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ISSUE 404 I SEPTEMBER 2026 TAHAWULTECH.COM

LEAP INTO FUTURE LEAP 2026 brings AI, digital infrastructure and investment together to accelerate the Middle East’s technology transformation.

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EDITORIAL

From ambition to impact Technology transformation across the Middle East has entered a decisive new phase. Ambition remains high, but attention is increasingly shifting towards execution, measurable outcomes and long-term economic impact.

Our events This September issue of CNME explores how artificial intelligence, digital infrastructure, connectivity and emerging technologies are moving beyond experimentation to influence enterprises, governments and societies.

Talk to us: Sandhya D'Mello Editor, CNME E-mail: sandhya.dmello@ cpimediagroup.com

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The next chapter will belong to organisations that can translate bold ideas into secure, scalable and lasting value.

Our cover story examines LEAP 2026, where more than US$15 billion in technology investments and strategic partnerships were announced on the opening day. The scale of commitments across AI, cloud computing, data centres, autonomous mobility and digital government reflects the region’s growing determination to help shape the global technology agenda.

LEAP also highlighted an important reality. Advanced technology cannot deliver meaningful change without strong infrastructure, trusted data, effective governance and skilled people. AI models require computing power, storage, secure networks and carefully designed operating environments. Digital government platforms depend on interoperability, resilience and public confidence. Physical AI, autonomous vehicles and robotics introduce further questions around safety, accountability and regulation.

The challenge facing technology leaders is no longer limited to selecting the right platforms. Organisations must connect innovation with business priorities, integrate new systems with existing environments and ensure every investment addresses a genuine operational or societal need.

Several developments featured in this issue reinforce this transition. Ericsson’s involvement in South Korea’s AI-RAN initiative demonstrates how intelligent connectivity could support autonomous industrial operations. Tenable’s CyberAgents Exchange points towards greater collaboration in agentic cybersecurity. LG’s 5G telematics platform shows how advanced connectivity is supporting software-defined and autonomous vehicles.

Trust is also becoming inseparable from innovation. SIM-based authentication is emerging as an alternative to vulnerable SMS passwords, while enhanced safeguards for teenage AI users underline the growing responsibility placed on technology providers. These developments show that progress must be accompanied by stronger security, transparency and governance.

The Middle East possesses the capital, ambition and strategic direction to become a significant force in the global digital economy. Real success, however, will be determined by what happens after the announcements. Infrastructure must enable useful applications, investments must strengthen industries and innovation must improve services, productivity and everyday experiences.

This issue captures a technology landscape moving rapidly from possibility to practical implementation. The next chapter will belong to organisations that can translate bold ideas into secure, scalable and lasting value.

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CONTENTS

10 COVER STORY

Sibia Technologies

Ericsson

40 AIvaluesovereignty moves beyond models to build lasting 64 Epicor Names Vaibhav Vohra As Next Ceo

AVEVA appoints new Chief Revenue Officer from 1 66 October 2026

Epicor

Salam

evolves from telecom provider to digital 20 Salam transformation partner powers Saudi Arabia’s next phase of 26 Ericsson innovation

36 From using AI to working through AI

Ericsson

FOUNDER, CPI Dominic De Sousa (1959-2015)

ADVERTISING Group Publishing Director Kausar Syed kausar.syed@cpimediagroup.com

EDITORIAL Editor Sandhya D'Mello sandhya.dmello@cpimediagroup.com

Sales Director Sabita Miranda sabita.miranda@cpimediagroup.com

OnlineEditor Daniel Shepherd daniel.shepherd@cpimediagroup.com

AVEVA

Published by

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DIGITAL SERVICES Web Developer Adarsh Snehajan webmaster@cpimediagroup.com

Publication licensed by Dubai Production City, DCCA PO Box 13700 Dubai, UAE Tel: +971 4 5682993 © Copyright 2026 CPI All rights reserved While the publishers have made every effort to ensure the accuracy of all information in this magazine, they will not be held responsible for any errors therein.

NEWS

Ericsson looks to be a major influence on AI and 6G in South Korea

Rakuten looks to improve online medical services Rakuten Group has recently taken steps to advance an existing online medical and pharmacy service by collaborating with technology company J Frontier. The pair intend to align to deliver online medical consultations and guidance on medications, a move which would build on the services

Ericsson is set to be a significant

provided by the Rakuten Healthcare

for deliveries is being added to

Yoyakusuri app.

improve choice.

Rakuten stated the app currently

Rakuten explained the companies

provides pharmacy reservation and

would work to enable its registration

medical record services across Japan.

and login features to function on J

It is bringing online consultation

Frontier’s app to provide a smooth

influence on the development of

and guidance services J Frontier

service. It also plans to enable

physical AI and 6G in South Korea

provides in its own app into the mix.

payment options.

after being chosen for the nation’s

The initial integration means

The company pitched the app

Hyper-AI Network Infrastructure

users of the J Frontier app can pick a

integration as the latest step in

Demonstration Project.

Yoyakusuri Pharmacy for collection

a broader backing of the digital

The vendor’s position as

of prescription medication along with

transformation of Japanese healthcare

a main consortium partner

guidance on its use. A third timescale

services.

essentially involves contributing its technologies to the creation of a

pilot AI-RAN. Ericsson highlighted specialities in standalone 5G and intelligent network automation among the elements it brings to the table. It stated a second phase in the

SIM-based security is a major focus for U.S. operators Digital identity company Glide.id is teaming up with AT&T, T-Mobile U.S.

project would involve putting

and Verizon to deploy its carrier-native

the AI-RAN set-up through its

security platform which eradicates one-

paces in a logistics setting at the

time SMS passwords.

manufacturing facility of vehicle

Launching in public beta across iOS

maker KG Mobility in the city of

and Android, MagicalAuth uses open

Pyeongtaek.

network APIs and hardware-rooted

Sibel Tombaz, head of Customer

cryptographic authentication embedded

Unit Korea, said Ericsson’s

in SIMs and eSIMs to defend against AI-

selection was aided by a

based identity fraud.

longstanding relationship with SK

Glide.id noted operators face intense

losses, leading operators to shift security from SMS to their networks.

Telecom (SKT), which is heading

pressure to protect consumers from

one of two Hyper-AI Network

sophisticated threats. It explained SMS

mathematical challenge which can only

Infrastructure Demonstration

verification has long been plagued by

be solved by the unique cryptographic

Project consortiums. Counterpart

SIM-swapping and social engineering,

key installed in each SIM.

KT is overseeing the second.

and is increasingly helpless against

Ericsson explained it would provide “an end-to-end network foundation” which can “connect,

MagicalAuth issues a network-level

This mirrors the secure architecture

deepfakes, automated vector attacks

of chip-and-PIN payment cards,

and voice cloning.

verifying user identity without

It cited U.S. Federal Trade

passwords, authentication apps or

coordinate and continuously

Commission statistics showing

optimise intelligent machines and

consumer fraud losses reached $15.9

autonomous industrial operations”.

billion in 2025, with account takeovers

launch as an essential evolution in

accounting for almost 33% of enterprise

digital trust.

SEPTEMBER 2026

manual code entries. Operator executives positioned the

www.tahawultech.com

Tenable launches industry’s first open-source AI agent exchange Tenable® Holdings, Inc., the

peer-supported AI components.

exposure management company,

Underscoring the industry’s

recently launched the CyberAgents

commitment to collaborative,

Exchange, a new open-source

open-source AI defence,

AI exchange created to foster

industry leaders SentinelOne and

industry collaboration and improve

Recorded Future have joined the

collective cyber defence.

initiative as founding members

The CyberAgents Exchange,

of the CyberAgents Exchange. By

contributing their deep expertise

purpose-built, cybersecurity-

in autonomous security operations

native registry for AI agents, skills,

and threat intelligence, these

MCP servers and multi-agent

industry pioneers will help anchor

playbooks in the current market.

the Exchange as a truly unified,

Security teams are increasingly turning to AI to scale security operations and manage risk

Vlad Korsunsky, Chief Technology Officer, Tenable.

overload, but end up building

vendor-agnostic ecosystem. “Security is a team sport. We’ve addressed a gaping hole in the ecosystem of AI Agents, built

AI agents in isolation, repeatedly

these development silos and empowers

for defenders, by defenders. With the

reinventing the wheel. Existing AI

industry collaboration with a truly

CyberAgents Exchange, we’re creating

exchanges are either general-purpose

open, free-to-use exchange. Built for

a collaborative 'town square' where

or vendor-gated, forcing security teams

trust and transparency, the Exchange

cybersecurity practitioners can build,

to wade through irrelevant use cases,

provides code-level visibility into who

test, improve and share the best in

waste time on duplicate design and

built each AI component, when it was

agentic defence”, said Vlad Korsunsky,

build efforts, or accept restrictive vendor

created and its peer-supported status.

Chief Technology Officer, Tenable.

lock-in. To improve the cybersecurity

This transparency enables members

“With our deep roots in the open source

industry’s collective defence and outpace

to deploy AI components tailored to

community and our global ecosystem

AI-generated threats, defenders need a

their specific organisational needs

of customers and partners, Tenable

unified, cyber-specific hub to accelerate

confidently. Additionally, the Exchange

is uniquely positioned to steward this

development and share collective agentic

is a career asset for practitioners to

collaborative effort to help scale security

tooling.

build verifiable expertise in an emerging

teams' capabilities and outpace evolving

discipline and develop a catalogue of

threats”.

The CyberAgents Exchange eliminates

India to drive tech manufacturing interest with new deal The government of India is

bill introduced earlier this year,

reportedly planning to offer

valid until 2031.

longer tax exemptions to

According to FT, suppliers

foreign technology companies.

have asked the government

This news is speculated to

to amend laws to ensure

be part of a bid to convince

companies are not taxed for

these manufacturers to invest

owning machinery provided to

in the country and set up

their manufacturers.

manufacturing hubs that rival

The document states the

China.

proposals are “aimed squarely

Financial Times (FT)

at strengthening India as a

reported the proposed boosted

manufacturing base, especially

tax exemptions were submitted to

“provide ease of doing business and tax

for electronics, and at deepening

parliament on the 4th of August

certainty”.

supply chains that support it”, before

2026, with finance minister Nirmala

The government has tabled a proposal

adding the measures “give them

Sitharaman stating they should be

which would extend tax exemptions by

long-term certainty they need to

pushed through with urgency to

a decade through to 2041, building on a

commit.”

www.tahawultech.com

SEPTEMBER MAY 2026

NEWS

OpenAI enhances ChatGPT safety for teens OpenAI has recently launched

step-by-step guidance for

a new version of its ChatGPT

schoolwork, while enabling

AI program for users aged

responsible homework

13-years to 17-years with

reminders for users who

enhanced safety measures,

appear to be trying to bypass

parental controls and learning

an assignment and redirect

tools as the company faces

them towards collaborative

rising scrutiny over the risks

problem solving. Features

its chatbot poses to younger

including quizzes, learning

people.

visualisations and study

According to OpenAI, the

hours were also added.

ChatGPT for Teens service

Criticism

will automatically activate

The AI player first

when the AI chatbot detects

introduced parental controls

underage user activity or receive notifications in limited high-

to its chatbot in 2025, after being hit

13-years to 17-years. The safeguards

risk situations, including suspected

with a lawsuit in California over the

aim to “reduce exposure to content that

eating disorders. Measures will also

suicide of a teenager who was allegedly

may be harmful or developmentally

include teen-specific onboarding,

coached by the company’s platform on

inappropriate” and help teens “learn,

break reminders and cues explicitly

methods of self-harm.

think critically, deepen understanding,

identifying the service as AI.

and use AI with confidence”. The service includes additional

and age prediction systems

when a user self-identifies as aged

On chatbot interactions, OpenAI said

Indeed, criticism of ChatGPT’s impact on young people, including concerns

ChatGPT for Teens will not use romantic

around inappropriate content, violence,

protections covering self-harm,

language, encourage emotional

loneliness and its effect on learning,

violence, eating disorders, dangerous

dependence or imply it has feelings or

have been mounting. OpenAI faces

activities and explicit sexual or

consciousness “to reinforce healthy,

multiple lawsuits from families across

graphic content. Parents with linked

real-world relationships”.

the U.S. alleging ChatGPT contributed

teen accounts will be able to set quiet hours, manage settings and

Beyond safety, the company also introduced Study Mode to provide

to or encouraged teenagers’ suicides or violent crimes.

ByteDance is looking to develop an AI model to rival Mythos According to recent reports, ByteDance is in the process of developing an AI model which could rival Anthropic’s Mythos system. These rumblings are since as part of a wider bid for the company to establish itself as a leader in China’s AI ecosystem. Financial Times (FT) reported the TikTok owner is in the early stages of training a model with as many as 10 trillion parameters. This would put ByteDance’s offering ahead of Anthropic’s cutting-edge Mythos and make it

size of its models, FT reported the most

being pre-trained, a stage in

three-times larger than Moonshot

advanced Mythos 5 system has 8 trillion

development which typically takes

Kimi K3, the biggest model to come

parameters and its Fable 5 about 5

three-to-six-months. It would then be

out of China so far.

trillion.

fine-tuned and released, provided there

While Anthropic does not reveal the

SEPTEMBER 2026

ByteDance’s model is apparently

are no issues.

www.tahawultech.com

LG provides 5G telematics to European vehicles LG Electronics is working to provide 5G telematics to European vehicle manufacturers with a set-up employing the latest 3GPP specifications. The key takeaway is LG’s

Apple unveils the new foldable iPhone Duo

latest system is faster, tapping the capabilities of Release-16 specifications to make data transmission more reliable and less prone to delay than equipment running the 3GPP’s previous iteration of 5G standards. LG booked a 100-fold improvement in

autonomous driving. LG explained telematics systems

reliability and a fivefold gain in the rate

using Release-16 deliver the services

data is transmitted between a telematics

“with greater stability”, boosting

module and base station.

autonomous driving ambitions “where

Aside from its claim to being the first company providing such a

rapid response and safety are critical”. The set-up runs LG’s aWare vehicle

Apple has officially entered the

system in Europe, LG stated there

software, which spans entertainment

foldable smartphone market with

would be benefits for the software

and driver assistance functions. The

the announcement of the new

defined vehicle sector by delivering

company incorporated 12 antennas

iPhone Duo.

“essential infrastructure” for services

in one hardware item to help

including OTA software updates,

manufacturers with positioning and

debut seven years after Samsung

vehicle-to-everything connectivity and

minimise the wiring required.

launched its first foldable

The iPhone Duo makes its

smartphone and on the heels of a recent launch by Huawei. Pre-

Google debuts flagship Pixel 11 series

orders for the device begin in

Google recently showcased its

launches of the iPhone 18 Pro,

Pixel 11 series phones alongside

Pro Max, Apple Watch Series 12,

expanded hardware at an annual

Apple Watch Ultra 4 and AirPods

event, introducing processor

5, Ternus saved the foldable for

and camera upgrades along with

last but drew a quick distinction

adjusted memory configurations.

between the Duo and competing

October. After running through the

The range spans the base Pixel

devices.

11 (priced at $899), Pixel 11 Pro

“Others have created foldables

($1,099), Pixel 11 Pro XL ($1,299)

that just feel like two phones

and Pixel 11 Pro Fold ($1,899),

awkwardly stuck together”, new

which all run on Google’s Tensor

CEO John Ternus said during the

G6 processor. Google stated Tensor G6

company’s Surprise and Shine and cut energy by the same proportion.

provides a 50% increase in compute

A revamped CPU speeds web browsing

performance than its previous

by 25%.

generation and is built to accelerate

event on the 9th September 2026. He described the Duo as having “a larger display that feels as

An updated Titan M3 coprocessor

natural and intuitive as iPad,” and

on-device execution of the Gemini Nano

adds post-quantum cryptography to the

stated it has the “largest display

generative AI model.

secure boot process. The devices use the

ever on an iPhone, while still fitting

The company noted on-device AI

Android 17 OS and models with 16GB of

easily in your pocket”.

workloads run up to 3.5-times faster

RAM are configured to run Gemini tasks.

www.tahawultech.com

SEPTEMBER 2026

COVER STORY

LEAP 2026

SEPTEMBER 2026

www.tahawultech.com

Zebra Technologies

LEAP 2026 ACCELERATES MIDDLE EAST’S DIGITAL FUTURE From more than US$15 billion in technology commitments to major advances in AI, cloud, digital infrastructure and government services, LEAP 2026 demonstrated how investment, innovation and national ambition are converging to reshape the region’s digital economy.

www.tahawultech.com

SEPTEMBER 2026

COVER STORY

LEAP 2026 closed its landmark fifth edition with a clear indication of the Middle East’s expanding influence on the global technology landscape. Riyadh brought together technology leaders, investors, founders, policymakers and innovators at a time when artificial intelligence, cloud infrastructure and digital government are moving from strategic ambition into largescale implementation. More than US$15 billion in technology investments and strategic partnerships were announced on the opening day. Further commitments followed across artificial intelligence, cloud computing, data centres, autonomous mobility, government services and startup development. Collectively, the announcements reflected a market focused not only on adopting emerging technologies, but also on building the infrastructure, capabilities and ecosystems

required to deploy them at national and enterprise scale. The event attracted 1,323 speakers and 1,397 investors from 1,027 firms across 72 countries. Those investors collectively represented US$18.3 trillion in assets under management. More than 1,500 exhibitors participated, including over 750 global companies, while 1,294 companies took part across the exhibition and

startup programme. LEAP’s scale reveals a technology economy where capital, infrastructure and national priorities are increasingly interconnected. The significance of the event will ultimately be measured by how effectively its announcements translate into stronger public services, more competitive enterprises, new industries and sustainable economic growth.

From ambition to execution Technology access is no longer the region’s central challenge. Global platforms, infrastructure providers and emerging innovators are already establishing a strong presence across Middle Eastern markets. The more pressing question is whether organisations can integrate, govern and operate these technologies in ways that deliver measurable value. Modern transformation programmes extend well beyond deploying hardware or

SEPTEMBER 2026

www.tahawultech.com

software. Enterprises require clear business cases, suitable architecture, secure data foundations, integration with existing systems, regulatory alignment, workforce readiness and continuous optimisation. Artificial intelligence introduces further considerations around computing capacity, model governance, data quality, security and responsible use. National digital strategies have created the direction and momentum for change.

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Execution will depend on the ability of governments and businesses to connect policy, investment and technology with practical operational requirements. Saudi Vision 2030 provides a prominent example of this approach, using digitalisation to support economic diversification, public-sector modernisation and the development of new industries. Technology delivers its greatest value when it improves a government

service, increases industrial productivity, strengthens a supply chain, expands access to healthcare or helps a business compete more effectively. LEAP 2026 placed this transition from ambition to measurable outcomes firmly in focus.

AI moves into large-scale deployment Artificial intelligence ran throughout LEAP 2026, but the conversation had shifted decisively beyond experimentation. Announcements centred on models, computing infrastructure, data centre capacity and applications capable of supporting AI deployment at scale. HUMAIN introduced M3, an open-weights Arabic language model trained on more than one trillion Arabic tokens, alongside HUMAIN Voice, a conversational platform supporting Arabic dialects. The announcements underscored the growing

SEPTEMBER 2026

COVER STORY

14 importance of AI systems built around regional languages, cultures and operating contexts. Tareq Amin, Chief Executive Officer of HUMAIN, highlighted the collaborative effort required to realise this ambition: “No company delivers something at this scale on its own. What you are seeing is a country rallied around a mission, with partners across the Kingdom building alongside us.” HUMAIN and AWS also announced a joint US$5 billion investment in the AWS HUMAIN AI Zone. AMD and HUMAIN confirmed the deployment of AMD’s largest inference cluster outside the United States, while xAI outlined a Saudi data centre deployment beginning at 50MW and scaling to 500MW.

SEPTEMBER 2026

These developments show how the AI race is becoming an infrastructure race. Advanced models require high-performance computing, reliable storage, fast networks, efficient cooling and secure access to data. Dr Abdullah Alotaibi, Regional Director and Vice President at Supermicro, said: “Delivering

AI at scale requires powerful, efficient and adaptable computing environments capable of supporting rapidly evolving workloads.” Infrastructure alone, however, will not determine the success of enterprise AI. Organisations must connect computing resources with trusted

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data, cybersecurity controls and workflows designed around genuine business needs. Data preparation, system integration, model management, user adoption and measurable return on investment will be central to moving AI from isolated pilots into core operations. Arabic AI presents an especially important opportunity. Language models and conversational platforms must understand dialect, context and user expectations across diverse markets. Regionally grounded capabilities could enable more effective applications across government, financial services, retail, healthcare, education and customer experience.

Digital infrastructure becomes strategic LEAP’s third day reinforced the importance of the infrastructure beneath emerging digital services. NHC

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Innovation announced the SAR 3.3 billion Khuzam Digital Valley data centre project, with NAVER Innovation and BytePlus named as its first anchor customers. AWS is also preparing to launch its first Saudi Region in December, supported by more than US$5.3 billion in investment. Data centres and cloud regions are increasingly viewed as strategic economic infrastructure. Local capacity can reduce latency, support data residency requirements and give organisations faster access to advanced computing

No company delivers something at this scale on its own. What you are seeing is a country rallied around a mission, with partners across the Kingdom building alongside us. Tareq Amin, Chief Executive Officer, HUMAIN.

services. It can also help governments and businesses build greater operational resilience while accelerating the development of cloudnative and AI-enabled applications. The economic effect extends beyond large technology projects. Stronger digital infrastructure can support innovation across construction, energy, logistics, finance, healthcare, education and tourism. Smaller companies can access computing capabilities that would previously have required significant capital investment, allowing them to adopt enterprise-grade platforms through flexible cloud and managed-service models. The expansion of regional capacity also creates new demands. Organisations must modernise applications, connect hybrid environments, monitor performance, control

SEPTEMBER 2026

COVER STORY

cloud costs and protect increasingly distributed data. Cybersecurity, observability, backup and business continuity will become more important as essential services depend on interconnected digital systems. A passing but important role will fall to the region’s technology ecosystem, including distributors, systems integrators, service providers and specialist partners. Their implementation capabilities can help enterprises translate global platforms into secure, locally relevant environments. The wider story, however, concerns the transformation of the regional economy as digital infrastructure becomes fundamental to competitiveness and growth.

SEPTEMBER 2026

Physical AI moves technology beyond the screen LEAP also demonstrated how artificial intelligence is moving into the physical world. HUMAIN and Applied Intuition announced plans to deploy physical AI across Saudi Arabia, beginning with autonomous trucking and aiming to establish a network of thousands of autonomous vehicles across key logistics corridors by 2030. Visitors encountered humanoid robots, advanced prosthetics, robotaxis, autonomous delivery drones and flying taxis. While these technologies remain at different stages of commercial maturity, their presence pointed towards a future where AI will increasingly interact with

people, machines and physical environments. Physical AI could reshape logistics, manufacturing, healthcare, mobility and public services. Autonomous trucking, for example, could influence freight efficiency, road safety and supplychain planning. Robotics may support industrial automation, hazardous operations and areas facing shortages of specialised labour. Advanced prosthetics show how intelligent systems could also deliver more personalised healthcare outcomes. Deploying such technologies will demand more than sophisticated algorithms. Physical AI depends on reliable connectivity, edge computing, sensors, real-time data

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processing, cybersecurity and integration with operational technology. Safety, regulation, accountability and public trust will be equally important, particularly when autonomous systems operate in shared or critical environments. The emergence of physical AI therefore broadens the regional technology agenda. Governments and enterprises must prepare not only for more intelligent software, but also for machines capable of perceiving conditions, making decisions and acting in the physical world.

Digital government demonstrates national scale Saudi Arabia’s Tawakkalna platform offered one of the clearest examples of digital transformation operating at national scale. During LEAP 2026, 62 government entities were recognised for completing the integration of their services into the platform. A total of 926 services from those entities

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were consolidated through a single interface. Tawakkalna now serves more than 36 million users, facilitates over 85 million daily transactions and provides access to more than 1,700 government services. The figures demonstrate the potential of integrated digital platforms to simplify interactions between citizens, residents, visitors and public institutions.

Scale also increases technical and operational complexity. Government services must remain available under heavy demand, data must move securely between entities and users need a consistent experience across different functions. Identity management, interoperability, cybersecurity and service resilience become inseparable from the quality of publicservice delivery. Tawakkalna shows how digital government can develop from individual online services into an interconnected platform model. Such platforms can reduce fragmentation and create a more unified experience, but their longterm value depends on trust, accessibility and the ability to evolve with changing public needs. Other governments across the region will be watching these developments closely. The lessons extend beyond the platform itself to the

SEPTEMBER 2026

COVER STORY

policies, architecture, crossgovernment coordination and technical capacity required to deliver services at population scale.

Investment meets innovation

LEAP’s investor presence strengthened its position as a meeting point between capital and emerging technology. Nearly 1,400 investors attended the event, while the Rocket Fuel competition attracted more than 3,000 applications and awarded US$1 million across seven prizes. A further 653 applications had already been received for the 2027 startup programme by the close of the event. Talal Alasmari, Founding Partner at Ra’ed Ventures, said: “LEAP has evolved from a major technology gathering into a platform that connects ambitious founders from around the world with real

SEPTEMBER 2026

opportunities in Saudi Arabia and the region.” Capital can accelerate product development and market expansion, but investment alone does not guarantee commercial success. Startups need access to customers, relevant use cases, regulatory guidance, technical validation and the ability to deliver consistently after deployment. Enterprises also need confidence that emerging solutions are secure, scalable and capable of integrating with existing environments. The partnership between the Digital Government Authority and STV reflected this need to connect innovation with opportunity. The initiative will identify and support startups through government use cases, an innovation sandbox, procurement opportunities and regulatory and funding pathways.

Programmes of this kind can help reduce the distance between invention and adoption. They give founders clearer routes into complex markets while allowing government entities to assess new technologies in controlled environments. Successful solutions can potentially be developed into repeatable models for wider public- and private-sector use.

Talent and trust shape the next phase The scale of ambition displayed at LEAP also exposed two defining challenges: skills and trust. Advanced infrastructure cannot create lasting value without people capable of designing, deploying and governing it. The region will need more architects, data engineers, cybersecurity specialists, cloud professionals, AI researchers and industry experts.

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Technical capability must be supported by leadership and organisational readiness. Business teams need to understand how AI and digital platforms affect processes, roles and customer expectations. Technology leaders must communicate outcomes in commercial terms, while boards require greater clarity around risk, accountability and return on investment. Trust will remain essential as AI becomes more autonomous and digital platforms handle larger volumes of sensitive data. Organisations must establish clear controls over data access, model behaviour and automated decisions. Cybersecurity, privacy, regulatory compliance and operational continuity need to be designed into systems from the beginning rather than added after deployment. Skills development must therefore extend beyond certifications or product knowledge. It should include data literacy, responsible AI, sector expertise and the ability to manage multidisciplinary transformation programmes.

Organisations that combine innovation with governance will be better placed to scale new technologies without undermining resilience or public confidence.

A region shaping the technology agenda LEAP 2026 confirmed that the Middle East is no longer approaching digital transformation solely as a technology adoption exercise. The region is investing in the infrastructure, models, platforms, companies and talent needed to exert greater influence over the next phase of the global digital economy. Riyadh brought together capital, innovation and national ambition on a

Delivering AI at scale requires powerful, efficient and adaptable computing environments capable of supporting rapidly evolving workloads. Dr Abdullah Alotaibi, Regional Director and Vice President, Supermicro. www.tahawultech.com

remarkable scale. The announcements across AI, cloud, data centres, digital government, autonomous systems and startup development revealed both the breadth of opportunity and the complexity of execution. The lasting test will come after the exhibition halls close. Investment must produce capable infrastructure. Infrastructure must support useful and secure applications. Innovation must address genuine economic and social needs. Skills, governance and collaboration must advance at the same pace as technology. LEAP offered a view of a region determined to help shape the future rather than simply respond to it. Success will be measured not by the volume of announcements, but by the enterprises strengthened, services improved, industries created and lives positively affected by the technologies placed into operation.

SEPTEMBER 2026

INTERVIEW

Salam

SALAM EVOLVES FROM TELECOM PROVIDER TO DIGITAL TRANSFORMATION PARTNER Abdullah Khorami, Chief Business Officer at Etihad Salam Telecom Company (Salam), discusses Salam’s transformation from a telecommunications provider into an integrated digital partner and its role in advancing Saudi Arabia’s digital economy.

Etihad Salam Telecom Company unveiled Salam B2B 2.0 at LEAP 2026, marking its evolution from a traditional telecommunications provider into an integrated digital partner. The strategy brings together connectivity, AI, IoT, cybersecurity, cloud and industry-specific expertise to help enterprises overcome integration challenges and achieve measurable business outcomes. In an interview with CNME, Abdullah Khorami, Chief Business Officer at Etihad Salam Telecom Company, discusses the company’s customer-led portfolio, its approach to end-to-end digital transformation and the role of smart factory and logistics solutions in supporting Saudi Arabia’s Industry 4.0 ambitions.

Interview excerpts Salam launched B2B 2.0 at LEAP 2026. What does this evolution mean in practice, and how does it change the way Salam engages with enterprise customers? Salam B2B 2.0 represents

SEPTEMBER 2026

Abdullah Khorami, Chief Business Officer at Etihad Salam Telecom Company (Salam). our transformation from a traditional telecommunications provider into an integrated digital transformation partner. Our role is to bridge the gap between what customers need and what technology vendors offer. This repositioning allows us to remain relevant to enterprise customers, understand their business priorities, and deliver solutions aligned with their operational requirements. It marks a shift from selling telecommunications services to building long-

term partnerships focused on digital transformation and measurable business outcomes.

Many digital transformation projects struggle to deliver their intended outcomes. Why do you believe enterprises need a digital transformation partner rather than multiple technology vendors? Research cited by Boston Consulting Group indicates that 77 per cent of digital

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transformation projects fail to realise their potential value. Several factors contribute to this, including integration challenges, limited access to specialists capable of managing complex deployments and misalignment between technology solutions and business objectives. New technologies and vendors continue to emerge, making it difficult for enterprises to manage multiple providers independently. Organisations need a partner that understands their industry, operates close to the market and can integrate technologies from different vendors into a complete end-to-end solution. Salam aims to fill this gap through its expanded portfolio, partner ecosystem and understanding of key industry verticals. This approach helps ensure that technology deployments are aligned with the outcomes businesses want to achieve.

Your LEAP showcase spans AI, IoT, cybersecurity and cloud technologies. How do these capabilities come together to deliver measurable business value rather than isolated technology deployments? Our portfolio was developed through surveys and discussions with customers, vendors and technology partners. We used these insights to select products and services that can be integrated into cohesive

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solutions. Most of the technologies showcased at LEAP can work together to address specific business requirements. The focus is not on selling individual products based solely on their features. Salam combines AI, IoT, cybersecurity, cloud and connectivity capabilities to deliver integrated outcomes aligned with each customer’s operational and strategic objectives.

Industry 4.0 is a major focus area for Saudi Arabia. What role can solutions such as Salam’s Smart Factory command centre play in helping the Kingdom accelerate industrial modernisation? Smart factories, smart buildings and intelligent logistics systems can operate as part of an interconnected industrial ecosystem. Salam’s Smart Factory solution uses industrial IoT sensors to collect operational data and provide owners and decision-makers with relevant information at the right time. Integrating this capability with smart logistics solutions can help organisations monitor equipment, manage its

Salam B2B 2.0 represents our transformation from a traditional telecommunications provider into an integrated digital transformation partner.

movement and improve delivery operations. AI and other digital technologies can further support logistics planning, asset visibility and operational decisionmaking. These integrated capabilities can help industrial organisations improve efficiency and advance Saudi Arabia’s Industry 4.0 ambitions.

The theme of Salam’s participation this year is “Powering What’s Next.” What does that vision look like for Saudi Arabia’s digital economy over the next decade? Saudi Arabia’s digital economy is expanding rapidly. Its contribution to GDP has increased significantly and is expected to approach 20 per cent by 2030. Salam wants to contribute to this growth by developing new solutions, introducing advanced technologies and opening its infrastructure to vendors and partners seeking to bring innovation to Saudi Arabia. The Kingdom has established clear performance indicators that can be translated into practical technology projects. Companies seeking to succeed in the market must understand these national priorities, select the right partners and combine the appropriate technologies and services. Salam intends to support this journey through innovation, collaboration and integrated digital solutions.

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INTERVIEW

IFS

IFS ADVANCES INDUSTRIAL AI ADOPTION IN SAUDI ARABIA Mohammad Saddeh, Country Sales Leader, Saudi Arabia, IFS, discusses the company’s partnership with Microsoft, investment in the Kingdom and approach to embedding AI within asset-intensive operations

Saudi Arabia’s Vision 2030 is accelerating technology investment across assetintensive sectors, creating growing demand for AIpowered operational systems that improve productivity, resilience and service delivery. IFS is strengthening its presence in the Kingdom by investing in local capabilities, developing its Saudi partner ecosystem and building deeper customer relationships. In an interview with CNME at LEAP 2026, Mohammad Saddeh, Country Sales Leader, Saudi Arabia, IFS, discusses the company’s collaboration with Microsoft, the role of industrial AI across critical industries and how organisations can transition from traditional infrastructure to AI-powered operations by prioritising measurable business outcomes.

Interview excerpts Could you elaborate on IFS’ participation at LEAP 2026, particularly through its partnership with Microsoft? LEAP is a strategic event and an important platform for IFS because it brings together the technology ecosystem,

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customers and decisionmakers shaping Saudi Arabia’s technology vision. Our participation also reflects the strength of our ecosystem and relationship with Microsoft. IFS brings deep industry capabilities across areas such as asset lifecycle management, field service management, manufacturing and complex industrial operations. Microsoft provides the cloud infrastructure required to support these solutions, enabling customers to benefit from the combined strengths of both companies.

Where does Saudi Arabia fit into IFS’ broader Middle East strategy, and what investments are you making in the Kingdom? Saudi Arabia is a strategic growth market for IFS, not only regionally but globally. Vision 2030 is driving transformation at scale, aligning closely with our strengths across assetintensive and service-centric industries. Our strategy is centred on establishing a sustainable, long-term presence in the Kingdom. We are investing in our local organisation and capabilities, developing a strong

Saudi partner ecosystem, collaborating with strategic technology partners and strengthening relationships with major customers across our core industries. Our objective extends beyond selling technology. We want to partner with customers throughout their digital transformation journeys and help translate technology investments into tangible business outcomes.

How is IFS integrating AI across asset lifecycle management, field service management and other industrial operations? Our approach is to embed industrial AI directly into operational workflows, where critical decisions are made by people. In assetintensive environments, AI can help organisations assess asset conditions, predict potential failures, optimise maintenance schedules and make better decisions throughout the asset lifecycle. In field service operations, it can help determine which technician should be dispatched, the skills and spare parts required, and the right time to complete

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the work. This can improve service-level performance, reduce costs, and strengthen margins. The strength of our approach lies in combining AI capabilities with deep industrial expertise and proprietary industry data models. The objective is to improve asset availability, increase workforce productivity, reduce costs and deliver better service outcomes.

Which sectors in Saudi Arabia could benefit most from industrial AI? Saudi Arabia is particularly well positioned to benefit from industrial AI because much of the transformation under Vision 2030 involves asset-intensive industries and infrastructure. We see significant opportunities across energy and utilities, manufacturing, telecommunications, infrastructure, construction and engineering. Organisations in these sectors manage complex assets at scale, and we are seeing strong demand for technologies that can improve operational performance, resilience and decisionmaking.

How can organisations transition from traditional industrial infrastructure to AIpowered operations while remaining resilient? Organisations should begin by defining the business outcome they want to achieve rather than treating AI as an objective in itself. In

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Mohammad Saddeh, Country Sales Leader, Saudi Arabia, IFS.

an industrial context, the desired outcome could be improving asset availability, reducing unplanned downtime or increasing technician productivity. The next requirement is the right operational data model, industry context and workflows. AI capabilities can be combined with these foundations and delivered to frontline employees and

other decision-makers within their daily operational environment. This connected approach allows organisations to transition progressively from traditional processes to AI-powered operations. IFS supports this journey by combining AI capabilities, industry expertise and operational workflows designed for asset-intensive sectors.

SEPTEMBER 2026

INTERVIEW

Octave

OCTAVE ADVANCES INDUSTRIAL INTELLIGENCE THROUGH CONNECTED DATA Allam Al Beainy, Director of Sales – Middle East and Africa, Octave, discusses the company’s evolution from Hexagon’s Asset Lifecycle Intelligence division and explains how contextualised data can support scalable AI and intelligent transformation.

Industrial organisations have invested extensively in digital technologies, yet fragmented data across multiple products, processes and systems continues to limit transformation. Connecting and contextualising this information across the asset lifecycle can help businesses make faster, better-informed decisions while establishing a reliable foundation for AI. In an interview with CNME at LEAP 2026, Allam Al Beainy, Director of Sales – Middle East, Türkiye and Africa, Octave, explains how the newly independent company is building on decades of experience from Hexagon’s Asset Lifecycle Intelligence division. Al Beainy also discusses Octave’s “Unleashing Intelligence at Scale” strategy and its role in helping organisations design smarter, build faster, operate more efficiently and protect critical infrastructure.

Allam Al Beainy, Director of Sales – Middle East, Türkiye and Africa, Octave.

Interview excerpts Octave is a new name at LEAP. Who is Octave? Octave may be a new

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name, but the company brings decades of industry experience. This is our first LEAP under the Octave brand, although we have participated throughout the event’s journey under the Hexagon name. Octave was launched as an independent company at the beginning of this year following a spin-off from Hexagon’s Asset Lifecycle Intelligence division. We help organisations across multiple industries realise the value of digital transformation throughout the asset lifecycle, from design and construction to operations and protection. Our goal is to bring data and information together so organisations can unleash intelligence at scale.

Your theme at LEAP is “Unleashing Intelligence at Scale.” What does that mean? Organisations do not necessarily have a shortage of data. The challenge is that their data is scattered across multiple products, processes and systems. Our focus is to bring this data and information together, place it in the right context and provide organisations with a strong digital foundation. This enables them to use their data effectively and make betterinformed decisions more quickly.

AI is obviously a major topic at LEAP. How does Octave see the role of AI in industry? AI offers enormous potential, but it cannot deliver value in isolation. Its effectiveness

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depends on the quality and context of the data behind it. Octave helps organisations establish accurate, properly contextualised data across the entire asset lifecycle, from design and construction to operations and the protection of critical infrastructure. Once this foundation is in place, organisations are better prepared to scale AI and generate meaningful value from it.

What is holding organisations back from achieving true digital transformation? One of the biggest challenges is data fragmentation. Organisations possess significant volumes of data, but it is often distributed across multiple systems following extensive investments in different technology tools. Businesses do not necessarily need to expand their technology stacks. The priority should be to integrate their existing information, contextualise the data, and enable its continuous flow across the entire asset lifecycle. This will allow organisations to progress from digital transformation to intelligent transformation and unlock the value of their data at scale.

Our goal is to bring data and information together so organisations can unleash intelligence at scale.

What did Octave demonstrate at LEAP? We are demonstrating how data intelligence can prepare organisations for the next stage of their transformation journey. We will show how continuous data flow across the entire asset lifecycle can help organisations design smarter, build faster, operate more efficiently and protect their most critical infrastructure.

What does the future of industrial digital transformation look like? The industry is moving from digital transformation towards intelligent transformation. Organisations are increasingly focused on using and contextualising the data they already possess. The future is not about adding further complexity through multiple technology platforms. It is about making existing data work harder for the organisation and using it to generate greater operational and business value.

What did visitors take away from Octave at LEAP? AI is undoubtedly important, but it should not introduce additional complexity into an organisation. We want visitors to understand the importance of bringing information together and establishing a strong data foundation that enables them to scale their AI journey effectively.

SEPTEMBER 2026

INTERVIEW

Ericsson

ERICSSON POWERS SAUDI ARABIA’S NEXT PHASE OF DIGITAL TRANSFORMATION AND INNOVATION Ante Mihovilovic, Vice President and Head of Networks, Europe, Middle East and Africa, Ericsson, spoke to CNME at LEAP 2026 about Saudi Arabia’s rapid digital transformation, the evolution of 5G, AI-powered network automation, cloud-native telecom infrastructure and the technologies shaping the next phase of connectivity.

Saudi Arabia’s rapid digital transformation is strengthening its position as an emerging global technology hub, driven by Vision 2030, growing international investment and an expanding technology ecosystem. Global companies are establishing and strengthening their presence in the Kingdom, attracted by its talent, ambitious digital agenda and accelerating adoption of advanced technologies. Ericsson is among the companies contributing to this transformation, supporting the connectivity foundations required for an increasingly digital economy. In an interview with CNME at LEAP 2026, Ante Mihovilovic, Vice President and Head of Networks, Europe, Middle East and Africa, Ericsson, discusses Saudi Arabia’s growing influence on the global technology dialogue, the evolution of 5G and 5G Standalone, AI-powered

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network automation, cloudnative infrastructure and the technologies shaping the next phase of telecom transformation.

Interview excerpts Saudi Arabia is rapidly emerging as a major technology hub. How do you see the Kingdom shaping the global technology landscape? Saudi Arabia’s transformation is happening incredibly quickly. Vision 2030 has set an ambitious direction for the Kingdom, and you can see changes taking place every day. Saudi Arabia is probably one of the most digitalised countries I have lived in, and I have lived in many countries. There is very little that cannot be done online today, from government services to communications and everyday activities. What makes Saudi Arabia particularly interesting is the speed at which technology

moves from discussion to deployment. Technologies are being implemented and tested very rapidly. LEAP itself demonstrates this momentum. This is its fifth edition, and you can see companies and technology leaders from across the world coming to Saudi Arabia. Ericsson has participated since the beginning, while this is personally my second LEAP since moving to the Middle East two years ago. There is tremendous optimism in the market, much of it connected to Vision 2030. Technology companies, operators and the wider ecosystem are contributing to this transformation. Saudi Arabia has established a reputation for being at the forefront of technology adoption.

How are 5G and Open RAN reshaping network strategies for telecom operators in Saudi Arabia? 5G has opened significant new opportunities for operators

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Ante Mihovilovic, Vice President and Head of Networks, Europe, Middle East and Africa, Ericsson.

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INTERVIEW

28 to expand into different segments. Connectivity is no longer only about sending messages or making calls. It is increasingly about connecting different aspects of society and industry. This includes mission-critical networks and connectivity across industries, where networks need to remain constantly available and reliable. Particularly during periods of regional uncertainty, resilient connectivity becomes even more important. There is also the consumer dimension. Fixed Wireless Access, gaming and streaming are examples of how 5G is changing everyday connectivity. Many of the use cases that the industry has envisioned for years are now becoming a reality. On the radio side, our

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Open RAN-ready portfolio gives operators greater flexibility to integrate network components from multiple vendors, helping reduce vendor lock-in. This promotes competition and innovation while giving operators greater choice and control over their network investments.

Saudi Arabia is building the digital foundations for future generations. How is Ericsson contributing to that journey? We contribute primarily

Saudi Arabia has established a reputation for being at the forefront of technology adoption.

through our technology. If you want to digitalise society, everything relies on stable, reliable and highperformance connectivity. This is where Ericsson has considerable strength. We work across different industries in Saudi Arabia, including with government entities and telecom operators, helping provide the underlying connectivity foundation that enables organisations to introduce new digital services.

How can AI and automation improve network performance, reliability and operational efficiency? Automation is a key element, but effective automation requires strong

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processes and a solid network foundation. AI can then be used to enable networks to operate with less manual intervention while improving efficiency, including energy efficiency. This is particularly relevant in Saudi Arabia because the Kingdom has ambitious sustainability objectives connected to Vision 2030. When we discuss networks, we increasingly talk about levels of autonomy. Highly autonomous networks can operate with significantly reduced human intervention. Energy optimisation is one area where AI can make a major difference. Networks contain increasing amounts of equipment, which naturally consume energy. AI can analyse traffic patterns and determine when certain equipment can be temporarily powered down while maintaining the required network performance. One important differentiator is that we can introduce AI capabilities across equipment that has already been deployed over the past five or six years through software updates. Hajj is a good example. We use AI-powered capabilities to steer network traffic during one of the world’s largest annual gatherings, using infrastructure that may have been deployed several years earlier. Technology continues to evolve rapidly, but operators can still prepare their existing networks for future use cases.

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What are the key benefits and challenges of adopting cloud-native telecom networks? The key benefits are flexibility and scalability. Traditionally, individual network functions often required dedicated infrastructure. This resulted in numerous separate systems across the network, each consuming energy and requiring its own operational expertise. With cloud-native architecture, resources can be used according to demand. When fewer resources are required, consumption can be reduced, helping lower both costs and energy usage. When additional capacity is required, operators can scale much more easily. Multiple network functions can also operate on a common platform and share resources. Once everything operates on a common infrastructure, it also becomes much easier to introduce AI and automation.

How can telecom operators modernise their networks while reducing energy consumption and operating costs? Operators can adopt newer generations of network technology, with each generation delivering improvements in energy efficiency. However,

Technology continues to evolve rapidly, but operators can still prepare their existing networks for future use cases.

significant gains can also be achieved through software enhancements to the existing installed base. We continue to improve the energyperformance envelope, with meaningful efficiency gains possible year after year. When operators combine those improvements with greater automation and AI capabilities, the potential benefits become much larger. AI can optimise how network resources are used, helping operators maintain performance while reducing unnecessary energy consumption.

What technology priorities will define the next phase of telecom transformation? The next major evolution will be 5G Standalone. A great deal of focus so far has been on deploying 5G infrastructure, but 5G Standalone opens the door to the full potential of 5G and differentiated connectivity. Different applications require different network characteristics. Gaming may require extremely low latency, while someone working from home needs highly stable and reliable video connectivity. Financial services may require connectivity with particularly strong security characteristics. Network slicing makes it possible for a single network to support these different requirements and deliver differentiated connectivity depending on the use case. I believe we will see significant advances in this area going forward.

SEPTEMBER 2026

INTERVIEW

Mannai

MANNAI ADVANCES CONNECTED TECHNOLOGY AND DIGITAL RESILIENCE IN SAUDI ARABIA Sumanta Roy, Group ICT President, Mannai Corporation, discusses connected stadiums, sports technology, scalable digital platforms and AI-powered cyber resilience at LEAP 2026.

Saudi Arabia’s accelerating digital transformation is creating new opportunities for organisations to build secure, scalable technology foundations while supporting economic diversification. Sports technology is also emerging as a key area of innovation, with AI, cloud and data reshaping athlete performance, connected stadiums, fan engagement and coaching. In an interview with CNME at LEAP 2026, Sumanta Roy, Group ICT President, Mannai Corporation, discusses Mannai Information Technology’s growing presence in Saudi Arabia, its connected-platform capabilities, the evolution of the Kingdom’s sports technology ecosystem and the role of AI in strengthening cyber resilience.

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Sumanta Roy, Group ICT President, Mannai Corporation.

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Interview excerpts What is Mannai Information Technology showcasing at LEAP 2026, and are there any new announcements to highlight? Mannai Information Technology is relatively new to Saudi Arabia, so LEAP 2026 provides an important opportunity to introduce our brand and showcase the work we have delivered across the GCC. Our capabilities cover connected platforms, stadiums, buildings and airports. This year, we are focusing particularly on connected stadiums and the broader sports technology ecosystem surrounding them. We have not made a specific announcement at LEAP. Mannai is committed to expanding its footprint across the Gulf, the wider Middle East and Africa, with a particular focus on new opportunities in North Africa and the Gulf region.

How is digital transformation supporting Saudi Arabia’s economic diversification? Saudi Arabia has an opportunity to leapfrog legacy technologies and build its digital infrastructure from the ground up. Instead of retrofitting older systems, the Kingdom can establish a strong digital spine that supports use cases across citizen services, education, healthcare and other sectors. A digital foundation designed to work across industries, remain secure, and scale

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effectively can support the creation of new services and business models. This approach enables economic diversification to be incorporated into the Kingdom’s digital development from the outset.

How can AI, cloud and data create smarter stadiums and transform fan experiences as Saudi Arabia’s sports ecosystem evolves? Sports technology can be viewed across four main areas. The first focuses on athletes and performers, using data to monitor factors such as nutrition, weight, movement and overall performance. Similar technologies can also support motorsport by analysing variables such as weather and track conditions. The second area is the instadium experience, including connectivity, content, instant replays and other digital services. The third is the wider fan experience, covering how supporters follow teams, access replays, engage with events and purchase merchandise. The fourth area concerns aspiring athletes. Technology

Mannai is committed to expanding its footprint across the Gulf, the wider Middle East and Africa, with a particular focus on new opportunities in North Africa and the Gulf region.

can help a young footballer assess physical development, identify the most suitable playing position and access personalised coaching. This could include guidance from professional coaches or AIpowered training platforms. Demand for these capabilities is high, and the technology is developing rapidly. The diversity of applications means sports technology can deliver value to athletes, venues, fans and emerging talent.

What practical steps can organisations in the Kingdom take to strengthen resilience amid an evolving regulatory and threat landscape? Artificial intelligence can be used both to launch cyber threats and defend against them. AI-powered security tools can analyse patterns, identify anomalies and detect potential threats faster than many traditional technologies. No enterprise can assume it is completely protected from cyberattacks. Organisations must therefore focus not only on prevention but also on how quickly they can recover following an incident. AI can support this process by helping organisations isolate threats, protect critical computing environments and prioritise the restoration of essential services. Strong resilience requires effective threat detection, well-defined recovery priorities and the ability to restore operations quickly.

SEPTEMBER 2026

INTERVIEW

Egnyte

GOVERNED PROJECT DATA UNLOCKS AI VALUE IN AEC Stan Hansen, Chief Operating Officer at Egnyte, explains how connected project information, purpose-built AI agents and safeguards can support secure AI adoption across the Middle East.

Egnyte has expanded its Middle East offering with AI-powered capabilities designed to help architecture, engineering and construction (AEC) firms connect, govern and extract intelligence from complex project information. The enhancements include Project Hub, purpose-built AI agents, AI Safeguards and right-to-left language support for its Arabic web interface. In an exclusive interview, Stan Hansen, Chief Operating Officer at Egnyte, discusses why effective AI requires trusted project context, how specialised agents can support complex projects and the role of governance in scaling AI securely across the region.

Interview excerpts Why does effective AI require connected, wellgoverned project context rather than simply access to documents? Content is the fundamental layer that powers AI in knowledge work. To produce relevant business outcomes, AI needs more than access to documents. It needs to understand the connected information and relationships

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between content, projects, people, systems, and industry knowledge. Furthermore, the content that AI processes should follow the data governance principles set by the organisation. This is where Egnyte provides the trusted industry context that helps AI deliver more accurate answers and automate specialised workflows, especially for the built environment. Our AI Safeguards prevent sensitive data from being included in AI-generated responses. Egnyte helps organisations establish the connected and governed data foundation needed to apply AI reliably across project delivery.

How can purpose-built AI agents help AEC firms improve efficiency and turn complex project information into actionable intelligence? Middle East region is delivering increasingly large and complex projects involving distributed teams, joint ventures, consultants, contractors, owners, and extensive technology ecosystems. These projects generate enormous volumes of drawings, BIM models,

specifications, contracts, correspondence, and other project information. Egnyte provides an information foundation that helps firms connect this information across teams and technology platforms, apply governance consistently, and use trusted project and business data to power AI. To accelerate AI adoption, Egnyte is introducing three AI agents relevant to the built environment: Specifications Analyst, Contract Analyst, and Building Code Analyst. These pre-built AI agents are grounded in the firm's own governed documents rather than general-purpose AI knowledge. The agents help companies apply AI to large and complex project specifications, analyse intricate contracts, and research building code requirements and surface jurisdiction-specific requirements.

What role does a common data environment play in standardising project structures, managing access and connecting information across multiple platforms? Project information is

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frequently fragmented across offices, jobsites, applications, project teams, and external stakeholders. A common data environment like Egnyte’s Project Hub helps create a consistent information structure so teams can find and work with trusted information while maintaining appropriate controls. Project Hub provides project dashboards, standardised project templates, team and permissions management, and lifecycle automation. It works with Egnyte's broader AEC ecosystem, including integrations with Procore and Autodesk, helping firms connect Egnyte-managed information with purposebuilt project delivery workflows.

Why is Arabic right-toleft language support critical to platform adoption, collaboration and information access across Middle East enterprises? Many enterprise users in the Middle East operate in Arabic as their primary working language. Egnyte’s Right-toLeft (RTL) support for Arabic in the web supports mirrored navigation, bidirectional text handling, and localised interface elements. Native-language UI parity for Arabic removes a critical adoption barrier for enterprises, especially in Saudi Arabia, the UAE, and Qatar, as users can navigate, manage files, and collaborate in their preferred language without workarounds.

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Stan Hansen, Chief Operating Officer at Egnyte.

Egnyte combines RTL UI with its core strengths of enterprise-grade governance, granular permission controls, and hybrid cloud architecture, none of which can be matched by general-purpose tools.

How can organisations apply AI safeguards while using AI tools to generate measurable business outcomes across live projects at scale? As organisations accelerate AI adoption, ungoverned access to sensitive content by AI systems represents a

growing and underappreciated risk. Egnyte’s AI Safeguards addresses this directly by embedding AI controls into the same platform that already manages content, permissions, and governance policies. AI Safeguards enables IT and compliance teams to precisely define which users, groups, file locations, and file properties can be processed by AI. AI interactions are visible and auditable through detailed reports, helping reduce the risk of AI becoming a black box inside the organisation.

SEPTEMBER 2026

INTERVIEW

Workday

AI RESHAPES WORKFORCE PLANNING ACROSS MIDDLE EAST Workday highlights how connected data, agile operating models and responsible AI can help organisations build future-ready workforces

AI is reshaping how Middle East organisations manage talent, develop skills and prepare for future workforce demands. With GCC adoption accelerating, businesses face growing pressure to move beyond isolated pilots and embed AI into core workflows to deliver measurable value. In an interview with CNME, Zakaria Haltout, Group Vice President for the Middle East, Turkey and Africa at Workday, discusses the importance of connected data, agile operating models and responsible governance in scaling AI-led transformation.

Interview excerpts How is AI changing the way Middle East organisations manage people, skills and workforce planning? Across the Middle East, organisations are moving beyond using technology solely to automate administrative processes and are beginning to use AI to augment day-today work, strengthen skills development and help people contribute more strategically to growth and innovation. When people, financial and operational data are brought together with AI-driven insights, organisations can better understand the skills

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Zakaria Haltout, Group Vice President for the Middle East, Turkey and Africa, Workday. they have, anticipate the capabilities they will need and make more informed workforce decisions at speed. This helps leaders move from reacting to talent gaps after they emerge to taking proactive action whether that means developing skills internally, redeploying talent or planning for future demand.

understand that transformation is not simply about access to new technology. Many organisations can launch an AI pilot. But the challenge is moving from experimentation to AI-powered execution. That requires a clear business case, trusted data, leadership commitment and an operating model that enables new capabilities to be adopted at scale. AI initiatives need to be connected to the workflows where work is actually done, not positioned as a separate experiment or another assistant layered on top of disconnected systems. In the GCC, businesses are operating against some of the world’s most ambitious transformation agendas, and adoption is accelerating rapidly. GCC AI adoption has moved from 62% to 84% in two years. The next differentiator will be how effectively organisations turn that momentum into sustainable value. Those that do will combine advanced AI capabilities with the governance, transparency and control needed to move quickly and responsibly.

What separates organisations that succeed in digital transformation from those that struggle to move beyond pilot projects?

How can regional business leaders build operating models that are more agile, data-driven and future-ready?

The organisations that succeed

Agile operating models

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are built on the ability to make informed decisions at speed. That begins with connecting people, finance and operational data so leaders have a shared, trusted understanding of business performance, workforce capacity and the choices available to them. When data is fragmented, organisations spend too much time reconciling information and responding to issues after the fact. When data is connected and paired with AI-driven insights, leaders can identify patterns earlier, model different scenarios and act with greater confidence. This supports a shift from reactive decision-making to proactive action, creating greater agility, resilience and business impact. As work changes, organisations need the flexibility to understand emerging skills needs, develop internal talent and deploy people where they can create the greatest value. Equally important is building governance, accountability and data literacy that allow teams to use AI responsibly. The result is an organisation that can respond faster to change while maintaining the control and confidence required to scale transformation.

What role can cloudbased platforms such as Workday play in supporting the Middle East’s AI and digital transformation ambitions? Workday provides the foundation for organisations to

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turn transformation ambitions into action at the pace the region demands. By bringing together trusted people, financial and operational data, Workday helps leaders make more informed decisions and act on them more quickly. The future of enterprise AI is not about introducing another assistant into the workplace. It is about embedding AI directly into business processes, enabling organisations to automate work, streamline operations and make better decisions in real time. Workday helps customers move beyond isolated AI experimentation and into AI-powered execution, where technology is connected to enterprise data, guardrails and real-world workflows. This is particularly relevant for organisations across the GCC, where the imperative is not only to innovate but to implement faster, accelerate adoption and realise value sooner. Workday can help customers create a more agile and resilient organisation by providing a unified platform for people, finance and operations, with AI-driven insights built into the flow of work.

What practical steps should organisations take now to prepare their workforce for the next phase of AI-led business change? First, organisations should establish a trusted view of their people, skills and work. They need to understand which activities can be automated or augmented, where skills gaps are emerging

and how workforce needs are likely to change. This creates a practical basis for moving from broad AI ambition to focused action. Second, leaders should identify where AI can be embedded into priority workflows to remove routine work, improve decisionmaking and create capacity for higher-value contribution. The most effective initiatives are anchored in tangible business outcomes, such as improving productivity, accelerating planning or strengthening the employee experience. Third, organisations must invest in skills. Technical capability is important, but so are the human skills that help employees work effectively alongside AI: critical thinking, collaboration, creativity, judgement and adaptability. Learning must be continuous, relevant to the work people do and connected to the organisation’s strategic priorities. Finally, organisations should put responsible AI principles into practice from the start. That means clear governance, transparency, appropriate controls and accountability for how AI is used. When innovation operates within trusted data, enterprise guardrails and real-world workflows, leaders can scale AI with greater confidence. The organisations best prepared for the next phase of AI-led change will be those that treat AI as a catalyst for better work, better decisions and stronger business performance, not simply as a technology deployment.

SEPTEMBER 2026

INTERVIEW

Sibia Technologies

FROM USING AI TO WORKING THROUGH AI Rany Tannouri of Sibia Technologies discusses AI-enabled enterprises, evolving telecom models and the future of intelligent customer and government services.

AI adoption is moving beyond individual productivity tools towards intelligent systems capable of executing tasks, coordinating workflows and supporting business operations. Achieving this transition requires connected systems, accessible data and strong governance, alongside a redefinition of how people contribute through judgement, creativity and relationships. In an exclusive interview with CNME, Rany Tannouri, Regional Sales Director at Sibia Technologies, discusses how organisations can become genuinely AI-enabled, why the UAE provides a strong environment for translating AI experimentation into measurable outcomes, and how telecom operators can evolve into digital transformation partners. Tannouri, also explores TravelAd’s approach to engaging international

travellers and explains how AI-powered enterprise communications could simplify customer experiences and government services.

Interview excerpts How can organisations move from employees simply using AI tools to becoming genuinely AIenabled enterprises? For me, there is a big difference between employees using AI and a company actually being AI-enabled. Today, a lot of people are already using tools like ChatGPT or Copilot to write emails, summarise documents, research topics, prepare presentations or analyse information. That's useful, but I see this as the first stage. The next stage is when we start delegating actual tasks to AI. Instead of asking AI to help you do something, you give it an objective, access to the right information and systems, and then your role becomes more about

If AI can take care of more of the repetitive execution, people can spend more time on judgement, relationships, creativity, and the things they are individually very good at. SEPTEMBER 2026

reviewing and validating the outcome. Then you have a third level, which I think is where things become interesting: AI agents and workflows that can manage parts of day-to-day operations with much less human involvement. This is when we move from using AI to actually working through AI. But companies cannot get there just by buying more AI tools. Data needs to be accessible, systems need to communicate with each other, and there needs to be clear governance around what AI can access and what actions it is allowed to take. I also think this will change people's roles. If AI can take care of more of the repetitive execution, people can spend more time on judgement, relationships, creativity, and the things they are individually very good at.

What makes the UAE a strong environment for converting AI experimentation into measurable government and business outcomes? One of the things I really like about the UAE is the speed at which new technologies

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Rany Tannouri, Regional Sales Director, Sibia Technologies

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INTERVIEW

can move from an idea into something practical. There is obviously a very strong push around AI from the leadership, but what I find more interesting is that the conversation is already moving beyond simply saying, "We are using AI."

The questions are becoming much more practical. Did it make the service faster? Did it improve the citizen or customer experience? Did it reduce manual work? Did it improve productivity? Can we deliver a service differently because AI is now available? The UAE also has a strong ecosystem where government entities, telecom operators, technology companies and the private sector work quite closely together. That makes it easier to take an idea, test it and,

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when it works, move towards implementation. I think the next few years will be especially interesting because the measurement of AI success will change. It will not be about how many AI initiatives or PoCs an organisation has. It will be about what those initiatives actually delivered.

How can telecom operators evolve beyond connectivity to become digital transformation partners for enterprise customers? I see a huge opportunity here, particularly from

Data needs to be accessible, systems need to communicate with each other, and there needs to be clear governance around what AI can access.

what we are experiencing through our work at Sibia Technologies across the Middle East and Africa. Telcos already have something that many technology companies would love to have: infrastructure, reach, large enterprise customer bases and established relationships with those customers. The question is what else they can build on top of that. Today, an enterprise doesn't only need a SIM card, internet connection or fibre. They also need cloud communications, AI, cybersecurity, customer experience solutions and many other digital services. If operators can bring these together, their conversation with the customer changes. Instead of discussing only connectivity and price, they can start discussing

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the customer's actual business challenges and how technology can solve them. We are already seeing this transition in different markets. But it also requires a different mindset from the operator. You need the right technology partners, the right solutions, technical capabilities and, importantly, sales teams that are comfortable having a broader technology conversation with customers. For me, that is how the telco moves from being a connectivity provider to becoming a real technology partner.

How is TravelAd helping brands engage international travellers through more relevant and measurable digital communications? The idea behind TravelAd is actually quite simple. International travellers are a very valuable audience, but reaching the right traveller, at the right moment and with something genuinely relevant is not always easy. With TravelAd, we are looking at this differently by combining telecom reach with digital engagement. The platform allows brands, tourism organisations and other stakeholders to engage inbound international travellers through channels they already use, such as SMS, WhatsApp and other messaging platforms. For me, the important part is the context. Someone who has just arrived in Dubai, for example, has completely different intentions and

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needs from someone sitting at home somewhere in Europe or Asia seeing a general advertisement about Dubai. If you understand that travel context, the communication can become much more relevant. It could be an attraction, an experience, a restaurant, an event or another service that makes sense at that particular point in the traveller's journey. At the same time, the engagement becomes measurable. We can understand whether people interacted with the communication, showed interest in an offer or took an action, rather than looking only at advertising impressions. And there is a bigger story behind TravelAd as well. It shows how telecom infrastructure can be used for much more than connectivity. It can help create an ecosystem connecting travellers, brands, tourism organisations and service providers.

How will the convergence of AI and enterprise communications reshape customer experience and government services? I think this is going to completely change what we consider a communications platform. Traditionally, communications technology was mainly about connecting two people.

A customer calls or sends a message, an employee receives it, understands what the customer wants, searches different systems for information, and then tries to resolve the request. With AI, that model starts to change. The platform itself can understand what the customer is asking, understand the context, access the organisation's knowledge and systems and, increasingly, take actions on the customer's behalf. That last part is very important. We are moving from AI that can answer to AI that can actually do. Imagine this from a government perspective. Today, citizens often need to know which government entity, website, application, or department they need for a particular service. In the future, I think that complexity can disappear from the citizen's perspective. You simply explain what you need, and the AI understands the request, accesses the relevant government systems and coordinates the processes behind the scenes. The same applies to enterprises and their customers.For me, the best customer or citizen experience is ultimately the one where the technology becomes almost invisible. The person shouldn't need to understand how complicated the organisation is behind the scenes. They should simply be able to say what they need and get it done.

SEPTEMBER 2026

INTERVIEW

AI SOVEREIGNTY MOVES BEYOND MODELS TO BUILD LASTING VALUE Marco Biaggi, AI and Data Leader at EY MENA, explains how control over data, infrastructure, talent and trusted ecosystems can help the Middle East develop distinctive AI capabilities and drive long-term economic growth.

AI sovereignty is becoming a strategic priority as governments and enterprises seek greater control over the data, infrastructure, talent and technology ecosystems underpinning artificial intelligence. Building these capabilities requires a balance between local ambition, trusted global partnerships and governance frameworks that support responsible innovation. In an exclusive interview with CNME, Marco Biaggi, AI and Data Leader at EY MENA, discusses how the Middle East can move beyond AI adoption to develop distinctive sovereign capabilities, strengthen regional talent and intellectual property, and create long-term economic value through AI-led business transformation.

Interview excerpts Why does AI sovereignty extend beyond models to include control of data, infrastructure, talent and the wider technology ecosystem? SEPTEMBER 2026

AI sovereignty is about much more than where models are hosted. It encompasses control over the data, infrastructure, talent, knowledge, and ecosystem needed to develop, deploy, and scale AI effectively. As AI becomes increasingly embedded across economies, governments, and critical sectors, these capabilities are emerging as strategic national assets that influence competitiveness, resilience, and long-term growth.

How can strategic partnerships help governments and enterprises accelerate sovereign AI development? Building sovereign AI capabilities does not require isolation. The most successful approaches combine local ambition with a trusted ecosystem of partners across every layer of the AI stack, including data, infrastructure, technology, models, talent, and skills. By leveraging external expertise while

simultaneously developing internal capabilities, governments and enterprises can accelerate progress and create sustainable long-term value.

How can organisations establish trusted AI governance without slowing innovation? Organisations should view AI governance as an accelerator of value rather than a constraint on innovation. The goal is not to maximise the number of AI pilots or use cases, but to ensure AI delivers measurable outcomes within a framework of risk management, accountability, and trust. Effective governance helps organisations scale adoption with confidence, enabling innovation that is both responsible and value-driven.

How can the Middle East progress from adopting AI to developing and scaling its own distinctive capabilities? The Middle East's opportunity is not

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Marco Biaggi‫‏‬, AI and Data Leader, EY MENA

simply to adopt global AI technologies, but to build capabilities that reflect its own economic priorities, languages, and market needs. Achieving this requires continued investment in talent, innovation ecosystems, and local AI development, while leveraging global partnerships to accelerate knowledge transfer and capability building. Over time, this combination of strong regional demand, local innovation, and international collaboration can enable the region to create AI solutions that are both globally competitive and uniquely relevant to the markets it serves.

How can sovereign AI ecosystems generate long-term economic value through investment, talent, intellectual property, and new industries? Sustainable value is created when AI moves beyond isolated use cases and becomes embedded across business operations and industry value chains. AIled business reinvention drives demand for new skills, intellectual property, products and services, creating a multiplier effect across the wider economy. In the long term, the most successful ecosystems will be those that enable organisations to become AI-native, unlocking continuous innovation, productivity gains and new sources of growth.

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SEPTEMBER 2026

OPINION

JAGGAER

RISING COST PRESSURES MAKE TAIL SPEND A STRATEGIC PRIORITY Better visibility, guided buying and AI-driven automation can help organisations control fragmented expenditure and offset external cost shocks, writes Francesco Colavita, SVP, MEAPAC, JAGGAER.

For most business leaders, the past two years have been defined by forces largely outside their control. Inflation has proven stubborn across major economies, with the IMF estimating global inflation at 5.8% in 2024. At the same time, operating costs continue to fluctuate unpredictably. Energy prices, for instance, remain volatile, with petrol prices in the UAE now just a hairsbreath from AED4 per litre, amid global pressures. These are the kinds of macroeconomic shifts that dominate boardroom discussions. They are significant, highly visible, and often difficult to control beyond hedging and longterm planning. But in focusing so intently on these headline challenges, many organisations are overlooking a quieter, more insidious trend. Cost unpredictability is no longer confined to bigticket items. It is steadily moving downstream into thousands of small, routine transactions that rarely

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receive the same scrutiny. This is where tail spend begins to matter, and why it is becoming far more dangerous than it first appears.

When small costs stop being small Consider something as routine as fuel. For a company managing a fleet of delivery vehicles, even a modest increase per litre compounds quickly across daily operations. The same principle applies across the business. A marketing team signs off on a lastminute campaign tool. An IT department adds another SaaS subscription to solve a niche problem. An office manager orders equipment from a convenient supplier rather than a preferred one. Individually, these decisions feel insignificant. They are quick to approve, low in perceived risk, and often necessary in the moment. But collectively, they form what is known as tail spend: non-core categories of

expenditure spread across multiple suppliers, often without central oversight. As this spend becomes more fragmented, it creates additional complexity across purchasing, accounts payable processes, cost control, and governance. What appears small and manageable at the transaction level can quickly become difficult to monitor, standardise, and optimise at an organisational level.

Death by a thousand paper cuts Tail spend is often dismissed as administrative noise, but its cumulative impact tells a very different story. In many organisations, these low-value, high-frequency, high-volume transactions can account for 20% or more of total procurement spend, yet receive a fraction of the oversight. To make this tangible, imagine a midsized enterprise with US$200 million in annual indirect spend. If even 10% of that sits in unmanaged or poorly controlled purchasing, that

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Francesco Colavita, SVP, MEAPAC, JAGGAER.

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SEPTEMBER 2026

OPINION

is US$20 million exposed to inefficiencies. Time dedicated to this activity can account for as high as 50% the overall procurement and purchasing activities, taking focus away from the most strategic and value-oriented procurement areas.

What makes this particularly compelling is that, unlike large strategic sourcing decisions, addressing tail spend does not require trade-offs that impact core business operations. There is no need to compromise on quality, delay major initiatives, or renegotiate critical supplier relationships. Instead, it is about tightening control over areas that have historically been overlooked.

Why traditional approaches fall short While the opportunity is clear, curtailing tail spend is often slowed by organisational friction. Procurement teams are typically structured to focus on high-value sourcing activities where the stakes are highest. Meanwhile, employees across the business often bypass formal processes for smaller purchases because they perceive them as too slow or restrictive. Procurement cannot realistically review every low-value transaction, and employees are incentivised to prioritise convenience over compliance. Over time, this creates a culture where “small” spend operates outside the guardrails of strategic procurement. This type of spend is also the

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one that generates more ‘maverick’ spend, and spend not against contract.

Turning control into a seamless experience This is where a more intelligent, AI-driven approach begins to shift the equation. Rather than attempting to enforce control through manual oversight, organisations can embed it directly into the purchasing process itself. The first step is visibility. Businesses need a clear understanding of what constitutes tail spend within their own context. For some, that might be purchases under $5,000; for others, the threshold could be higher. More importantly, it requires identifying which categories generate the highest volume of low-value transactions and where inefficiencies are most likely to occur. Without this baseline, any attempt at optimisation is effectively guesswork. From there, the focus shifts to simplifying decisionmaking. Instead of routing every purchase through complex approval chains, organisations can define clear thresholds and policies that allow routine transactions to flow automatically. For example, a facilities team ordering standard office

The most meaningful gains are often not found in the headline numbers, but in the thousands of small decisions that shape them.

supplies should not need multiple layers of sign-off if the purchase falls within predefined limits and approved categories. The goal is not to remove control, but to apply it more intelligently with insight and optimisation scenarios.

Embedding intelligence into everyday decisions The real transformation happens when AI is introduced as an active participant in these workflows. Rather than acting as a passive system of record, it can guide purchasing decisions in real time. Imagine an employee attempting to buy a new laptop. Instead of searching externally, the system presents pre-

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approved options from preferred suppliers, highlights negotiated pricing and flags any deviations from policy. This approach not only reduces costs but also eliminates the friction that often leads to off-contract spending in the first place. Employees are not forced to navigate cumbersome processes; they are simply guided towards better decisions. Equally important is the role of supplier management. By consolidating low-value purchases through a curated list of approved vendors, organisations can unlock pricing advantages that would otherwise be inaccessible. AI can continuously monitor these relationships,

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identifying opportunities for better terms or alternative suppliers without requiring constant manual intervention.

Continuous improvement, not one-off optimisation Effective tail spend management is not a onetime initiative. It requires ongoing monitoring and refinement. Adoption rates, compliance levels, and realised savings all provide valuable insights into how well the system is functioning. Human oversight remains critical, not as a bottleneck, but as a safeguard to ensure that automation operates within defined boundaries. Over time, this creates a feedback loop where policies, thresholds, and supplier

strategies evolve based on real-world data. The result is a procurement function that is both more efficient and more responsive to changing business needs.

A practical starting point for AI-driven ROI Reeling tail spend back in doesn’t just deliver marginal gains. It shifts the narrative. Instead of chasing efficiencies in areas beyond their control, organisations can start by addressing what is right in front of them. That matters because, in today’s environment, the most meaningful gains are often not found in the headline numbers, but in the thousands of small decisions that shape them.

SEPTEMBER 2026

OPINION

DXC Technology

MIDDLE EAST IS PRIMED FOR PHYSICAL AI, BUT IS GOVERNANCE READY? Autonomous systems can unlock significant value across the region’s assetintensive industries, but governance must evolve before AI begins acting at machine speed, writes Mohamed El Yahya, Managing Partner, Global Infrastructure Services, Middle East and Africa, DXC Technology.

Artificial intelligence (AI) is moving beyond screens and into systems that can move, touch and act in the physical world through robots, machines, vehicles and infrastructure. One market forecast estimates that the Physical AI market will grow from roughly US$7 billion in market value in 2026 to more than US$430 billion by 2030. If verified, that would show how quickly capital and attention are shifting. For the Middle East, where strategically important industries are built around physical assets and complex operations, the opportunity is difficult to ignore. Oil and gas remains a cornerstone of Gulf economies, while logistics is becoming increasingly important as the region positions itself as a global trade and transportation hub. These are precisely the environments where physical AI could have significant impact, from autonomous inspection and maintenance to intelligent logistics,

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robotics and increasingly automated industrial operations. The opportunity is considerable, but so is the question that comes with it. As AI moves from generating information to making decisions and taking action, how should organisations govern systems that can act at machine speed and increasingly affect the physical world?

The real risk is not rogue AI Popular narratives about AI swing between utopia and apocalypse. Robots will save us, or robots will destroy us. Both miss the point. The real threat is not rogue AI or sentient machines, but ungoverned autonomy. Agents operating at machine speed, connected to

The real threat is not rogue AI or sentient machines, but ungoverned autonomy.

imperfect data and deployed through operating models never designed for physical consequences, are the real risk. Imagine a logistics operation running hundreds of autonomous machines. A routine update introduces a subtle data mismatch, several systems begin operating outside approved parameters and one enters an area occupied by people. There is no malice. There is no sentience. There is simply autonomy operating at speed, connected to stale or inaccurate data, without effective guardrails. Enterprises have seen this failure pattern for decades with software, where rapid deployment, siloed ownership and governance bolted on after something breaks, have become the norm. Physical AI simply makes those familiar gaps consequential.

Five reasons physical AI changes the governance equation Physical AI does not add one new risk. It amplifies

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existing governance gaps simultaneously. First is kinetic agency. AI does not simply recommend an action. It moves, touches and changes the physical world, while many existing risk frameworks still assume a predominantly digital impact. Second is speed of action. Autonomous systems can make decisions at machine speed, while approval workflows and oversight processes remain designed around human timescales. Third is data dependency. Physical AI relies on realtime sensor data combined with enterprise information. Data quality is no longer simply a prerequisite for good analysis. It becomes an operational control. Fourth is self-optimisation. As systems adapt how they achieve objectives, traditional changemanagement processes can struggle to keep pace. Finally, there is the expanded attack surface. Prompt injection in AI-enabled systems, sensor spoofing and adversarial inputs introduce new vulnerabilities into systems that can have consequences beyond the digital environment. The catastrophic scenario therefore isn't the dramatic robot rebellion. It is mundane, predictable wrongness at scale, from misread information and incorrect temperatures, to routing collisions or flawed decisions. Each is trivial in isolation, but multiplied across thousands of agents and millions of decisions, minor issues can become regulatory,

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Mohamed El Yahya, Managing Partner, Global Infrastructure Services, Middle East and Africa, DXC Technology.

reputational or operational events.

The same question applies to digital agents Physical AI governance and the region's broader ambitions for agentic AI reinforce each other rather than compete for attention. Getting physical AI governance right builds the muscle, and the trust, needed for agentic AI, more broadly, so organisations that invest here put themselves ahead on both fronts at once. The governance principles required when AI can control

a machine share many of the same foundations as those required when an AI agent can act on behalf of a citizen, customer or employee. Across the Middle East, governments and businesses are exploring AI systems that can increasingly act on behalf of people. The UAE’s growing focus on agentic AI in government services is one example of a future where AI agents could navigate processes, make decisions and execute tasks with a degree of autonomy. These systems may not have wheels, motors or robotic arms, but

SEPTEMBER 2026

OPINION

the underlying governance question is remarkably similar. What authority does an agent have? What data can it access? What decisions can it make? Who is accountable when it gets something wrong? How quickly can its actions be detected, stopped or reversed? These questions matter whether an AI agent is directing a machine in a warehouse or helping to deliver a government service. When governance failures occur in digital systems, the impact can already be financial, operational or reputational. When those systems are connected to critical services and interact directly with the public, the consequences can become much broader. The principle is therefore bigger than physical AI. As AI becomes more autonomous, governance has to evolve alongside it.

Two futures. Same technology. The Middle East has an

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opportunity to approach this differently. Rather than waiting for autonomy to become widespread and then bolting governance on after something goes wrong, organisations can begin thinking about governance at the same time they think about autonomy. That is particularly important in a region where governments and businesses are making ambitious bets on AI and moving quickly to turn those ambitions into operational reality. One path leads to autonomous systems being deployed quickly, with unclear identities and boundaries, fragmented ownership, compliance added after deployment and human oversight operating at machine speed. Data quality issues, security vulnerabilities and small operational errors compound until the organisation can no longer intervene effectively.

The other looks very different. Autonomy is developed with clear accountability, defined boundaries, governed access to data, appropriate testing and continuous oversight. The technology is the same, but the operating model around it changes what that technology can safely achieve. The Middle East is already thinking seriously about what AI can do for its economies, governments and industries. The next question is how seriously it thinks about what AI should be allowed to do. The recommendation is simple: before autonomous systems are scaled, organisations should define ownership, data controls, testing standards, escalation routes and clear stop mechanisms. Until then, the issue is not only AI safety. It is governance maturity.

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IFS

FIVE WAYS CONSUMERGRADE AI FAILS IN INDUSTRIAL OPERATIONS Industrial environments require AI grounded in operational context, embedded workflows, trusted data and governance, writes Hannes Liebe, Regional President, APJMEA, IFS AI is everywhere, but most of it was never built for industrial operations. Tools designed for documents, dashboards, and demos break down fast when confronted with assets, uptime, safety, and execution at scale. This is why so many Industrial AI initiatives stall and why Industrial AI exists at all.

Failure #1: Consumer Grade AI Understands Language, Not Industrial Reality Consumer grade AI is exceptional at language. It can summarise documents, answer questions, and generate text with impressive fluency. That strength is also its first failure in industrial operations. Research shows that most industrial AI failures are not caused by weak models, but by a lack of operational and domain context. AI that understands language but not assets, workflows, and constraints simply cannot perform in real operations. (source: Rand) Industrial businesses do not run on language. They run on assets, crews, uptime

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targets, service commitments, safety rules, failure modes, and regulatory constraints. Decisions are not abstract. They are physical, operational, and often irreversible. Generic AI platforms treat context as something you prompt for. Industrial AI treats context as foundational. It understands how assets behave over time, how work is planned and executed, and how decisions ripple across operations. That is the difference between AI that can talk about work and AI that can support work that actually matters. This is why organisations relying on horizontal AI tools quickly hit a ceiling. The AI sounds confident, but it has no operational grounding to make decisions you can trust.

Failure #2: Consumer Grade AI Produces Insight but Cannot Carry Work Most industrial organisations are not short on insight. They are short on follow through. Consumer grade AI excels at surfacing recommendations but stops there. What happens next is left to people, inboxes,

spreadsheets, and disconnected systems. Decisions stall between teams. Execution becomes inconsistent. Value leaks out long before impact shows up. The execution gap is now well documented. While nearly all organisations are investing in AI, most never move beyond isolated use cases. Large-scale impact remains elusive, with only a minority able to translate AI adoption into enterprise-level results. (Source: McKinsey State of AI Report) Industrial AI is designed to close the execution gap. It does not simply recommend what should be done. It embeds intelligence into workflows, coordinating decisions and actions across systems, people, and digital workers. This is a critical competitive divide. AI that stops at insight creates more work. AI that carries work through completion changes performance at scale.

Failure #3: Consumer Grade AI Assumes Mistakes Are Acceptable Most consumer grade and general enterprise AI was built

SEPTEMBER 2026

OPINION

Hannes Liebe, Regional President, APJMEA, IFS.

SEPTEMBER 2026

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for low risk environments. If it produces the wrong answer, the cost is usually time or inconvenience. In low risk environments, hallucinations are inconvenient. In industrial operations, they create financial loss, compliance exposure, and safety risk. In fact, $67 billion was reported as a loss in a single year from business around the globe due to false AI outputs. (Source: Suprmind) Industrial operations do not work that way. Mistakes can shut down production, impact safety, violate regulations, or damage customer trust. AI that is unpredictable, opaque, or difficult to govern introduces risk instead of reducing it. Industrial AI is built for environments where failure is expensive. It operates within defined rules, uses trusted data, and supports explainable, auditable decisions. It is designed to be deployed deliberately, expanded confidently, and trusted in mission critical workflows. This is not a difference in model quality. It is a difference in design philosophy. One assumes experimentation. The other assumes responsibility.

Failure #4: Consumer Grade AI Lives Outside the Systems That Actually Run Operations A common pattern with consumer grade AI is that it lives “on the side.” A chat window. A copilot. A separate interface that users must remember to consult. AI tools that live beside operations are blind to most of what

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matters. Without systemlevel integration, even the best models are working with incomplete reality. (Source: IBM) Industrial work does not happen on the side. It happens inside systems of record that manage assets, service, projects, supply chains, and compliance. AI that sits outside those systems cannot shape outcomes consistently, no matter how intelligent it appears. Industrial AI is embedded where work happens. Inside planning, execution, maintenance, and service workflows. Intelligence is not optional or occasional. It is continuous and operational. This is where many AI buying decisions go wrong. Teams choose tools that look powerful in isolation but cannot change how work actually gets done at scale.

Failure #5: Consumer Grade AI Treats Operations as Experiments, Not Commitments Generic AI platforms are optimised for rapid experimentation. Spin up a pilot. Try a use case. Iterate later. Industrial organisations do not have that luxury. They are responsible for infrastructure, services, and outcomes that economies and communities rely on every day. AI adoption cannot depend on heroics, custom glue code, or a handful of experts. The problem is not experimentation. The problem is stopping there. When AI is treated as a pilot instead of operational infrastructure, it never becomes institutional.

In fact, over 80% of AI initiatives fail to scale beyond pilot or early deployment, resulting in wasted investment and diminishing confidence in effectiveness. (Source: Strategy of Things) Industrial AI is designed to become institutional. It scales across teams, processes, and geographies. Knowledge does not live in prompts or individual users. It is encoded into how the organisation operates. This is the final, decisive difference. Consumer grade AI experiments. Industrial AI runs operations.

Choosing AI That Can Be Trusted to Run What Matters Most AI is no longer a question of possibility; it is a question of suitability. And, the pattern is consistent: most AI fails in industrial environments not because it lacks intelligence, but because it lacks operational grounding, execution capability, governance, and scale ready design. The organisations that win with AI will not be the ones chasing the flashiest demos or the broadest generic platforms. They will be the ones that choose AI built for the realities of their business, where decisions carry operational, financial, and safety consequences. They need AI that understands how work actually gets done, turns insight into action, manages risk, and scales in environments where failure is expensive. That is why Industrial AI is not just another version of enterprise AI. It is the model for applying AI where outcomes matter most.

SEPTEMBER 2026

OPINION SAS UAE

BANKS DO NOT NEED FASTER AI; THEY NEED MORE ACCOUNTABLE DECISIONS AI-native CRM eliminates administrative friction, accelerates quoting and empowers B2B sales teams to build stronger customer relationships.

The UAE has established itself as one of the most ambitious adopters of Artificial Intelligence. The challenge is no longer deploying AI, but ensuring that every AI decision can be trusted, explained and governed. For financial services this has become a leadership issue as much as a technology one. The challenge for the boardroom now is delivering both innovation and responsible AI at the same time. AI is starting to influence decisions at the core of the business, for example, in credit, fraud, pricing, collections, customer engagement, compliance, and operational resilience. These decisions affect customers, regulators, shareholders, employees, and the institution’s ability to compete. Speed alone will not define the next phase of AI in financial services. Banks will need discipline, especially as AI begins to influence decisions that customers and regulators may later challenge. The investment is already happening. The SAS Data and AI Impact Report, with research insights from IDC, found that banks are ahead of other sectors in AI spending and in the adoption of trustworthy AI practices. That sounds encouraging,

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Michel Ghorayeb, Managing Director, SAS UAE.

and it is, up to a point. The same research also shows a trust gap that still exists. Only 11% of banks have both high internal confidence in AI and systems that are demonstrably trustworthy. Nearly half fall into what IDC describes as the “trust dilemma”, either underusing reliable AI because they do not trust it enough or over-relying on AI that has not been properly validated.

Governance considerations Confidence can be misleading. A model can perform well in testing and still fail the institution if the data is fragmented, governance is weak, or no one can explain

how the decision-making process took place. Banking is not forgiving terrain for unclear decisions. The problem usually shows up in ordinary places, such as a credit recommendation that cannot be properly traced, a fraud model that produces too many false positives, or a customer receiving inconsistent treatment across channels. The issue is not only whether the model works but whether the bank can explain, monitor, and adjust the decisions it supports. Governance cannot serve as the final stamp of approval at the end of the innovation process. It has to be part of

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how AI is designed, deployed, and managed from the start. This does not mean slowing everything down. In many cases, good governance helps organisations move faster because teams know the rules. They know which data can be used, which models need review, which decisions require human oversight, and where escalation is needed. In a regulated environment, that clarity is what allows innovation to survive real customers, regulators, and market pressure. In the UAE, the Central Bank continues to emphasise sound risk management, operational resilience, and innovation as the financial sector accelerates its digital transformation. As AI becomes embedded in more customer-facing and business-critical decisions, governance is becoming a strategic business capability. Institution that can innovate quickly while demonstrating transparency and accountability in their AI driven decisions are the ones that will be winning the race.

Getting value Return on investment (ROI) needs the same discipline. Efficiency matters, and banks cannot ignore cost pressure. But the stronger AI business case is not always found in replacing effort. It is often found in improving the quality, speed, and consistency of decisions. The SAS/IDC banking findings support this. Organisations using AI to improve customer experience

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reported stronger returns than those focused primarily on cost savings. The study also found that organisations prioritising trustworthy AI were 60% more likely to report doubling overall return on their AI initiatives. Instead of asking only what can be automated, banks should ask where better decisions can create measurable value, faster and fairer credit assessment, and more accurate fraud detection, among other benefits.

In an enterprise setting, AI agents need more than language models. They require trusted data, advanced analytics, decision logic, governance, and compliance to deliver reliable, auditable outcomes. Banks will use more advanced AI. What is less clear is whether leadership has created firm enough boundaries around where it may act, when it must escalate, and who remains accountable.

The UAE's banking sector is among the region's most digitally advanced.

Delivering value

As competition intensifies and digital banking continues to evolve, the greatest value from AI will not come from automation alone. It will come from improving the quality, consistency, and transparency of decisions while strengthening resilience and building long-term customer trust.

An integrated approach This is where financial leaders play a critical role. AI cannot belong only to data science teams or technology functions. It has to connect with finance, risk, compliance, operations, and customer strategy. The banks that make progress will bring these functions closer together around shared decisionmaking. Agentic AI makes this even more important. AI agents can analyse data, make decisions, and take action across workflows with limited human intervention.

Across the UAE and GCC, financial institutions are responding to rising customer expectations, an increasingly digital banking landscape, evolving fraud risks, and a rapidly changing regulatory environment. As the Central Bank of the UAE continues to support innovation while reinforcing sound governance and resilience across the financial sector, the winner in the AI era will not necessarily be the banks that deploy AI first; they wjll be the institutions that can innovate confidently while demonstrating that every critical decision remains transparent, accountable and worthy of trust. AI will help banks move faster. The harder task is making sure speed does not weaken accountability. In financial services, leadership still comes down to the quality of the decisions made, the evidence behind them, and the willingness to stand behind them when it matters.

SEPTEMBER 2026

OPINION

AVEVA

GEOPOLITICAL INSTABILITY EXPOSES COST OF FRAGMENTED ENGINEERING Overlapping geopolitical, economic and supply chain pressures are turning disconnected engineering workflows into a significant delivery and profitability risk.

Greg Pada, SVP, Head of Engineering Business, AVEVA.

Amid the protracted conflict in Middle East, the world is entering an era of permacrisis. Over the last five years, Covid, the Ukraine war, inflation shocks, and energy crises have shaken the foundations of industry and the global economy. For the engineering, procurement and construction (EPC) sector, this is creating a new phase of industrial

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complexity. Across energy infrastructure, marine assets, data centres and manufacturing, projects are becoming larger, more electrified and more operationally intertwined than at any previous point in history. The onset of the US-IsraelIran war on February 28, where energy prices soared and supply chains came under

strain, represented more than another geopolitical disruption. It marked the end of predictable global logistics that underpinned EPC projects for decades. In its place is something closer to ongoing disruption – geopolitical shocks, climate events, and market instability – which manifests not as isolated incidents but as overlapping pressures.

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Supply chain uncertainty is making cost estimation difficult, while delivery timelines and material costs remain volatile. Some contractors are addressing this contractually by building in price ranges and escalation clauses that pass on uncertainty to clients, but this can only be a temporary solution. At the same time, some companies continue to demand fixed-price contracts despite ongoing volatility. This pushes prices higher and reduces competition, as smaller firms cannot bid on contracts that exceed their risk tolerance. This new environment is shining a light on how disconnected EPC projects have been in the past. They have relied on highly-document focused, fragmented workflows spread across contractors, spreadsheets, emails and isolated data environments. A vast amount of time is lost looking for data and managing the handover inefficiencies that occur between project phases. In times like these, the model’s flaws are moving beyond inefficiency into delivery and profitability risk. In particular, workflows built around email chains and document handovers are becoming a commercial risk. This is especially true in marine infrastructure, utilities, and hyperscale data centres, where assets require coordination across multiple engineering

Catching up with complexity

disciplines.

B&W eliminated 20-30

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The scale of that risk is increasingly evident. A 2025 peer-reviewed study published in Energy Research & Social Science analysed 662 energy infrastructure projects across 83 countries and found that more than three-fifths experienced cost overruns. The researchers revealed that energy infrastructure projects cost, on average, around 40% more than originally expected, with delays most prevalent in large and technologically novel projects. While these overruns are driven by multiple factors – including supply chain volatility and regulatory uncertainty – fragmented engineering and data environments increasingly contribute to coordination failures, design inefficiencies and operational risk across projects. Babcock & Wilcox, the US power industry equipment provider, confronted this problem directly. Running multiple legacy engineering applications with data trapped in silos, the firm found it increasingly difficult to manage drawings and documents across disciplines and project phases. As Max Guillois, director of engineering solutions at B&W, puts it: "If you enhance the quality of the data in the beginning, then you enhance the quality of the project overall." By deploying an integrated engineering environment,

redundant applications, saved around $600,000 per year on a single application alone, and used the unified platform to develop BrightLoop – a lowcarbon hydrogen technology that uses chemical looping to produce hydrogen, steam, or syngas while capturing CO2.

Preserving tacit knowledge In another broad trend, the industry has been slow to adapt to shifting demographics. A generation of experienced engineers will retire globally over the next five to ten years, taking with them decades of accumulated project knowledge that is rarely documented in any transferable form. Geopolitical pressures also affect workforce planning. In some countries, tender rules require a set share of workers to be hired locally, while finding enough skilled labour for complex projects remains a major challenge. Those entering the workforce to replace retiring engineers will be less experienced, more dependent on technology, and expected to deliver at a level the industry may not yet be equipped to support. This highlights the importance of the quality of the underlying engineering data. If the next generation of EPC engineers will rely heavily on AI to do their jobs, the data those systems operate on must be trustworthy.

‘Living’ operations EPC firms are recognising that engineering environments

SEPTEMBER 2026

OPINION

cannot remain isolated from operational environments. Rather than treating design, procurement, construction and handover as separate phases with separate data environments, they are working to create digital asset models that carry value all the way through to client operations. The industry is moving toward a 'living operational model': a continuously updated digital representation of the asset that supports engineering changes, operational optimization, maintenance planning and long-term lifecycle management. For EPCs, the aim is to hand over a fully trusted, operationally meaningful digital asset. A related development is the emergence of asset lifecycle management as a distinct discipline within continuousprocess industries. What marine and offshore clients increasingly want is something purpose-built: a

component, maintenance cycle and operational change across the full life of an asset – from first steel to decommissioning. That is driving growing interest in integrated engineering stacks – environments that bring together what were traditionally standalone solutions for electrical design, piping, instrumentation, simulation, asset management and operational monitoring into a single connected stack. Early results from integrated marine engineering environments have shown productivity gains of upwards of 50%, with design certification processes shortened by a factor of ten. When energy, operational and data systems become tightly interconnected, isolated engineering environments can translate directly into project risk.

system that can track every

The broader significance

SEPTEMBER 2026

An age of continuous change

is that EPC digital transformation is entering a new era. The first phase focused largely on connectivity and data aggregation. The next is likely to centre on operational intelligence: connecting engineering, procurement and construction data into environments capable of supporting continuous decision-making across the full project lifecycle. That shift has important implications for resilience in an EPC context. The events of early 2026 have made the cost of fragility visible on a massive global scale. The same logic applies at the project level. In a world where 'permacrisis' has entered the industrial and global lexicon, EPCs need to maintain continuity and control across complex projects under pressure – and that requires trusted, connected data from first design to final handover.

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RESEARCH ServiceNow

UAE ENTERPRISES FACE GROWING AI EXECUTION GAP

ServiceNow research finds AI spending has increased by 105%, but fragmented systems, limited governance and skills shortages continue to restrict enterprise-wide deployment.

ServiceNow, the AI control tower for business reinvention, today released UAE-specific findings from its Enterprise AI Maturity Index, exposing a critical disconnect between organisations’ AI spend and execution. Despite a 105% year-on-year increase in AI spending, UAE organisations achieved an AI maturity score of 48 out of 100. While this marks a 13-point year-onyear increase, it highlights the shortcomings that must be addressed as UAE organisations move from early experimentation toward more advanced execution. The findings suggest the gap is not due to a lack of investment. Alongside the sharp increase in spending, UAE organisations expect AI to account for almost onefifth of total IT budgets by 2027. Instead, the research shows many organisations are still trying to layer AI onto fragmented technology environments, disconnected data and siloed workflows.

SEPTEMBER 2026

While organisations have made noteworthy progress in AI vision, strategy and leadership, execution remains constrained by lower maturity in AI-enabled workflows and talent development, limiting their ability to scale AI across the enterprise. While agentic AI has emerged as one of the region's defining technology trends this year, the report suggests that, in reality, organisations are approaching autonomous AI deployment cautiously as they work to establish the governance, trust and operational foundations needed to scale it safely. Currently, more than half (57%) of UAE organisations have implemented agentic AI, but only 7% have used it to build autonomous workflows.

The organisations pulling ahead are no longer distinguished by how much they spend on AI, but by how effectively they operationalise it.

In most organisations, AI is still helping employees work more efficiently rather than transforming how the business operates. “The UAE remains one of the world’s most ambitious AI markets. The government’s long-term strategy and regulatory leadership have given organisations a genuine head start,” said Saif Mashat, VP – Middle East & Africa at ServiceNow. “While UAE organisations have built the financial and strategic commitment to AI, the ones pulling ahead are moving from AI pilots to AI orchestration, connecting legacy systems, data, governance, and AI agents in one control tower. That's where enterprise-wide execution begins.” Beyond the shift from agentic augmentation to true business transformation, the report identifies three further foundational challenges UAE organisations must address to regain their AI maturity edge. Legacy technology

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Saif Mashat, Vice-President, Middle East and Africa, ServiceNow.

59 remains a significant constraint, with just 14% of organisations having replaced legacy systems with integrated platforms. As a result, AI is often deployed across fragmented, siloed workflows rather than a unified operational backbone. Data readiness also continues to hold organisations back. More than three-quarters (77%) of UAE executives cite inadequate data accuracy, access and management as a major barrier to AI adoption. This reinforces the importance of modernising data management and integration as organisations scale AI across the enterprise. Finally, the report shows that organisations with the highest levels of AI maturity take a broader approach to AI transformation, than simply

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investing in new technologies. They are significantly more likely to establish a shared AI strategy, modernise and integrate their data, deploy autonomous AI workflows, invest in continuous workforce upskilling, and embed trust and transparency into AI governance. As a result, these businesses achieve an average AI return on investment of 160%, rising to a projected 194% within two years. They are also 5.6 times more productive, 2.7 times more successful at scaling AI and 2.6 times more effective at managing risk. In the UAE, however, only 16% of organisations have implemented AI testing, auditing and risk management processes, highlighting a significant opportunity to strengthen the governance

foundations needed for AI at scale. “The organisations pulling ahead are no longer distinguished by how much they spend on AI, but by how effectively they operationalise it. This requires moving from point solutions to unified, orchestrated platforms,” said Mashat. “Strong governance, connected data and orchestrated workflows are what translate investment into business outcomes. Together, these give organisations the confidence to scale AI, manage risk and generate measurable returns. The UAE government has already created many of the conditions for AI leadership. The challenge for enterprises now is to bring that same discipline and consistency into their own organisations.”

SEPTEMBER 2026

INDUSTRY RADAR

ServiceNow and Aramco Digital

SERVICENOW AND ARAMCO DIGITAL ADVANCE AI-POWERED TRANSFORMATION The collaboration will establish a unified platform for governing digital workflows across Aramco affiliates, subsidiaries and joint ventures in more than 50 countries.

ServiceNow, the AI control tower for business reinvention, and Aramco Digital, the technology subsidiary of Aramco, have announced the signing of a Collaboration Agreement to enable AI-powered workflows and accelerate enterprise transformation across the Aramco ecosystem. Through this Collaboration Agreement, Aramco Digital will leverage ServiceNow as a foundational platform to standardize and govern digital workflows across a highly distributed network of affiliates, subsidiaries, and joint ventures operating in more than 50 countries. The initiative supports a more unified approach to reducing fragmentation, modernizing enterprise processes, and establishing a consistent AIenabled foundation that can scale across the ecosystem. ServiceNow runs more than 100 billion workflows annually across some of the world's largest enterprises — supporting Aramco Digital’s vision to drive efficiency, strengthen governance, and enhance consistency across the ecosystem. Four domains, one platform The Agreement focuses on addressing key operational challenges associated

SEPTEMBER 2026

with managing a large, geographically dispersed enterprise group across four interconnected domains: • AI-powered workflows: Enabling intelligent automation across enterprise systems to improve operational efficiency, reduce manual processes, and accelerate execution. • Customer experience: Enhancing service

The initiative supports a more unified approach to reducing fragmentation, modernising enterprise processes and establishing a consistent AIenabled foundation.

management and customer engagement through unified, CRMdriven solutions that establish consistent service standards across entities. • Group shared services: Standardizing core business functions to enable a unified service model, reduce duplication, and improve operational consistency across the group. • Enterprise resource planning (ERP) modernization: Modernizing and optimizing legacy ERP environments to reduce technical debt, improve cost efficiency, and support scalable digital growth.

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About ServiceNow ServiceNow (NYSE: NOW) is the AI control tower for business reinvention. The ServiceNow AI Platform integrates with any cloud, any model, and any data source to orchestrate how work flows across the enterprise. By unifying legacy systems, departmental tools, cloud applications, and AI agents, ServiceNow provides a single pane of glass that connects intelligence to execution across every corner of business. With more than 100 billion workflows running on the platform each year, ServiceNow helps organizations turn fragmented operations into coordinated, autonomous workflows that deliver measurable results. Learn how ServiceNow puts AI to work for people at www.servicenow. com.

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© 2026 ServiceNow, Inc. All rights reserved. ServiceNow, the ServiceNow logo, Now, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/ or other countries. Other company names, product names, and logos may be trademarks of the respective companies with which they are associated. About Aramco Digital: Aramco Digital is a Saudi-based Industrial AI company focused on accelerating industrial digital transformation through advanced connectivity, digital platforms, cybersecurity, and AI-powered solutions. The company provides critical industries with secure, reliable, and scalable digital capabilities that enhance

operational efficiency, resilience, and long-term value creation. Through its integrated portfolio spanning Digital Connectivity, Digital Industrial Solutions, Digital Platforms, and Digital Business Services, Aramco Digital enables organizations to accelerate their transformation journeys and unlock the full potential of Industrial AI. Headquartered in Saudi Arabia, Aramco Digital supports the Kingdom’s digital economy ambitions and contributes to Saudi Vision 2030 by developing future-ready digital ecosystems, building national capabilities, and advancing the adoption of transformative technologies across industries. For more information, visit www.aramcodigital.com.

SEPTEMBER 2026

INDUSTRY RADAR

ASUS

ASUS LAUNCHES AI-POWERED EXPERTBOOK B5 FLIP G2 IN GCC The convertible laptop combines four usage modes with a built-in neural processing unit, touchscreen options and enterprise-grade security.

ASUS has announced the ExpertBook B5 Flip G2 in the GCC, offering students a versatile laptop for research, study and entertainment. With a 360-degree flippable design, the laptop enables students to use the device in laptop, tablet, tent and display modes. Powered by up to the latest Intel Core 7 Series 3 processor with a built-in 17 TOPS NPU and Intel Graphics, the laptop offers AI-powered productivity that can adapt to any scenario. “Students today need a high-performing device for their studies, and the ASUS ExpertBook B5 Flip G2 strikes the right balance of performance, portability and flexibility,” said Tolga Özdil, Regional Commercial Director, META at ASUS. “We are seeing AI being a core part of school curricula in the Middle East, and ASUS wants to ensure they have the right technology to support this.” The ExpertBook B5 Flip G2 weighs just 1.34kg and measures 14.9mm, ensuring portability without compromise. It comes with an optional garaged stylus for sketching diagrams or scribbling notes. Externally, it has a premium aluminum chassis with an elegant Gentle Gray finish. There is a 14-inch NanoEdge display with an 84% screen-to-body ratio and a 16:10 panel delivering

SEPTEMBER 2026

Tolga Özdil, Regional Commercial Director, META, ASUS.

400 nits of brightness. The TÜV Rheinland-certified eye-care technology helps with comfortable extended viewing. There is an optional touchscreen that provides additional flexibility for interactive work and study. Connectivity-wise, the laptop comes with dual Thunderbolt 4 USB-C ports, HDMI 2.1, two USB-A ports and a combo headphone and microphone jack.

The laptop meets MILSTD 810H US military-grade durability standards and includes a spill-resistant keyboard, reinforced hinges, and strengthened I/O ports to handle daily usage. It also comes with enterprise-grade security that protects files. There is a fingerprint sensor embedded into the power button for easy logins and a physical webcam shield for privacy. ASUS also engineered the laptop with sustainability in mind, using recycled materials and is built for long-term reliability. With the ExpertBook B5 Flip G2, students can count on their semester running on greener, more responsible technology.

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BMC Helix

BMC HELIX NAMED LEADER IN GARTNER ITSM ASSESSMENT The recognition follows the company’s positioning as a Visionary in the 2026 Gartner Magic Quadrant for Observability Platforms. BMC Helix, a global leader in software solutions that help the world’s most forwardthinking organizations reset the economics of IT, has been named a Leader in the 2026 Gartner Magic Quadrant for IT Service Management Platforms [1] for the 10th time. As a creator and accelerator of the ServiceOps category, BMC Helix is advancing an operating model that connects service management and operations through

Kiran Diwakar, Vice-President of Product Management, BMC Helix.

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shared context, coordinated workflows, AI-driven intelligence, and governed execution. This helps teams move from fragmented signals and serial handoffs to a coordinated response centred on the service and its business impact. BMC Helix was also positioned as a Visionary in the recently published 2026 Gartner Magic Quadrant for Observability Platforms, making it the only vendor

recognized in both the 2026 Gartner Magic Quadrants for IT Service Management Platforms and Observability Platforms. In the companion research, Gartner Critical Capabilities for IT Service Management Platforms, the company also received recognition across the three Critical Capabilities use cases for Advanced ITSM, Intermediate ITSM, and Service Desk Operations. "I am proud to see how BMC Helix has placed in the 2026 Magic Quadrants for both IT Service Management Platforms and Observability Platforms,” said Kiran Diwakar, Vice President of Product Management at BMC Helix. “Together, in our view, these results reflect the strength of our platform strategy and our ability to connect service management, operations, observability, automation, and AI-driven execution. We feel our leadership in ITSM and Visionary recognition in Observability come together to power our ServiceOps strategy - helping customers move from signals and service context to coordinated workflows and governed action. We believe this is a meaningful step forward for our teams, customers, and partners.”

SEPTEMBER 2026

APPOINTMENT

Epicor

EPICOR NAMES VAIBHAV VOHRA AS NEXT CEO

The planned leadership transition will see Vohra succeed Steve Murphy on 1 October 2026, building on Epicor’s cloud, AI and industry-focused software strategy.

Epicor, a global leader in industry-specific enterprise software, has announced that Vaibhav Vohra will become Chief Executive Officer effective October 1, 2026. Vaibhav succeeds Steve Murphy, who will step down as CEO at the close of Epicor's fiscal year, September 30, 2026, and will continue to serve on the company’s Board of Directors. The transition is the outcome of a planned succession process led by Epicor's Board of Directors, beginning with Vaibhav’s appointment to President in October 2024, and reflects the company's confidence in its strategy and trajectory. Steve and Vaibhav will work closely together to ensure an orderly transition and business continuity for Epicor's customers, employees and partners. “Vaibhav is a proven leader with deep experience in enterprise software, and I am confident he is the right person to lead Epicor into its next chapter,” said Jeff Hawn, Chair of Epicor's Board of Directors. “On behalf of the Board, I want to thank Steve for his outstanding leadership at Epicor and the strong foundation he leaves in place.” Vaibhav joined Epicor in 2021 as Chief Product Officer

SEPTEMBER 2026

Vaibhav Vohra, incoming Chief Executive Officer, Epicor. and has since taken on roles of increasing responsibility, most recently as President and Chief Product and Technology Officer. In that time, he has led Epicor's product strategy, development, management and design, and has been central to advancing the company's cloud, AI and data supply chain vision. Before Epicor, he built and scaled technology businesses, including as a product leader at Gecko Robotics, and held executive product roles at SAP. “I am honored to lead Epicor as we enter a new era of transformation across

enterprise software. Over the past five years, I’ve seen firsthand the people, customers, and partners that make this company special. Our focus remains on helping our customers grow and succeed in an increasingly dynamic world,” said Vaibhav Vohra. “I want to thank Steve for his exceptional leadership and for all he has done to position Epicor for continued success.” Under Steve’s guidance, Epicor strengthened its position as a SaaS leader in industry-focused ERP, accelerated its transition to a cloud-first business, expanded its capabilities through sustained innovation and strategic acquisitions, and surpassed $1 billion in annual recurring revenue. “It has been a privilege to serve Epicor and the talented team behind it,” said Steve Murphy. “We've sharpened Epicor's focus on the customers and industries we serve, and I'm proud of what this team has accomplished. With the company performing well and a clear strategy in place, this is the right time for a change. Vaibhav has been instrumental in shaping our product and technology direction, and he is the right leader for what comes next.”

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APPOINTMENT

AVEVA

AVEVA APPOINTS BROCK BALLARD AS CHIEF REVENUE OFFICER

The former Bentley Systems executive will join AVEVA on 1 October 2026, succeeding Sue Quense as she moves into an advisory role.

AVEVA, a global leader in industrial software, today announced the appointment of Brock Ballard as Chief Revenue Officer effective 1 October 2026. Brock joins the team from Bentley Systems following an extensive recruitment process led by AVEVA; he will succeed Sue Quense in the role as she steps into an advisory capacity. Brock brings over 20 years of senior leadership in technology sales, having joined Bentley in 2020 as Vice President and Regional Executive, Americas, being named Chief Revenue Officer in 2023, leading all of Bentley’s accounts globally. Previously, Brock held leadership roles DELMIA Sales, Dassault Systems, at Autodesk Inc. He holds a Bachelor of Arts degree in communication and information sciences from the University of Alabama. “I am delighted to welcome Brock to the Executive Leadership team at AVEVA, where we will benefit from his expertise, experience and commitment to building successful, high-growth tech companies. Brock’s engaging approach sets him apart in our sector, and I look forward to working with him to drive the next phase of AVEVA’s

SEPTEMBER 2026

outstanding software portfolio, technical leadership and ambitious growth trajectory lead the market. This, coupled with the team’s shared commitment to driving responsible use of resources, has never been more important to enabling the transformation of businesses across the world. I cannot wait to get started,” says Brock Ballard, AVEVA

Brock Ballard, incoming Chief Revenue Officer, AVEVA. growth. I also want to extend my personal thanks to Sue Quense for her outstanding leadership and good counsel over the past five years. She will continue to work with AVEVA leadership in an advisory capacity, even as she steps back from the day-today running of the business,” said Caspar Herzberg, CEO, AVEVA. “Having long admired AVEVA’s vision to drive innovation in the industries that deliver the essentials of life, I am delighted to be joining the executive leadership team. AVEVA’s

Quense to remain an Advisor to the AVEVA Executive Leadership Team Sue Quense will not fully step down from AVEVA, however she will step back from her full-time executive commitments into an advisory capacity, something that she has been planning for some time. Sue will work closely with Brock during the transition and beyond. She added, “In Brock, we have found someone who embodies the AVEVA values and shares our focus on driving innovation for our customers and enabling industries to thrive in our rapidly-evolving world. I look forward to working closely with Brock during this transition and in continuing to contribute to AVEVA’s success in my new role.”

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