-based AI that generates full reports in “one go” from user prompts. Perhaps it is even backed by RAG, but it is still detached from how the business really works. A better approach is to break the process into steps: defining scope, applying methodologies and relevant frameworks, retrieving information, drafting, and reviewing. Subsequently, design the solution so each step is a distinct, AI-supported but human-controlled interaction. For example, let AI suggest relevant sources, while the user validates and adjusts before moving forward. The result is trust, better quality and higher efficiency as the AI takes care of the bulk of the work while complementing users in their native way of working.

AI is not a silver bullet, but it is not just a buzzword either. It is a capability you build use case by use case, sprint by sprint, with the right foundation underneath it. The organizations that succeed are the ones that start with a clear problem, invest honestly in their data readiness and people, and resist the urge to skip straight to the demo. That is how AI moves from promise to practice, and from a one-off experiment to sustainable impact. This article reflects the hands-on experience of BearingPoint applying AI in large, complex organizations. It’s not about the latest frame work release, it’s about what’s actually possible, and how they help their clients get it done. Curious how this applies to your organization? Come talk to BearingPoint at Data Expo 2026, find them at their stand or during one of the roundtable sessions. They’d love to explore what AI can realistically do for you. You can also visit www.bearingpoint.com.

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

THURSDAY 10 SEP TEMBER 2026 Keynote Page 38-39

10.45 - 11.30 False Clear Ahead - When Agents Derail Your Defenses Rens van Dongen (Nederlandse Spoorwegen (NS))

Hall 1

Hall 2

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Hall 3 Page 44

10.15 - 10.45 Jij bent de x-factor in datamanagement

10.15 - 10.45 Datagedreven werken is en blijft mensenwerk!

Morgan Djotaroeno (Dux Group) Bas Van Gils (Strategy Alliance)

Nico de Roo (UWV)

11:00-11:30 Van complexe tuchtzaken naar bruikbare content: generative AI in de praktijk

10.45 - 11.15 Van flows naar agents: schaalbare AI voor klantcontact bij Univé Merel Derlagen (Digital Power) Ties van der A (Univé)

11.00 - 11.45 Politie bewaakt het Data vertrouwen

Hall 4 Page 45

10.45 - 11.15 Van scale-up naar datagedreven organisatie: de journey van Connex Dane Bakker (Connex)

Oscar Wijsman (Politie) Ruud Staijen (Politie)

Marin Schrijen (Stichting DSI) 11.30 - 12.00 Dynamic Governance for AI Agent Access at Roche

12.00 - 12.45 Enexis: Road to Excellent Data Products Kasper Kisjes (Enexis)

11.45 - 12.15 Van onbeheersbare datagroei naar grip op informatie, samenwerking en governance

Rosie Geenty (Roche) Colin Mitchell (Immuta)

Jan van Dijk (RID-Utrecht) 12.15 - 12.45 From Art to Cart: datakwaliteit als marketinginstrument

12.30 - 13.00 Modernizing Analytics at Odido: Jelle Swaan (Werk aan de Muur) Building the Foundation for AI

12.00 - 12.30 Software modernization: building AI on a system you can’t touch

12.45 - 13.15 Iedereen wil iets met AI. Maar is jouw organisatie er klaar voor? 13.00 - 13.30 Louis de Roo (E-mergo) Bridging business & technology: preparing brands for the Agentic Era

13.15 - 14.00 Building AI workstations for data & analytics engineers: Follow Kramp’s journey

Marjolein Jongbloed (Datalab) 13.30 - 14.00 Hebben we straks nog een baan? AI en de toekomst van werk 13.45 - 14.15 AI bij Riksja Travel: wat je realiseert als je carte blanche krijgt Rutger Fokke (Riksja Travel) Sabine Vroemen (Riksja Travel)

14.30 - 15.15 Agents of Change: Scaling Smarter AI in HR Martin Woodward (Randstad) Erwin van der Meulen (Randstad)

14.30 - 15.00 AI governance in a fragmenting world: Compliance as strategic control

Bas Schnater (Under Armour)

Tor Boe-Lillegraven (Eneco)

Judith von Reeken (SeederDeBoer)

14.15 - 14.45 From data platform to AI platform: how Winparts prevents returns with data & AI Harm Albers (Winparts) Mark Schep (Mark Your Data) Rense van der Zee (Winparts)

Cassandra Moons (TomTom)

15.15 - 15.45 How analytics guides a challenger sports brand

15.45 - 16.30 AI Agents: The Rewards, the Risks, and the Realities

15.00 - 15.30 De superhuisarts bestaat — zo werkt AI als stille klinische partner in de eerstelijnszorg Emma de Ruiter (Stichting Health Base) Marijn Zeemeijer (Stichting Health Base)

13.30 - 14.00 Waarom je model niet gebruikt wordt: lessen uit netregisters 13.45 - 14.15 Tussen datastortplaats en goudmijn: grip op ongestructureerde data Nico Nijenhuis (Coöperatie VGZ UA)

14.30 - 15.00 Hoe selecteer je het meest waardevolle AI-project? Maartje Vennema (Chief AI Officer Academy)

Pascal Reijers (Alliander) Alex Doeves (Alliander) Joris Schut (Bearingpoint)

14.15 - 14.45 Het datamarketingteam van morgen: wat AI vraagt van mensen, teams en organisaties Brenda van den Berg (KPN) Monique Hartvelt-Zwanenburg (Achmea)

15.00 - 15.45 A.I., intelligentie en jouw baan 15.15 - 15.45 Architecting AI Agents in Production: Insights from Philips Hue

Michel van der List (Interpolis)

Mohamed Elkady (Signify) 15.45 - 16.15 Data spaces voor het Digitale Product Paspoort (DPP) Eva Koenders (Hogeschool Arnhem Nijmegen)

16.00 - 16.30 Scalable AI Impact: From Trusted Data Sharing to AIReady Companies Anil Turkmayali (International Data Spaces e. V.)

Yıldırım Umut Doğancı (havelsan)

Kishan Chamman (Eli5) Floris Schoenmakers (Eli5)

Johan Maat (Odido)

Oliver Meisch (Kramp)

11.45 - 12.15 Building the Data Foundation for a Nation-Wide AI Infrastructure

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

16.00 - 16.30 The Winning Number Game Jop Beuger (Jop Beuger)

LECTURE PROGRAMMA Hall 5 Page 47

Hall 6 Page 48

10.15 -10.45 Het Sensire Informatiehart: AIinnovatie en eigen regie in de zorg

Hall 7 Page 49

10.15 - 10.45 The AI Act in Action: What You Need to Know About Transparency

Jan Willem Tiemessen (Stichting Sensire) Selim Dogan (Signify) Dave Hamersma (Stichting Sensire) 10.45 - 11.15 Hoe MKB Brandstof AI-ready werd: de datafundamenten die het verschil maken 11.00 - 11.45 11.00 - 11.30 Datagedreven innovatie Tamara Francke (MKB Brandstof) AI Agents voor Iedereen!? bij Koninklijke INretail & Paul van de Schoot (Yonego Koninklijke Metaalunie Kai van den Berg (DTX) Agency B.V.) Ramon Maanders (DTX) Jon Sanders (Koninklijke Metaalunie) Marco ter Horst (INretail) 11.30 - 12.00 Minder administratiedruk bij Energie voor Elkaar: Slimmer en efficiënter werken met AI en 11.45 - 12.15 Automation So, What About the AI Act? Erik van Berkel (Energie voor Judith van Schie (Considerati) Elkaar) 12.00 - 12.30 Artificial Intelligence: Zakendoen in een nieuw krachtenveld

12.30 - 13.00 Scaling AI at the Dutch Tax Administration: A Risk-Based Control Frameworkvoor implementeren en uitrollen AI

Martijn Bauters (RVA)

14.00 - 14.30 Van model naar besluit: waar AI en MMM tekortschieten Tjaard Prins (Centraal Beheer)

12.45 - 13.15 De onboarding van je AI-collega: van pilot naar volwaardig teamlid Bas Overtoom (Nemko Digital) Hedwich Sijtsema (Belastingdienst) Thomas Klopstra (CBEE Remarkable) Sayed Nasibdar (Gen25)

13.30 - 14.00 De pensioentransitie als katalysator voor een solide datafundament Wouter Revenberg (AZL) Ricardo Jacobs (Nippur)

Gea Peters (Alliander N.V.) Jan Hornman (PONG.nl & DAMA NL)

14.15 - 14.45 Data Governance bij Albert Heijn: Sturen op waarde met de juiste governance

15.00 - 15.30 Just Because You Can, Doesn’t Mean You Should Do It: Where Ethics Meets Innovation Roos Brekelmans (Vattenfall)

15.30 - 16.00 Datawerkplaats: krachtig samenwerken in een digitaal ecosysteem Hans Kox (Waterweg Wonen) Niels Theunissen (Brand New Perspective)

10.30 - 11.00 De Fundering voor AI: Hoe Intergamma met MDM datakwaliteit schaalbaar borgt Patrick Grasza (Intergamma)

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10.30 - 11.15 Next Level Data Strategy: Build Your Data Foundation in 45 Minutes Barry Wildhagen (Informatica from Salesforce)

11.15 - 11.45 Hoe data Wakibi helpt groeien van €3M naar €10M aan uitleningen per jaar Sanne Kieftenburg (Digital Power 11.30 - 12.15 Executive Roundtable: The Blueprint Datahub) Marije Roozendaal for Certainty: ERP for Professional (Stichting Wakibi)

Services & AI

12.00 - 12.30 Healthcare of Tomorrow: AI Enabled by a Powerful Data Platform

13.45 - 14.15 At Swiss Sense, we don’t implement AI, we adopt it

12.45 - 13.30 De geest achter een wonderlijke gastbeleving: het data-fundament van de Efteling Jowan Gosens (Efteling) Milou Mutsaers (Efteling)

13.45 - 14.15 Flexibele en schaalbare AI-impact binnen de diversiteit van Pon

13.15 - 14.00 Eerst de data op orde, of meteen met AI beginnen? Merel Huitink (ABN AMRO) Maartje Vennema (Chief AI Officer Academy

Milou Ehrismann (Swiss Sense) Tom Klaver (Pon (Datalab)) Emiel van Lieshout (Swiss Sense) Kasper Meijjer (Pon (Datalab))

Ivo van den Berg (Albert Heijn) 14.45 - 15.15 Data Bedrevenheid: hoe krijg je een organisatie in beweging op data?

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Roundtable sessions

Fenna van Berkel (UMC Utrecht) Ruben Peters (UMC Utrecht)

Julia Krauwer (ABN AMRO)

13.15 - 13.45 How we set-up a Compliant Hybrid Cloud platform at the Belgian National Employment Office

Hall 8

14.15 - 15.00 Rondetafel: Van Homo Sapiens naar Robo Sapiens 14.30 - 15.00 14.30 - 15.00 Lizzy Prins (High Potential Factory) Van Azure Synapse naar Embedding software engineering Microsoft Fabric: bouwen aan een best practices into AI projects AI-ready dataplatform. Merel Theisen (QuantumBlack) Stan Toorneman (TKF) Diane Roodhardt (Victa)

15.15 - 15.45 15.15 - 15.45 How everything has changed, and The Analytics Chicken-and-Egg: nothing has: on building Product Proving Value Before You Have with AI the Team

15.15 - 16.00 Rondetafelsessie: Het datadrama: hoe krijgen we het vertrouwen van consumenten terug?

Jessica Ruland (TicketSwap)

Anthony Derrick (Vattenfall) Pascal Swier (Vattenfall)

Esmeralda Meijer (DDMA) Luuk Ros (DDMA)

16.00 - 16.30 ASN bank: Van transformatie naar dataregie

16.00 - 16.30 When your data warehouse talks back: How conversational analytics changes the analytics game.

15.45 - 16.30 AI is overal. Waarom verandert er zo weinig? Lizzy Prins (High Potential Factory)

Sepke van den Heuvel (ASN Bank)

Mark Schep (Mark Your Data)

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

PLATINUM CONNECTOR AT DATA EXPO: “THIS IS THE ULTIMATE MOMENT” CHRIS BOONSTRA Co-founder and co-owner | CBEE Remarkable

Automation and AI may sound appealing, but without a solid data foundation, they won’t deliver anything. That is the firm conviction of Chris Boonstra, co-founder and co-owner of CBEE Remarkable. “Data Expo is not about pilots; it’s about delivering lasting value. That is exactly what I believe in,” says the platinum sponsor. According to Boonstra, this is the “ultimate moment” to showcase CBEE Remarkable at Data Expo, where business leaders, data experts, and tech professionals come together. He sees the market shifting from experimentation to performance, from wishful thinking to value, and how these themes will take center stage at the Jaarbeurs on September 9 and 10. Data Expo is also the ideal venue for CBEE Remarkable: “Industry players come together there. As consultants, we play a role in connecting people and turning business ambitions into reality.”

Connector and coach

Boonstra says he has always been a connector. “Ten years ago, drawing on my background as a registered controller, I started CBEE. I began by providing services in accounting and controlling, with the idea of expanding into and collaborating with other disciplines.” From there, a few years later, he founded CBEE Remarkable with two partners, specializing in the implementation of Salesforce and Certinia. It’s a kind of incubator, says Boonstra: “We have a lot of talent on staff who came to us from universities and colleges. That’s why 36

training and coaching are such an important part of my work. I think that’s truly amazing.”

“Data, context, and trust really need to be in place. Then AI doesn’t function as a toy, but as a colleague who takes work off your hands and adds value.” Platform thinking

CBEE Remarkable now employs nearly twenty people; the company is headquartered in Groningen and also operates out of Utrecht. Boonstra: “Unlike many of our competitors, we didn’t start with CRM, but with business processes and the financial side of the business. Since we started in 2019, we have believed in platform thinking. We became a partner of Salesforce, the largest CRM provider. It is a complex platform that allowed us to connect marketing, sales, and operations with finance.” CBEE also partnered with ERP provider FinancialForce, now known as Certinia, which enables companies to bring project management, resource planning, and financial processes together within the same Salesforce platform.

From lead to cash

Boonstra describes CBEE Remarkable as an IT company and niche consultancy. “We digitize, automate, and connect business processes from lead to cash, that is, from

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

finding the customer all the way through to processing the invoice. We do this for knowledge-based and service-oriented SMBs: companies whose core business revolves around projects, contracts, or memberships, including those in healthcare and life sciences.” Clients and prospects range in size from approximately 50 to 1,200 FTEs, says the co-founder: “That usually means we have direct contact with the board and often with the founders as well. We aim for long-term partnerships with short lines of communication, where we can make a big difference with a small team.”

Best practices

“To help companies implement software,” Boonstra continues, “you have to listen closely to clients from the very beginning. How do you do business? What challenges do you face? We make choices that align with the client’s business processes. We align those processes with the software’s out-ofthe-box best practices. We provide as little customization as possible and try to keep programming to a minimum. That saves time and makes maintenance easier.”

More silos as a result of AI

Boonstra sees how AI has increasingly become part of daily life and work, both for himself and for his clients. These new possibilities may conflict with the platform-based approach he so strongly believes in: “You can imagine that AI within organizations leads to more silos, just as Excel did in the past. With AI, you can generate output very

BOONSTRA’S BUSINESS PARTNER, THOMAS KLOPSTRA, WILL SPEAK ABOUT ONBOARDING YOUR AI COLLEAGUE: FROM PILOT TO FULL-FLEDGED TEAM MEMBER DON’T MISS IT!

Lecture hall 6

quickly, but how do you ensure that you’re getting the right output?”

“Data Expo is not about pilots. It’s about delivering lasting value. That is exactly what I believe in.” Data, context, and trust

It starts with the right input, according to Boonstra: figures and other data about customers, projects, and invoices shouldn’t be scattered across different departments, systems, and files, but should instead be kept up to date and centrally available in one place. “Data is the core of what you can achieve with automation and AI.” According to this expert, two more things are needed for AI to be truly useful: context and trust. “AI must understand how your organization works, know the agreements and arrangements behind the scenes, and understand why certain things are sensitive. That’s what makes the difference between a general answer and the right answer.” On trust: “You only let AI take the reins when you can truly rely on it, when it does what you expect and you trust the platform with your data. That’s why we chose Salesforce.”

Key Question

Boonstra observes that organizations are already making extensive use of AI and that “countless experts” have emerged to help them with this, sometimes without laying the proper foundation. “Data, context, and trust really need to be in place. Then AI doesn’t function as a toy, but as a colleague who takes work off your hands and adds value. If any one of those three things is missing, they remain nothing more than experiments that never really deliver results. The key question we’re now answering for clients is: How can we make the most of these new opportunities?” The answer often lies in centralizing data, connecting systems and

Thursday

12:45 - 13:15

processes, and mapping out a data strategy. “This involves issues such as ownership, definitions, and change management.”

New truths

The question of how organizations can derive value from data and AI is central to Data Expo. “A fantastic theme,” says Boonstra, “that fits well with our company. We now know that you have to start small with projects. The market is now looking for new truths, and those can differ from one sector to another. For financial data, for example, 99 percent accuracy isn’t enough; in other segments, that might be different. I think it’s great that different worlds come together at Data Expo, including the business community, academia, and government. They all have different priorities, but face similar challenges.”

CBEE Remarkable at Data Expo

Boonstra is looking forward to Data Expo, taking place on September 9 and 10 in Utrecht. Visitors will encounter CBEE Remarkable there in various ways: “Together with Gen25, another partner from the Salesforce network, my business partner Thomas Klopstra will give a presentation on onboarding AI colleagues. This helps organizations prevent AI projects from getting stuck in the pilot phase. Certinia is hosting a roundtable with CFOs and operations directors to discuss the challenges they face. A client will also be taking part, along with my other business partner, Bart Blokzijl, who will represent CBEE Remarkable.” “Visitors can, of course, find us at the booth, which we’re sharing with Salesforce and Certinia,” Boonstra continues. “We each have our own display area to showcase what we can offer. Our names also appear on the many thousands of lanyards that visitors receive upon entry.” CBEE Remarkable is also featured on the Data Expo website: Boonstra writes a series of blog posts, for example, about reliable and smart AI.

“AI needs to understand how your organization works, be aware of behind-thescenes agreements, and know why certain issues are sensitive. That’s what makes the difference between a generic answer and the right answer.” Exposure, knowledge, and leads

When will Data Expo be considered a success for the platinum sponsor? “The value lies primarily in exposure, the opportunity to showcase ourselves,” says Boonstra. “Who we are, what we do, and for whom. And, of course, we’ll be exchanging knowledge with visitors and fellow exhibitors. Leads and prospects are the result of that. On top of that, we’re just going to have a blast. We’re fully focused on it internally and really looking forward to it. We’re all going to have a great time together, celebrating the strides our company is making.” Alongside Data Expo, CBEE Remarkable is running a recruitment campaign, Boonstra explains: “Be sure to stop by the Jaarbeurs.”

OGZ

Boonstra speaks highly of the collaboration with OGZ, the organizer of Data Expo. “They’re very on top of things. You can tell by how closely they stick to deadlines and, for example, their use of data automation. What we advise in sales and marketing, OGZ puts into practice every day.” Their stakeholder management is professional and well-organized, yet approachable, Boonstra continues: “They want the best for the expo and the sponsor; delivering quality is the goal. They provide us with tremendous support to make it a real success.”

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

THURSDAY 10 SEPTEMBER 2026 KEYNOTE PROGRAM Moderator: Tom van ‘t Hek

10:45 - 11:30

False Clear Ahead - When Agents Derail Your Defenses AI agents that pass an initial security review can still derail through prompt injection, tool poisoning, or destructive over-alignment — the “false clear.” Drawing on recent research, real-world incidents, and AI governance at Dutch Railways, this talk explores how agentic AI reshapes the enterprise attack surface and what defense-in-depth strategies help you govern agents without blocking

Rens van Dongen

innovation.

AI Officer

12:00 - 12:45

Enexis: Road to Excellent Data Products How do you turn data from a fragmented by-product of operational processes into a strategic asset that can be reused, governed and scaled across the enterprise? In this session, Enexis shares its road towards a shared data foundation and explains how data products are becoming a core organising concept. Expect a practical story about direction, design choices and lessons learned, illustrated with concrete

Kasper Kisjes

use cases from a grid operator operating in the heart of the energy transition.

Chief Data Officer

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

13:15 - 14:00

Building AI workstations for data & analytics engineers: Follow Kramp’s journey AI workstations have proven their value for software engineers, but what happens when you apply the same concept to data and analytics professionals? In this keynote, Oliver Meisch, head of data at Kramp, shares the journey of building an AI workstation specifically for data & analytics engineers, from initial experiments to a solution used in practice. Discover how Kramp approached this

Oliver Meisch Head of data

14:30 - 15:15

challenge, which choices they made, and how AI is being integrated into everyday data work. With real-world examples, Oliver will share the lessons learned, the impact so far, and what’s next.

Agents of Change: Scaling Smarter AI in HR Unlock the future of talent acquisition through the lens of AI agents. In this keynote, Randstad pulls back the curtain on how a leading recruitment firm builds next-gen talent tools. They will share a balanced blueprint for driving massive business value while seamlessly embedding the guardrails of the EU AI Act to build

Martin Woodward

Global Responsible AI Officer

an AI ecosystem candidates and clients can trust.

Erwin van der Meulen Global Head of AI

15:45 - 16:30

AI Agents: The Rewards, the Risks, and the Realities After a decade leading data and AI across very different industries — eBay, Schiphol Group, ING, and now as Chief Data Officer at Eneco — Dr. Tor Bøe-Lillegraven offers a clear-eyed take on AI agents: real rewards, real risks, and the realities of managing swarms of agents at scale. His message is direct: today’s AI is evolutionary, not a revolution — yet.

Tor Boe-Lillegraven Chief Data Officer

The organisations creating real value aren’t chasing a big-bang transformation. They adopt AI steadily and safely, especially where mistakes are costly and can’t be undone. DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Trustworthy AI isn't optional anymore The EU AI Act and Cyber Resilience Act are here. We help you get compliant, stay compliant, and prove it.

From assessment to certification - a clear, practical path to AI governance and compliance.

Providing Trust in a Digital World

digital.nemko.com

Scan for your free AI compliance starting point

linkedin.com/company/nemko-digital/

DATA-DRIVEN WORK ISN’T JUST AN IT ISSUE

But that is how it often feels in many organizations

This blog is contributed by

Becoming data-driven is a practical challenge for many organizations. Everyone wants it, but almost no one finds it easy. One of the most frequently heard explanations keeps coming back again and again: “Data, isn’t that something for IT?” And that is exactly where things go wrong. What do we mean by data-driven work? Data-driven work means that decisions are made based on reliable, shared insights. Not because it’s possible, but because it helps us make better choices. It’s about

steering, accounting for actions, and making adjustments based on facts that the organization recognizes and trusts. That sounds logical. And yet, in many organizations, data is quietly being pushed toward the IT department.

How data became an IT party

If we’re honest, it’s not surprising that data ends up with IT. After all, data resides in systems. Systems are managed by IT. And when something needs to be done with data, IT seems like the logical place to start. This is how dashboards “for the business” are created—reports that are technically sound but go unused, and data platforms that require a lot of effort but are understood mainly by specialists. The result is a silent division of roles: • IT collects, makes accessible, and structures data • The business waits for insights • And no one really feels a sense of ownership

Data-driven work thus becomes something that’s done, rather than something that’s used.

Why is this so persistent

This pattern isn’t the result of unwillingness or incompetence. It’s logical behavior in complex organizations as we know them today. IT wants to help. The business is busy with day-to-day operations, and as long as results aren’t immediately visible, data remains something abstract. But data-driven work requires a different approach. The questions must come from the business side. That way, data is used to support concrete decisions, and responsibility for using data lies where decisions are made. As long as data is seen as an “IT thing,” the disconnect will persist.

What goes wrong

When data is primarily the domain of IT, familiar problems arise. Insights don’t address the real questions. Reports aren’t trusted or used. And new initiatives fail because no one knows exactly who is responsible for what. The risk is that data-driven work will be seen as “something that doesn’t work,” while the real problem is that it has been placed in the wrong department.

How organizations can make progress in this area

In organizations that are making progress in this area, we see one key difference. They don’t transfer ownership of data entirely to the business; instead, they share ownership with the business. This is a clear hallmark of a mature (IT) organization. And that

ownership starts with one simple question: Which decision(s) do we want to be better able to make together? From there, we look at: • What data is needed for that • Who understands that data • And who is responsible for its use IT plays a crucial role in this, but not as the owner of the problem. IT ensures reliability, accessibility, and consistency. The business determines the direction and the use. In this way, data becomes a tool, not an end in itself.

Start small

At Enable U, we see this tension every day. We help organizations extract data from systems, connect it, and make it reliably available—but always in service of a specific question, a process, or a decision. We help IT create peace of mind and clarity, and we help the business actually use the data. Not by changing everything at once, but by starting small and making value visible.

Data-driven work doesn’t have to start on a grand scale. One question. One process. One decision that could be better supported by data. That’s often enough to show that data isn’t just an IT thing, but a shared tool. Because data-driven work doesn’t succeed when IT handles it perfectly. It succeeds when the organization uses it.

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

THURSDAY 10 SEP TEMBER 2026 HALL 1

10:15 - 10:45

11:00 - 11:30

11:45 - 12:15

12:30 - 13:00

Jij bent de x-factor in datamanagement

Van complexe tuchtzaken naar bruikbare content: generative AI in de praktijk

Van onbeheersbare datagroei naar grip op informatie, samenwerking en governance

Modernizing Analytics at Odido: Building the Foundation for AI

Het succes van goed datamanagement ligt niet aan theorie maar aan mensen. In deze sessie laten we zien waarom jij de x-factor bent en hoe je frameworks zoals DMBOK (datamanagement body of knowledge) inzet als middel om je organisatie daadwerkelijk in beweging te krijgen.

Van knowledge base tot browserplugin: zo zet je AI effectief in voor jouw organisatie. Ontdek hoe Stichting DSI tuchtuitspraken vertaalt naar concrete learnings voor de financiële sector. En hoe een contentbot actuele content verrijkt met de eigen kernprincipes. De afgelopen periode richtte DSI zich op de vraag hoe AI verder komt dan een experiment. Ze leidde de ontwikkeling van een AI-contentpijplijn die complexe tuchtuitspraken omzet in bruikbare kennis voor de sector, en actuele content verrijkt met DSI’s kernprincipes. Powered by Siemens

Wie vandaag de dag met Microsoft 365 werkt, herkent het probleem: Teamsites blijven zich vermenigvuldigen, data groeit onverminderd door en het wordt steeds lastiger om overzicht en controle te houden. Wie heeft toegang tot welke informatie? Welke data is nog relevant? En hoe voorkom je dat gevoelige documenten op de verkeerde plek terechtkomen? Ook de Regionale ICT-Dienst (RID) stond voor deze uitdaging. Als ICT-partner voor zeven publieke organisaties en ruim 2.000 medewerkers zag de RID de hoeveelheid data en samenwerkingsomgevingen sterk toenemen.

As organizations prepare for AI, many first need to simplify and rationalise their analytics landscape. In this session, Johan Maat, Head of Intelligence & Assurance at Odido, shares why Odido embarked on an analytics rationalisation journey, why Strategy was selected as the strategic platform, and how the organization is building a trusted data foundation for the next generation of analytics and AI. Powered by Strategy

Morgan Djotaroeno Consultant

Bas Van Gils

Partner & Professor

Marin Schrijen

Lead Strategie & Innovatie

Jan van Dijk

Programmamanager & Consultant Digitale Werkruimte

13:45 - 14:15

14:30 - 15:00

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AI bij Riksja Travel: wat je realiseert als je carte blanche krijgt

AI governance in a fragmenting world: Compliance as strategic control

How analytics guides a challenger sports brand

Wat gebeurt er als je als marketing- en e-commerce team carte blanche krijgt om AI niet als tooltje, maar als serieuze versneller in te zetten? Bij Riksja Travel besloten we het grondig aan te pakken. Geen losse experimenten, maar een organisatiebrede switch naar slimmer, efficiënter en consistenter werken met AI.

Complex global regulatory landscape, geopolitical developments and insufficient organizational governance controls create exposure to non-compliance, operational disruption and potential loss of strategic control over AI and data assets. How can companies build sustainable, holistic AI governance to navigate through these turbulent times?

Under Armour is a challenger brand in the sports apparel market. And that means we have to be smart and use that underdog position to our benefit. That isn’t only reflected on how we present ourselves on social media, but also how we organize ourselves. Data insights help us to ensure to make smart decisions by launching the right product at the right time to the right consumer via the right channel. During this session, Bas will explain how Under Armour has built a smart data layer that enabled quick reporting. It unlocked quicker reporting agility, including advanced insights into end-to-end online customer reporting journey.

Rutger Fokke Marketeer

Sabine Vroemen Marketeer

Cassandra Moons

Legal Director Compliance

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Bas Schnater

Senior Manager Analytics

Johan Maat

Head of Intelligence & Assurance

LECTURE PROGRAM HALL 2

10:45 - 11:15

11:30 - 12:00

12:15 - 12:45

13:30 - 14:00

Van flows naar agents: schaalbare AI voor klantcontact bij Univé

Dynamic Governance for AI Agent Access at Roche

From Art to Cart: datakwaliteit als marketinginstrument

Hebben we straks nog een baan? AI en de toekomst van werk

Bij Werk aan de Muur staan 1,5 miljoen kunstwerken online, elk te bestellen in meerdere printvarianten, in elk formaat, met meerdere lijsten. Alles wordt geüpload zonder curatie. Het resultaat is een assortiment dat op papier oneindig is en in de praktijk onvindbaar.

Automatisering of augmentatie? Verdwijnen banen, of worden ze anders? AI raakt de arbeidsmarkt op manieren die we nog nauwelijks begrijpen. In deze sessie verkennen we de impact van AI op werk, productiviteit en arbeidsbelasting. Liggen we straks allemaal aan het strand, of krijgen we het juist drukker dan ooit? Je gaat naar huis met een realistisch beeld van wat AI doet met werk, en wat dat vraagt van jou als professional en organisatie.

Conversational AI verschuift razendsnel van scripted chatbots naar autonome AI-agents. Maar wat betekent dat voor klantcontact, medewerkers, governance en technologie? In deze sessie deelt Univé hoe we bouwen aan een schaalbaar AIgedreven contactplatform, welke lessen we leren en wat de toekomst brengt.

When autonomous AI agents act as an intermediary between users and secured data, traditional security models quickly fall short. The rise of agentic AI therefore requires a new approach to access management—one that considers not only who has access, but, more importantly, what an AI agent is allowed to do at any given moment. In this presentation, Roche and Immuta will demonstrate how we are addressing this challenge. We will start by exploring Roche’s journey from a manual database access process to a dynamic, tag-based marketplace for data access. We will then look ahead to our approach to governing AI agents. Powered by Systemation

Merel Derlagen Lead Data Analytics & AI consultant

Ties van der A Productowner Conversational AI

Rosie Geenty

Colin Mitchell

Data Security Engineer GM, Vice President Sales EMEA and APAC

Het probleem is niet het volume. Het probleem is dat de metadata niet aansluit op hoe klanten zoeken. Beeldmakers taggen wat ze zien: Erasmusbrug, tulpen, abstract. Klanten zoeken wat ze voelen: sereen, hotel chique, iets wat past bij mijn Scandinavische woonkamer. Daar tussenin zit een gat dat handmatige curatie bij dit volume niet dicht krijgt.

Jelle Swaan

Head of Marketing

14:15 - 14:45

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15:45 - 16:15

From data platform to AI platform: how Winparts prevents returns with data & AI

De superhuisarts bestaat — zo werkt AI als stille klinische partner in de eerstelijnszorg

Data spaces voor het Digitale Product Paspoort (DPP)

Winparts’ belofte: het juiste onderdeel voor jouw auto. Mislukt dat, dan volgt een retour — duur voor Winparts, frustrerend voor de klant. In deze sessie laat Winparts zien hoe ze stap voor stap een dataplatform uitbouwden tot een AIplatform op open source componenten. Van datapijplijnen en datamodellen tot AI-jobs die retouren structureel verminderen. Use case voor use case.

Stel je voor: één vraag in je Huisarts Informatie Systeem en binnen seconden een klinisch onderbouwd antwoord — inclusief bronvermelding, volledig op Nederlandse servers. Geen generieke chatbot, maar domeinspecifieke AI gebouwd op meer dan 40 jaar medische kennis. In deze sessie laat Health Base zien hoe je verantwoorde AI bouwt in een high-stakes omgeving: van geverifieerde kennislaag en RAG-architectuur tot sovereign infrastructuur en AVG by design.

Judith von Reeken Managing Consultant

De invoering van het digitaal productpaspoort (DPP) binnen de EU is een belangrijke stap voor de transitie naar een circulaire economie, maar vraagt ook veel van productieketens en bedrijven. In deze sessie gaan we in op het belang van standaardisatie en interoperabiliteit als het gaat om succesvolle implementatie van het digitaal productpaspoort (DPP). Ook kijken we naar de ontwikkelingen van data spaces als mogelijke oplossing voor betrouwbare en veilige data uitwisseling binnen waardeketens.

Mark Schep Founder

Harm Albers

Data Science Lead

Rense van der Zee Data Engineer

Emma de Ruiter Marijn Zeemeijer Apotheker Business Development

Apotheker Business Development

Eva Koenders

Docent / onderzoeker applied data science & AI

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

THURSDAY 10 SEP TEMBER 2026 HALL 3

10:15 - 10:45

11:00 - 11:45

12:00 - 12:30

13:00 - 13:30

Datagedreven werken is en blijft mensenwerk!

Politie bewaakt het Data vertrouwen

De omslag naar datagedreven werken vereist naast goed functionerende techniek een cultuur- en gedragsverandering. In mijn presentatie laat ik zien hoe bij het UWV datagedreven werken binnen de HRM-organisatie is geïmplementeerd. Daarbij sta ik stil bij het belang van een gedragen visie, educatie, communicatie en agile projectaansturing. En laten wij zien hoe wij denken dat KI in de nabije toekomst ons een sprong kunnen laten maken. En waar wij tegen aanlopen en hoe wij datagedreven werken succesvol hebben kunnen implementeren. En dat dit “slechts” de eerste stap is.

De politie zet steeds meer data in om politiemensen gerichter in te zetten en de veiligheid te vergroten. Daarbij worden thema’s als privacy, proportionaliteit en datakwaliteit steeds belangrijker. Een data-volwassenheidsonderzoek van drie jaar geleden liet zien dat de randvoorwaarden voor datagedreven samenwerking onvoldoende waren ingevuld. Er was sprake van versnippering, overlap, replicatie van data en beperkt bewustzijn van het belang van databeheer. Deze inzichten vormden de basis voor het programma Datagedreven Samen Werken. Zonder verandering dreigen de huidige oplossingen onbetaalbaar te worden en komt de wendbaarheid van de organisatie onder druk te staan. De politie blijkt sterk in het verzamelen van data, maar minder in het beheren, standaardiseren en borgen ervan. Ook kennis en expertise zijn versnipperd. De sprekers delen hun ervaringen, successen en valkuilen. Inmiddels wordt gewerkt aan een gezamenlijke taal (CSAE), opleidingen, harmonisatie van dataverzamelingen en de opbouw van een Datacare-organisatie.

Software modernization: building AI on a system you can’t touch

Bridging business & technology: preparing brands for the Agentic Era

How do you run AI on software that’s too old to update, but too critical to replace? This talk breaks down a project at a chocolate factory with a 20-year-old core system. We’ll share the initial technical assessment, the options we considered, and how we built a shadow database and custom apps around the legacy system instead of replacing it.

Traditional customer journeys are no longer enough as AI increasingly shapes how people research, compare and buy. Drawing on her move from global marketing into Pon’s Datalab, AI Commerce Strategist Marjolein Jongbloed shares how she bridges business and technology to help Pon brands prepare for the Agentic Era. Expect practical insights into AI Search, Agentic Commerce and what brands can do today to raemain visible, relevant and competitive.

Nico de Roo

Sr projectmanager (retired)

Internationale lead AI & Data Science

Ruud Staijen

Programmadirecteur

Kishan Chamman Founder & CTO

Floris Schoenmakers Partner

Marjolein Jongbloed AI Commerce Strategist

13:45 - 14:15

14:30 - 15:00

15:15 - 15:45

16:00 - 16:30

Tussen datastortplaats en goudmijn: grip op ongestructureerde data

Hoe selecteer je het meest waardevolle AI-project?

Architecting AI Agents in Production: Insights from Philips Hue

Scalable AI Impact: From Trusted Data Sharing to AI-Ready Companies

How do you move from LLM demos to reliable AI agents in production? In this session, Philips Hue shares its journey. We will cover architecture evolution, modular agent design, observability, and key lessons learned while scaling real-world AI agents.

High-quality AI needs high-quality data. Anil Turkmayali (IDSA) shows how trusted data sharing becomes enabler for AI: agentic AI uses enterprise data while control and IP rights stay with the data owner. That assurance builds trust, the basis for trustworthy agentic participation in data spaces. With the DataPACT AI Compliance Framework and AI Compliance Toolbox, companies become AI-ready and AI-Act-compliant during implementation rather than afterwards.

Nico Nijenhuis

Data Governance Specialist

Oscar Wijsman

Je wilt dat AI iets oplevert voor je organisatie, meetbaar in euro’s. Hoe bepaal je dat? En als je het al eens hebt bepaald, had je dan het juiste gemeten? Vaak vallen we voor resultaten zoals minder handmatig werk en snellere afhandeling van taken. Klinkt goed, maar heeft op zichzelf nog geen waarde. In de praktijk zien we dat juist deze cases zichzelf niet terugverdienen. In deze sessie leer je hoe je vooraf beoordeelt of een AI-project de investering waard is en hoe je het de investering waard laat maken.

Maartje Vennema Oprichter

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Mohamed Elkady System architect

Anil Turkmayali

Head of Research and Innovation Programs

LECTURE PROGRAM HALL 4

10:45 - 11:15

11:30 - 12:00

12:45 - 13:15

13:30 - 14:00

Van scale-up naar datagedreven organisatie: de journey van Connex

Building the Data Foundation for a Nation-Wide AI Infrastructure

Iedereen wil iets met AI. Maar is jouw organisatie er klaar voor?

Waarom je model niet gebruikt wordt: lessen uit netregisters

Iedereen wil ‘iets met AI’. Maar tussen ambitie en impact zit een ongemakkelijke realiteit: versnipperde data, onduidelijke doelen, compliance-vragen en organisaties die vooral experimenteren zonder richting. In deze sessie krijg je een nuchtere managementblik op AI. Geen technische demo’s of hype, maar een eerlijk verhaal over wat organisaties écht op orde moeten hebben om waarde uit AI te halen. Van datastrategie en datakwaliteit tot governance, adoptie en de rol van leiderschap. Want AI versnelt vooral wat je al bent.

Waarom worden datamodellen vaak niet gebruikt, terwijl ze technisch kloppen? In deze sessie laten we zien hoe verschillen tussen systeemlogica en business-realiteit leiden tot verkeerde interpretaties en gemiste adoptie. Aan de hand van praktijkvoorbeelden uit netregisters bij Alliander ontdek je concrete oorzaken van mismatch en vooral wat je anders kunt doen om data-oplossingen wél te laten landen.

Connex groeide van scale-up naar volwassen organisatie, en groeide daarmee ook toe naar een nieuwe fase in hun datavolwassenheid. In deze sessie vertelt Connex zelf hoe ze op zoek gingen naar een datafundament dat met hen mee kon schalen, en waarom TimeXtender daarin de keuze werd. Je hoort uit eerste hand hoe die keuze in de praktijk uitpakte: wat het hen heeft opgeleverd, welke inzichten ze onderweg opdeden, en hoe ze vanuit dat fundament nu doorbouwen richting AI-enablement. Een eerlijk en inspirerend verhaal van een organisatie die zelf de stap naar datagedreven werken heeft gezet.

ORION is HAVELSAN’s Big Data Management Platform, providing a unified, scalable, and secure foundation for managing complex data environments. By integrating data collection, migration, storage, processing, analytics, monitoring, orchestration, and AI/ ML, ORION supports the full data lifecycle while reducing operational complexity. Designed for mission-critical environments, it enables data sovereignty, high availability, and future-ready AI infrastructure at national scale.

Joris Schut

Business Advisor

Dane Bakker

Business Data Executive

Yıldırım Umut Doğancı Senior Solution Architect

Louis de Roo

Data Strategy Leader

14:15 - 14:45

15:00 - 15:45

16:00 - 16:30

Het datamarketingteam van morgen: wat AI vraagt van mensen, teams en organisaties

A.I., intelligentie en jouw baan

The Winning Number Game

Met de opkomst van (generatieve) A.I. is werk bezig aan een transformatie. Bedrijven maken een slag naar een herverdeling van onze taken. Wat betekent dat voor jou? Hoe bereid jij je voor op de toekomst met A.I.? Michel neemt je mee in de toekomst van jouw werk. Een toekomst die nú begint.

Can data predict a championship? Or deliver the right tactical call at the right moment? The Winning Number Game is about how elite sport is increasingly shaped by the numbers behind the scenes, from talent identification to tactics to injury prevention. Moneyball is no longer a utopia, it’s reality. This session shows how teams turn data into decisions that can tip the balance of matches and seasons.

AI verandert niet alleen de technologie waarmee marketeers werken, maar ook de manier waarop teams zijn georganiseerd. Op basis van de nieuwste inzichten uit het DDMA Data Driven Marketing Onderzoek (DDMO) laten Brenda van den Berg en Monique HartveltZwanenburg zien hoe organisaties omgaan met AI, welke competenties steeds belangrijker worden en wat dit betekent voor de toekomst van datagedreven marketing.

Brenda van den Berg Marketing Manager KPN

Monique HartveltZwanenburg

Michel van der List

Business Change Manager

Pascal Reijers

Alex Doeves

Data Business Partner Data Business Partner

Jop Beuger

Sport Data Scientist

Personalisatie marketeer bij Achmea

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

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LECTURE PROGRA M HALL 5

10:15 - 10:45

11:00 - 11:45

12:00 - 12:30

13:15 - 13:45

Het Sensire Informatiehart: AIinnovatie en eigen regie in de zorg

Datagedreven innovatie bij Koninklijke INretail & Koninklijke Metaalunie

Artificial Intelligence: Zakendoen in een nieuw krachtenveld

Hoe zet je data en AI concreet in om innovatie binnen jouw sector te versnellen? En hoe ondersteun je als branchevereniging honderden leden, ieder met hun eigen uitdagingen, bij het realiseren van aantoonbare impact? In deze sessie delen Koninklijke Metaalunie en Koninklijke INretail hun strategie, visie en praktijkervaringen rondom data en AI.

AI zet marges onder druk, imiteert producten en diensten, en neemt klantcontact over. Met scherpe voorbeelden en ongemakkelijke vragen dwingt ze je na te denken: hoe houdt jouw organisatie stand in dit nieuwe krachtenveld?

How we set-up a Compliant Hybrid Cloud platform at the Belgian National Employment Office

Sensire deelt de blauwdruk van hun datagedreven Informatiehart, gebouwd op GCP en open-source technologie. Het doel: zorgprofessionals ontlasten. Ontdek de techniek achter schaalbare innovaties zoals data-uniformering, GenAI voor het samenvatten van dossiers, en zelfontwikkelde spraaktechnologie voor automatische anamnese en rapportages. Leer hoe één platform zorgt voor slimme koppelingen en echte AI-impact.

Jan Willem Tiemessen

Dave Hamersma

Kwartiermaker BI & Robotisering

Data Scientist

Jon Sanders

Informatieanalist

Marco ter Horst Innovatiespecialist & DATA coördinator

Julia Krauwer

Sector banker Technologie, Media & Telecom

14:00 - 14:30

14:45 - 15:15

15:30 - 16:00

Van model naar besluit: waar AI en MMM tekortschieten

Data Bedrevenheid: hoe krijg je een organisatie in beweging op data?

Datawerkplaats: krachtig samenwerken in een digitaal ecosysteem

AI maakt het bouwen van modellen sneller en schaalbaarder. Maar het sneller hebben van modellen en modeluitkomsten, betekent niet meteen dat je sneller inzicht hebt.. In deze sessie laten we zien waarom MMM, triangulatie en AI zonder begrip juist leiden tot schijnzekerheid. De echte uitdaging zit in interpretatie, kennis en adoptie. Hoe zorg je dat je van modeloutput naar onderbouwde keuzes komt?

Data bedrevenheid: hoe zorg je dat mensen weten wat data is, wat je ermee kunt en hoe je er waarde uit haalt?

Hoe werk je samen aan maatschappelijke vraagstukken als woningcorporaties, gemeenten en zorginstellingen elk hun eigen data hebben? De Datawerkplaats is een ecosysteem waarin organisaties data, kennis en expertise bundelen om gezamenlijke vraagstukken effectiever aan te pakken, zonder elke keer het wiel opnieuw uit te vinden. In deze sessie delen Hans en Niels hun ervaringen: van bestuurlijke keuzes en governance tot de technische inrichting van het dataplatform.

Tjaard Prins

Lead Data Consultant

Gea Peters

Data Consultant

Jan Hornman

Data Maturity Export | Data Governance Consultant

Hans Kox

A walkthrough how we build out our hybrid cloud platform to facilitate secondary use of employment data, to improve fraud detection, generate national statistics and strategical decision making with a mindset of using social security information on a compliant way

Martijn Bauters Chief Data Officer

Niels Theunissen

Directeur Bestuurder Founder & Consultant

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

THURSDAY 10 SEP TEMBER 2026 HALL 6

10:45 - 11:15

11:30 - 12:00

12:45 - 13:15

13:30 - 14:00

Hoe MKB Brandstof AI-ready werd: de datafundamenten die het verschil maken

Minder administratiedruk bij Energie voor Elkaar: Slimmer en efficiënter werken met AI en Automation

De onboarding van je AI-collega: van pilot naar volwaardig teamlid

De pensioentransitie als katalysator voor een solide datafundament

Veel AI-projecten blijven hangen in de pilotfase. Thomas Klopstra (CBEE Remarkable) en Sayed Nasibdar (Gen25) laten zien wat er verandert als je een AI-agent behandelt als nieuwe collega in plaats van als IT-tool: met een functieprofiel, een inwerkperiode en een proeftijd. Aan de hand van praktijkcases uit klantenservice, klantcontact en enterprise search geven ze een concreet actieplan om vandaag nog te starten.

De Wet Toekomst Pensioenen is op dit moment de grootste transitie in het financiële stelsel in Nederland. 1500 miljard euro wordt omgezet naar individuele pensioenen en dit raakt vrijwel alle Nederlanders. AZL zit als grote pensioenuitvoerder middenin deze transitie en begeleidt ruim 30 pensioenfondsen in deze overgang. Om dit te kunnen ondersteunen heeft AZL haar IT-landschap volledig vernieuwd in de afgelopen 3 jaar. Hierbij is gekozen voor een domain driven architectuur met event based integratiepatronen om zodoende een efficiënte operatie via straight through processing te realiseren.

MKB Brandstof investeerde jaren geleden in een strakke data-infrastructuur, nog voordat AI een thema was. Die keuze blijkt nu goud waard. Hun datamodel legt bottlenecks bloot die anders verborgen blijven: uitval tussen bruto en netto klanten, kanaal-effectiviteit, noem maar op. Geen dure rapportages, geen ad-hoc analyses. Gewoon een vraag stellen en binnen minuten het antwoord zien. Deze sessie laat zien wat er gebeurt als je het fundament serieus neemt vóórdat je de tools inzet.

Bij Energie voor Elkaar kostte de registratie van biogrondstoffen wekelijks tot 40 uur administratief werk: CMR’s overtypen, weegbonnen terugzoeken en gegevens koppelen in Excel. Nu leest AI de documenten uit, koppelt een applicatie transporten automatisch en wordt de biomassarapportage dagelijks bijgewerkt. In deze sessie zie je hoe de oplossing in praktijk werkt en waar menselijke controle nodig blijft. Powered by Rockfeather

Tamara Francke Online marketeer

Paul van de Schoot

Senior Digital Advertising Specialist

Erik van Berkel

Data Landschap Ontwikkelaar

Thomas Klopstra Sayed Nasibdar Founder/ Salesforce Lead

14:15 - 14:45

15:00 - 15:30

15:45 - 16:30

Data Governance bij Albert Heijn: Sturen op waarde met de juiste governance

Just Because You Can, Doesn’t Mean You Should Do It: Where Ethics Meets Innovation

AI is overal. Waarom verandert er zo weinig?

Data governance wordt vaak gezien als iets abstracts: beleid, afspraken en structuren op papier. Maar de echte vraag is hoe je governance zo inricht dat het teams helpt om sneller, beter en met meer vertrouwen met data te werken. In deze presentatie laat Ivo van den Berg zien hoe Albert Heijn, Etos en Gall & Gall data governance inzetten als motor achter datagedreven werken en als fundament voor schaalbare innovatie, ondersteund door concrete bouwstenen zoals de implementatie van de Ataccama data catalog. Aan de hand van concrete voorbeelden deelt hij hoe governance in de praktijk wordt vertaald naar duidelijke verantwoordelijkheden, betere samenwerking en meer grip op datakwaliteit en waardecreatie.

Ethics and innovation are not polar opposites: they can strengthen each other so much. How we talk about AI actually shapes what we do and why ethics in fact drives better outcomes - not slower progress. Through storytelling and practical examples, you will explore diverse perspectives on decision-making and learn how curiosity and dialogue can turn responsible innovation into real impact.

Van Homo Sapiens naar Robo Sapiens: de volgende uitdaging is niet AI, maar de organisatie.

Ivo van den Berg

Head of Data Management Office

Strategic Consultant/ Trusted Advisor

Roos Brekelmans

Digital Innovation Accelerator

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Lizzy Prins Founder

Wouter Revenberg Streamlead

Ricardo Jacobs Data & analytics professional

LECTURE PROGRAM HALL 7

10:15 - 10:45

11:00 - 11:30

11:45 - 12:15

12:30 - 13:00

The AI Act in Action: What You Need to Know About Transparency

AI Agents voor Iedereen!?

So, What About the AI Act?

Scaling AI at the Dutch Tax Administration: A Risk-Based Control Frameworkvoor implementeren en uitrollen AI

This session provides a practical and brief overview of the EU AI Act’s transparency requirements, including when people need to be informed about the use of AI and how AI-generated or manipulated content should be labelled or disclosed. It will also translate these requirements into concrete considerations for business teams, helping participants understand what they mean for everyday decisions, processes and AI use cases.

Selim Dogan

Van experimenten naar echte digitale collega’s. Wat heb je nodig in je Data AI-landschap om AI-agents veilig, schaalbaar en beheersbaar in te zetten? In deze sessie nemen Ramon Maanders en Kai van den Berg je mee door het Microsoft-ecosysteem en ontdek je welke bouwstenen essentieel zijn voor succesvolle agentic AI.

Kai Van den Berg Ramon Maanders

Legal Counsel

Chief AI / Manager Data eXperts

Microsoft Power Platform & AI Consultant

Everyone is talking about AI, but what do the new rules actually mean for people working with data? This session explains the AI Act in simple, practical terms. No legal deep dive, but a clear overview of what to look out for when developing, buying or using AI systems. The session is especially relevant for data professionals, product owners, business stakeholders, innovation teams and managers who want to understand the impact of the AI Act.

Judith van Schie Managing Director

The Dutch Tax Administration aims to scale AI use cases across the organisation while ensuring security, compliance, transparency, and the protection of citizens. Together with Nemko Digital, it developed a risk-based AI control framework that enables safe, responsible, and scalable AI deployment. This session shares key insights and how such a framework can accelerate AI transformation.

Bas Overtoom Hedwich Sijtsema

Global Business Afdelingshoofd Development Director Business Ontwikkeling Analytics

13:45 - 14:15

14:30 - 15:00

15:15 - 15:45

16:00 - 16:30

At Swiss Sense, we don’t implement AI, we adopt it

Van Azure Synapse naar Microsoft Fabric: bouwen aan een AI-ready dataplatform.

How everything has changed, and nothing has: on building Product with AI

ASN bank: Van transfor matie naar dataregie

TKF transformeert haar bestaande dataplatform naar een schaalbaar en AI-ready fundament. In deze sessie hoor je hoe standaardisatie, governance en Microsoft Fabric zorgen voor snellere inzichten, nieuwe databronnen en betere sturing binnen de organisatie.

The way we build product changed faster than anyone expected. But going faster just moved the hard part from Delivery to Discovery. This is a practical story from TicketSwap about what AI actually changed, what stayed exactly the same, and why knowing what to build is now the real skill worth mastering. I’ll share real moments where AI shifted our pace and process and how knowing if you’ve made the right call hasn’t changed at all.

Achieving Real AI Impact at Swiss Sense by Combining Technology and Human Behavior Successful AI adoption goes far beyond giving employees access to individual AI tools. The real challenge lies not in the technology itself, but in the interaction between technology, people, and the organization. In this session, we will show how Swiss Sense has made AI a structural part of processes, teams, and decision-making through its AI Taskforce. Using concrete examples, we will demonstrate how AI has been scaled from isolated experiments to embedded solutions; from individual prompts to intelligent workflows and AI agents; and from personal productivity gains to organization-wide impact. We will share both the technical and human success factors that are essential for achieving sustainable AI adoption and long-term value creation within an organization.

Milou Ehrismann Manager Data Analytics & AI

Emiel van Lieshout Lead AI

Stan Toorneman Diane Roodhardt Business Intelligence Specialist

Manager Data Management

Jessica Ruland

Lead Product Manager

Kijk mee hoe we tijdens een ingrijpende organisatietransformatie een federatieve dataorganisatie hebben opgebouwd, ondersteund door heldere governance, een Enterprise Data Model, Collibra en datakwaliteitsmanagement. Daarmee hebben we het fundament gelegd voor betrouwbare data, slimme inzet van AI en de toekomstige realisatie van een centraal dataplatform.

Sepke van den Heuvel Lead Data Management

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

THURSDAY 10 SEP TEMBER 2026 HALL 8

10:30 - 11:00

11:15 - 11:45

12:00 - 12:30

12:45 - 13:30

De Fundering voor AI: Hoe Intergamma met MDM datakwaliteit schaalbaar borgt

Hoe data Wakibi helpt groeien van €3M naar €10M aan uitleningen per jaar

Healthcare of Tomorrow: AI Enabled by a Powerful Data Platform

De geest achter een wonderlijke gastbeleving: het data-fundament van de Efteling

Hoe transformeer je een complexe retaildataketen met AI, zonder de regie over je datakwaliteit te verliezen? In deze sessie deelt Patrick Grasza (Intergamma) hoe zij AI-agents strategisch inzetten om de databeschikbaarheid en -kwaliteit direct aan de bron te verhogen en handmatig werk te minimaliseren. Geen hypes, maar een pragmatische deep dive in schaalbaar Master Datamanagement. Het uitgangspunt is helder: betrouwbare artikeldata vormt de fundering voor álle retail-activiteiten. Zonder dat solide fundament benut je nooit de volledige potentie van AI.

Veel (non-profit) organisaties willen groeien om meer impact te maken, maar missen vaak de middelen om gerichte keuzes te maken. In deze sessie laten Wakibi en Digital Power Datahub zien hoe zij samen de groeiambitie van Wakibi (van €3M naar €10M aan uitleningen per jaar) met data ondersteunen. Van versnipperde inzichten naar een helder beeld van gedrag, funnels en de motivatie van uitleners.

Patrick Grasza

Head of Data Management

Sanne Kieftenburg

Relatiemanager Digital Power Datahub

Marije Roozendaal

Directeur Marketing & Communicatie

At Data Expo, UMC Utrecht shows how a modern data platform forms the backbone of data-driven healthcare and responsible AI use. In this session, Fenna van Berkel (Product Owner Data Platforms) and Ruben Peters (Tech Lead Data Scientist) demonstrate how a solid data foundation drives innovation, illustrated by the NoShow use case, and outline steps toward a future where data and AI are integral to healthcare.

Fenna van Berkel Product Owner Dataplatform

Ruben Peters

Tech Lead & Data Scientist

Jowan Gosens Data Engineer

Milou Mutsaers Data Engineer

13:45 - 14:15

14:30 - 15:00

15:15 - 15:45

16:00 - 16:30

Flexibele en schaalbare AI-impact binnen de diversiteit van Pon

Embedding software engineering best practices into AI projects

The Analytics Chickenand-Egg: Proving Value Before You Have the Team

Deze presentatie belicht de transformatie van Pon naar een datagedreven organisatie. Om optimaal te profiteren van AI, focust Pon Datalab eerst op het bouwen van een schaalbaar fundament binnen een complex bedrijfslandschap. Daarnaast legt de sessie uit hoe het Datalab de 80/20-regel toepast: door structureel 20% van de tijd te investeren in non-declarabele innovatie en experimenten, heeft de organisatie haar huidige voorsprong weten te bereiken.

Explore how software engineering best practices like modularity, testability, and reproducibility elevate AI project quality. We’ll see how these principles integrate into data workflows, making projects scalable and production-ready. Using Kedro as a practical example, we’ll share how these ideas translate into real projects, including modern AI techniques like Graph RAG and agentic reflection, covering both deterministic ML and nondeterministic agentic systems.

Many organizations face the same analytics paradox: the business wants better insights, more experimentation and smarter decision-making, but is not always ready to invest in additional analytics headcount until the value has already been proven. This creates a chicken-and-egg situation. You need analysts to create impact, but you need impact to justify analysts. In this session, we share a practical case study on how to break that cycle. Instead of waiting for the perfect team structure, we used external expertise and focused use cases to create momentum. Conversion rate optimization became one of the first proof points: by giving people the space to work on concrete optimization tasks, we could show how analytics directly improves our bottom line. From there, automation and AI helped us scale repetitive work, speed up analysis and make insights more accessible to the wider organization.

When your data warehouse talks back: How conver sational analytics changes the analytics game.

Tom Klaver

Lead Data Analytics

Hoe draagt data bij aan een zo wonderlijk mogelijke gastbeleving? Tijdens deze sessie nemen twee Data Engineers van het Data Platform-team je mee in het datafundament van de Efteling. Je ontdekt hoe met behulp van Amazon Web Services en Snowflake data op een betrouwbare en schaalbare manier beschikbaar wordt gemaakt. Daarmee legt het team de basis voor waardevolle inzichten en dataproducten die organisatiebreed worden ingezet. Zo draagt data direct bij aan het verbeteren van de gastbeleving en het creëren van nóg meer verwondering voor onze gasten.

Kasper Meijjer Lead Data Science

Merel Theisen

Principal Software Engineer

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

Anthony Derrick Digital Analyst

Pascal Swier

Digital Analyst and CXO specialist

What was the revenue this quarter? How often did we sell product X? How many customers did we have in 2025? Odds are you asked yourself similar questions recently. Maybe a dashboard provided the answer, maybe you asked the data team. What if you could ask these questions to your favourite agent. Be it Claude, ChatGPT, Gemini or any other agent. What if you could get the results in seconds, and the data team could focus on the bigger analytical problems. 10 years ago I thought this was impossible, during this presentation, I will show you that today this is very real. I simulated a ‘crafts supplies’ e-commerce company to learn how. I will share my learnings on how I believe this will impact data data driven decision making for business roles. As well as what this means for more technical roles in data warehousing, data engineering and data analytics. I’ll take the perspective from startup, to corporate to help you get started with conversational analytics within your company.

Mark Schep

Data & AI Engineer

LECTURE PROGRA PROGRAM M ROUNDTABLE

10:30 - 11:15

11:30 - 12:15

13:15 - 14:00

14:15 - 15:00

15:15 - 16:00

Next Level Data Strategy: Build Your Data Foundation in 45 Minutes

Executive Roundtable: The Blueprint for Certainty: ERP for Professional Services & AI

Eerst de data op orde, of meteen met AI beginnen?

Rondetafel: Van Homo Sapiens naar Robo Sapiens

AI versnelt werk. Maar wat wordt daardoor zichtbaar in organisaties?

Rondetafelsessie: Het datadrama: hoe krijgen we het vertrouwen van consumenten terug?

A hands-on breakout workshop by Informatica from Salesforce No slides. No generic frameworks. Just a real, working Data Strategy Canvas — built around your organisation’s goals and capability gaps in a single session. Facilitated by Informatica’s Community of Practice Director, the workshop runs on a simple premise: the AI proposes, you decide. Fast, timed rounds move you through Guiding Principles, Business Goals, Use Cases, and Data Capabilities — designed to produce signal, not noise.

Many ICT and SaaS leaders are caught between legacy fragmentation and the promise of AI. The gap between data capabilities and ambitions drives inefficiency, forecasting blind spots, and missed margins. This closed-door session explores how to build predictable resourcing, forecasting, and profitability through a strong data foundation, a modern PSA platform, and agentic AI. Learn practical steps, benchmark peers, and discover how unified operational data enables operational excellence.

Interactieve discussie over vertrouwen, transparantie en verantwoord datagebruik. Hoe kunnen organisaties werken aan herstel en versterking van consumentenvertrouwen?

Merel Huitink

Esmeralda Meijer Programmamanager

Lead Data Management Customer & Party Data Platform

Barry Wildhagen

Maartje Vennema

Community of Practice Director

Lizzy Prins

Oprichter

Luuk Ros

Founder

Team Lead Content & Community

Vijf systemen. Vijf keer een ander cijfer.” Kwartaalomzet volgens:

Één vraag. Vijf antwoorden. Vijf systemen. Vijf keer een ander cijfer. BranderSPOT brengt uw data samen tot één betrouwbaar stuurbeeld. Van bronkoppeling tot dashboard. Uw data blijft in uw eigen, beheerde omgeving.

ERP-systeem

4,2 mln.

CRM

3,9 mln.

Financiële tool

4,1 mln.

Voorraadsysteem

4,4 mln.

Rapportage-export

4,0 mln.

BranderSPOT

één bron, één cijfer

Ontmoet ons op Data Expo Stand 11 • 9 & 10 september 2026 info@brander.company +31 (0)297 893 096

BranderSPOT is een product van DATABrander.nl

AI IS NOT A MAGIC WAND In conversation with: MARTIN WOODWARD Global Responsible Al Officer & TJERRIE SMIT Chief Analytics Officer They both work for a major Dutch corporation, they both deal with AI on a daily basis, and they’re both keynote speakers at Data Expo. In the run-up to the event, Tjerrie Smit of NationaleNederlanden and Martin Woodward of Randstad sit down to discuss the added value of AI. They share practical experiences as well as the dos and don’ts of implementing AI. An open conversation about productivity, data governance, and the critical importance of multidisciplinary teams and data literacy. “With a well-trained workforce, you’ll see success much faster.”

Nationale-Nederlanden was an early adopter of AI, Tjerrie Smit tells his tablemate. Smit is Chief Analytics Officer at the NN Group, the publicly traded parent company of the insurer and financial services provider. “In early 2023, we launched our first major GenAI use case, in collaboration with ChatGPT. It was a call-logging application that automatically summarized call center conversations between agents and customers. We’d already been in contact with OpenAI, and we also had experience with machine learning. That allowed us to deploy it quickly. Technically, it went really well, but implementation turned out to be mainly a human challenge: people have to use the technology; they have to learn to work with this kind of AI. Everyone has to go through that same learning curve.”

RandstadGPT

“Very relatable,” responds Martin Woodward, Director of Global Legal & Global Responsible AI Officer at Randstad. It reminds him of a learning experience of his own: “One of our first true generative AI applications was our own RandstadGPT. It was back when more organizations were creating sandbox environments for chatbots. Nothing actually went wrong, but what you quickly realize with your own sandbox is that you can’t offer the same feature parity.” In other words: keeping up with the frontier AI labs—as Woodward refers to companies like OpenAI and Anthropic—is impossible. Yet employees do expect the latest innovations. “Why can’t RandstadGPT do what ChatGPT can?” they wondered, for example. Woodward: “That’s when the decision was made, and we fully committed to Gemini. We said goodbye to RandstadGPT fairly quickly. It just goes to show that you can’t keep up in terms of features and functionality if you develop it yourself.”

Scalability and repeatability

Technology is advancing rapidly, offering companies new possibilities with AI practically every week. “Of course, you have to test

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

new technologies in pilots first—you can’t do without them,” says Smit. “You could keep experimenting indefinitely, but at NN Group, we emphasize scalability and repeatability. AI can do a lot, but it’s not a magic wand. It often just involves hard work, a lot of trial and error, and continuous improvement—over and over again. Scalability and repeatability are so important because you can reuse successful solutions across the organisation.”

Productivity gains

Woodward sees a great deal of untapped potential within organizations when it comes to creating added value: employees aren’t making the most of the time savings that technology provides them. He illustrates this with an example from Randstad: “We started using generative AI to create job postings, which saved recruiters a lot of time. We had to teach them that they could spend that time on other tasks—such as making more client visits, for example, and spending less time at the coffee machine. Only then do you achieve productivity gains.” Woodward and his colleagues have learned from this: “Namely, that you’re most likely to succeed with AI use cases if you’re truly willing to scrutinize your entire business process and

reorganize it. For example, by assigning certain people to be responsible for job postings and freeing up others for those client visits. That’s when you’ll see a much greater impact from using AI.”

“For AI to succeed, you have to give everyone a seat at the table.” Martin Woodward

Governance framework

Smit takes over: “At NationaleNederlanden, we primarily try to apply AI to our core processes. If we can make these faster, better, and easier for customers, that’s where we’ll see the greatest benefits.” Woodward points out that this approach also carries risks: “By focusing on core processes, you’re choosing a path that many companies haven’t yet dared to take.” This brings Smit to the topic of data governance: “We use a governance framework based on the seven principles of trustworthy AI, as formulated by a European Union expert group. These principles were first set out in a report by an EU expert group, which later served as one of the foundations for the AI Act. They

include robustness, bias, non-discrimination, human oversight, and transparency. These are all core values that must be closely monitored in every AI use case. If you do that, you can safely deploy AI in your core processes as well.” Woodward: “Exactly what you’re saying. You can indeed see all those principles reflected in the AI Act.”

Trust-based approach

According to the Randstad legal expert, governance is often wrongly viewed as a brake on innovation: “It’s quite trendy to rail against all kinds of laws and regulations. It’s practically a meme. I think that when it comes to AI, we can actually learn from what wasn’t done when social media first emerged, even though we now see that it has both advantages and disadvantages. I think it’s good that lawmakers are taking this seriously, but data governance is also simply part of sound business management. It provides the foundation for trust, one of the core values instilled in us by our founder, Frits Goldsmeding. In our staffing agencies, human interactions fostered that relationship of trust, and we’re deeply committed to extending that into an AIenabled world.”

AI for governance

Smit adds: “The financial sector is subject to oversight, so we’ve traditionally been heavily regulated. We’re used to working with rules and governance—you simply need them to do things safely. In my experience, people who complain about governance often do so not because of the rules themselves, but because of their ineffective implementation. That’s a challenge we need to tackle together.” Woodward: “This is another area where AI can help us make progress. We’re successfully experimenting with GenAIdriven workflows. For example, we can partially pre-fill certain assessments, just as the tax authority does with tax return forms. Actually, we’re very enthusiastic about using AI for governance. It provides us with more insights and saves time. A human in the loop then only needs to verify the outcome. Of course, many aspects of our work ultimately require human judgment—not to determine legal compliance, but primarily for ethical review. This is and will remain particularly important when it comes to recruitment, selection, and HR.”

DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

KEYNOTE SPEAKERS TJERRIE SMIT WILL SPEAK ABOUT THE PATH TO FULLY AUTONOMOUS CLAIMS PROCESSING AT NN.

Keynote

Wednesday

14:30 - 15:15

MARTIN WOODWARD WILL SPEAK ABOUT AI GOVERNANCE AND AI STRATEGY, FEATURING MANY REAL-WORLD EXAMPLES.

Keynote

Thursday

14:30 - 15:15

Together with his Randstad colleague Erwin van der Meulen (Head of Global Application Management & AI Hub),

Multidisciplinary teams

Smit swears by multidisciplinary teams for successful AI: “You can run a pilot with a few techies in a corner, but I think the chances of moving from such a pilot to a successful, scalable implementation are very slim.” Nationale-Nederlanden always tries to put together teams with “tech experts and business experts,” according to Smit. “That way, we build something with the people who will eventually use it. Then you end up with applications that work well for the business, are of high quality, and are also embraced by the people who use them every day.”

A well-trained workforce

According to Woodward, AI projects are only partly about technology. “They’re mainly about behavioral change and organizational change. That’s why you see so much emphasis on AI literacy in the AI Act. You simply have to ensure that everyone who works for you knows how to interact with AI. That involves very practical skills, such as creating prompts quickly and effectively, use case development, training on specific systems, but also, for example, understanding the risks. With a welltrained workforce, you’ll see AI deliver results much faster.”

“Implementation is primarily a people issue.” Tjerrie Smit

A diverse group of people

The Randstad executive is also a strong advocate for multidisciplinary teams. “To organizations that are starting with AI tomorrow, I would advise them to bring together a diverse group of people. One of the things that makes AI truly unique in the business world is that you need so many different types of knowledge, insight, expertise, and skills from people to make AI projects a success. These include people with your own background, people with an IT background, people with an information security background, as well as compliance specialists—and, of course, the people from the business side who can identify problems and inefficiencies. If you want to have even the slightest success with AI, you’ll have to give everyone a seat at the table.”

Start with the problem

Smit has a “don’t” and a “do” for companies getting started with AI. “Don’t get started just because you think you have to do something with AI. You need to use AI to solve your business’s number one problem. If you don’t have a problem, don’t go looking for one.” The Chief Analytics Officer at NN Group speaks from personal experience: “In 2015, when I started working on machine learning solutions, I went around the company trying to sell my exciting new technology. ‘Who wants to use this!?’ It didn’t work at all. You have to flip it around

and start with the problem.” Then the “do”: “Make sure you have a solid ethical framework in place. Determining in advance what constitutes good AI and what doesn’t is very important. That prevents you from losing sight of that line later on due to enthusiasm. Always ask yourself whether something is possible, whether it’s allowed, and whether you actually want to do it.”

Shiny object syndrome

“AI FOMO” seems to exist, Woodward responds: “People rush headlong after the first salesperson who dangles a tempting carrot in front of them. They suffer from shiny object syndrome. They fall for the latest gadget, the newest tool, and the smoothest sales pitch. But for a successful approach, you first need to identify the problem you want to solve. Then you assess whether AI can help with that—and in what way.”

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IN CONVERSATION WITH…

VIDEO SERIES

The challenges surrounding data and AI are becoming increasingly relevant. But how do experts in the field approach them?

In this brand-new video series, industry experts discuss the challenges and opportunities shaping the data and AI landscape. Guided by current statements and thoughtprovoking questions, they share their perspectives and practical experiences.

The result: episodes packed with bold opinions, challenging questions and actionable insights. More from the series:

Julia Krauwer vs. Patrick Grasza

Lizzy Prins vs. Maartje Vennema

Is Europe too dependent on American AI models? And what if they suddenly became unavailable? Julia and Patrick share their perspectives and practical experience.

Is it okay to get started with AI if you don’t have a clear understanding of its business value? And where do you strike a balance between experimenting and deriving value from your project? All topics Lizzy and Maartje discuss in their episode.

High Potential Factory | CAIO Academy

ABN AMRO | Intergamma

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DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

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DATA EXPO 9 & 10 SEPTEMBER 2026 JAARBEURS UTRECHT

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