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ISSUE 405 I OCTOBER 2026 TAHAWULTECH.COM

DATA POWERS AI SUCCESS

Omar Akar of Everpure reveals how unified, trusted, and resilient data infrastructure can turn enterprise AI investment into measurable business value.

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EDITORIAL

Turning AI ambition into enterprise value Enterprise AI has reached a point where ambition must translate into operational

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progress. Across the region, technology leaders face a demanding brief: build infrastructure that supports intelligence, protect the information that powers it and demonstrate value that extends beyond a successful pilot. October’s CNME explores the decisions behind that transition. Our cover interview with Omar Akar of Everpure places trusted data at the centre of enterprise AI Talk to us: Sandhya D'Mello Editor, CNME E-mail: sandhya.dmello@ cpimediagroup.com

strategy. Unified information, resilient infrastructure and effective governance provide the foundations for organisations seeking to turn investment into measurable outcomes. Compute capacity matters, but its usefulness depends on the quality and availability of the data feeding it. Accountability runs through this issue. Our contributors examine the requirements for calculating AI returns, integrating agents into established workflows and governing the data those systems access. Banking offers a reminder that operational metrics tell only part of the story. Resolving a customer’s problem and earning their confidence remain better measures of service than simply closing a conversation.

Enterprise AI earns its value Our online platforms through trusted data, clear accountability tahawultech.com and measurable improvements in how Our social media organisations work.” facebook.com/tahawultech

Sovereignty adds another dimension to enterprise planning. Leaders need visibility into where information resides, who can access it and how systems remain available under changing operating conditions. Our coverage of controlled AI development environments and hybrid infrastructure reflects the importance of matching deployment choices to business requirements. People remain equally central. Conversations with Logitech’s leadership at RISE in Cairo examine how intuitive collaboration tools, regional insight and partner expertise can improve workplace experiences. Technology earns its place when employees can use it confidently and organisations can assess its contribution. Workforce development deserves the same attention as infrastructure investment. Beyond the workplace, this edition considers the connections shaping the region’s digital economy. GSMA discusses the relationship between advanced connectivity, skills and productivity, while Amadeus explores more integrated travel

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experiences. Ecocoast’s environmental monitoring perspective demonstrates how timely data can support decisions across ports, utilities and coastal developments. Industrial AI coverage also examines the importance of preserving expertise and

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applying operational intelligence. Together, these perspectives point towards a leadership priority: connect technology decisions with the outcomes that matter. Stronger foundations, clear ownership and practical measurement give innovation a durable purpose. For enterprise leaders, the opportunity lies in choosing priorities carefully,

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preparing teams thoroughly and reviewing progress honestly. Every investment should have a defined role in improving how the organisation works. October’s issue invites readers to examine those choices, challenge familiar assumptions and build the capabilities needed to deliver lasting value with confidence and discipline.

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CONTENTS

08 COVER STORY 22 Preparing enterprise strategy for AI era 24 PNY advances AI factories for enterprise deployment 38 Building foundations of intelligent economy

Logitech

Tidiane Lo

PNY Technologies Europe

Logitech

connects global workplace strategy 14 Logitech with regional partner opportunities strengthens partner ecosystem to 17 Logitech accelerate growth across emerging markets puts users at centre of smarter 20 Logitech workplace collaboration

Logitech

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

GSMA

Published by

PRODUCTION AND DESIGN Designer Prajith Payyapilly prajith.payyapilly@cpimediagroup.com

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

Apple looks to add to its smart-home device lineup

From digital classrooms to AI tutors: Gen Z expects the next transformation of education Ahead of World Teachers’ Day, Kaspersky reveals that Gen Z is particularly aware of emerging AI trends in education and sees the sector as a promising area for AI technologies. According to new research by Kaspersky’s internal market research centre, Gen Z shows greater awareness of technologies such as AI tutors and VR classrooms than other generations surveyed. Among Gen Z respondents, 18%

This interest comes as technology continues to become more integrated

identify personalised AI tutors as one of

into education. More than two-thirds

Apple is reportedly planning to

the most promising technologies for the

of Gen Z respondents (68%) say they

further its smart-home device

future — the highest proportion among

have seen technology become more

product line starting with the

all generations surveyed (16% overall),

widely used in their own educational

launch of a long-delayed hub on

reflecting Gen Z’s strong interest in

experience over the past five years,

the 13th October 2026.

AI-powered learning experiences and

compared with 55% of respondents

Bloomberg reported the smart-

putting these technologies on par with

overall. This broader shift in digital

home hub, code-named J490, will

smart public transport and conscious

learning creates a foundation for the

feature a roughly 6-inch square

consumption. Similarly, 14% see VR/

next stage of transformation, where AI

display mounted on a perforated

AR classrooms with AI assistants as a

could play a greater role in providing

speaker base, with the countertop

promising direction, again placing Gen Z

personalised support and interactive

version featuring an arm that

ahead of other generations (12% overall).

learning experiences.

allows users to tilt the display. A dedicated wall-mounted variant is code-named J491. The grey aluminium device runs on USB-C power without internal batteries or

CyberKnight strengthens zero trust ecosystem at GISEC Global 2026 with dual industry awards and more

physical buttons. The hub will use built-in microphones and a front-facing FaceTime camera to identify household members by voice or appearance, then display their calendars, messages, notes and contacts. A virtual white ring light will illuminate users approaching in low light, while an iPhone can

CyberKnight Technologies concluded

provide secondary authentication

a landmark three days at GISEC Global

more cybersecurity products into the

“Our role is not simply to put

if facial recognition fails. A

2026 at Expo City Dubai.

market. Security teams already have

The company brought 16 technology

enough technology to manage. The real

vendors together under one integrated

challenge is making those technologies

Zero Trust strategy, signed strategic

work together so customers can move

to place multiple displays around

MOUs with Harness and Asimily,

from identifying a risk to governing it,

the home for intercom calls, music

launched the region's first Women

containing it, and recovering from it.

streaming and control of HomeKit

in Cybersecurity series, received an

That is where our Zero Trust approach

accessories. In the kitchen, the hub

official award from Dr. Mohamed Al

helps customers operationalise

could also provide voice-guided

Kuwaiti, Head of Cybersecurity for the

resilience, not just buy more tools”,

recipes.

UAE Government, and celebrated its

Wael Jaber, Chief Strategy Officer,

ecosystem with an exclusive Gala Dinner.

CyberKnight Technologies.

visitor mode will hide personal information from guests. The tech giant expects customers

OCTOBER 2026

www.tahawultech.com

Proofpoint appoints Joyce Kim as Chief Marketing Officer Proofpoint, Inc., a leading cybersecurity

"AI is rewriting the rules of

and compliance company, recently

business, and security is the

announced the appointment of Joyce

foundation that makes this

Kim as Chief Marketing Officer (CMO),

transformation possible”, said Joyce

effective immediately.

Kim. "As CMO, my focus is to amplify

In her role, Ms. Kim will shape

Proofpoint’s leadership in data

Proofpoint’s global marketing and

security and share our vision for how

communications strategy, amplifying

organisations can innovate safely in

the company’s brand, go-to-market

the age of AI. Together, we’ll show the

execution, and demand acceleration initiatives worldwide, reporting directly to Proofpoint CEO Sumit Dhawan.

Joyce Kim as Chief Marketing Officer (CMO).

world that trust—and the protection of people and data—is what fuels meaningful progress”.

from product resale into recurring, OPSWAT and Redington sign distribution agreement path higher-value managed services”. Sayantan Dev, Chief Executive Officer, Software Solutions Group, Redington, said, “Critical infrastructure is becoming increasingly connected, making its protection more complex and more critical. As AI accelerates both innovation and the sophistication of emerging threats, partners need the right technologies, expertise and support to stay ahead. This is where OPSWAT, a global leader in critical

“Critical infrastructure customers

technology ecosystem orchestration

infrastructure protection (CIP)

cannot wait for technology to clear

becomes important – bringing together

cybersecurity solutions, and Redington,

borders, financing gaps or skills

the right security capabilities, partner

a leading technology aggregator,

shortages. Redington brings resilience

expertise and market context. Through

recently announced a distribution

on all three fronts. Its financial stability

our partnership with OPSWAT, we aim

partnership covering the Gulf

gives partners the confidence to pursue

to enable partners to strengthen cyber

Cooperation Council (GCC), Levant,

complex, multi-stage projects; its

resilience, address emerging AI-driven

Türkiye, Africa and the Commonwealth

regional stock and logistics help keep

risks and build relevant solutions that

of Independent States (CIS).

hardware-led deployments moving when

help customers protect the critical

Hussam Sidani, Regional Vice

supply chains are under pressure; and

infrastructure their businesses and

President – META, OPSWAT, said,

programs like DigiGlass give partners a

economies depend on”.

Cisco expands secure AI factory with NVIDIA for the rack-scale era Cisco is expanding the Secure AI

history", said Jeetu Patel, President

generating infrastructure, where

Factory with NVIDIA through a

and Chief Product Officer, Cisco.

compute produces intelligence,

partnership with Supermicro, bringing

"Every organisation is racing to

and intelligence drives revenue”,

its leadership in high-density, liquid

scale AI — but speed only counts

said Justin Boitano, vice president,

and air-cooled compute to Cisco’s

if it comes with control of data,

Enterprise AI, NVIDIA. “By expanding

industry-leading full-stack, secure

managed token costs, and real ROI. It

the Cisco Secure AI Factory

AI infrastructure architecture for

starts with the right infrastructure:

with NVIDIA, Cisco is providing

enterprises, neoclouds and sovereign

compute and networking, delivered

enterprises and neoclouds full-stack

clouds.

as an integrated solution that's easy

infrastructure that can get into

to deploy and secure from day one".

production faster and generate more

"We are at the beginning of one of the largest datacenter buildouts in

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“AI factories are revenue-

value from every watt”.

OCTOBER MAY 2026

COVER STORY

EVERPURE

BUILDING TRUSTED DATA FOUNDATIONS FOR ENTERPRISE AI Omar Akar, Area Vice President at Everpure, explains why unified data, resilient infrastructure and strong governance will determine whether organisations can move AI from experimentation to measurable business value.

OCTOBER 2026

www.tahawultech.com

Zebra Technologies

www.tahawultech.com

OCTOBER 2026

COVER STORY

Enterprise AI is reshaping infrastructure priorities across the Middle East, Central and Eastern Europe, Turkey, CIS and Africa. Organisations are looking beyond compute capacity to address the quality, availability, governance and protection of the data powering increasingly complex AI workloads. For channel partners, this transition creates opportunities to help customers modernise legacy environments, unify fragmented data and improve GPU utilisation while meeting sovereignty, privacy and regulatory requirements. Cyber resilience has also become central to the conversation, particularly as agentic AI systems begin using enterprise data to make decisions and take action. In this exclusive CNME cover interview, Omar Akar, Area Vice President, Everpure, discusses the foundations required to move AI from experimentation into production. Akar also explains why unified data strategies, outcome-led infrastructure and trusted partner expertise will determine whether organisations can translate AI investments into measurable business value.

capacity and anticipated growth. Enterprise AI has broadened that discussion because data now feeds expensive compute resources, making data readiness critical to both performance and the economics of AI. How quickly and consistently an organisation can discover, prepare and deliver data directly affects the value of its investment. An idle GPU

and applications, yet still struggle to integrate AI into everyday operations because information remains fragmented, difficult to prepare or poorly governed. A successful experiment may use a carefully selected dataset in a controlled environment. Expanding that application across the business requires reliable access to information from

Organisations need data infrastructure that can respond to changing requirements and deliver predictable outcomes, rather than forcing them to forecast every future capacity need." represents a costly resource waiting for information. Even substantial compute capacity can deliver limited value if the supporting data infrastructure cannot keep pace. Organisations therefore need a data strategy that connects infrastructure decisions with business outcomes. Flexibility also matters because AI workloads can evolve in ways that are difficult to forecast. Infrastructure must respond

multiple sources, clear ownership and confidence in how the data can be used. Preparation and governance become more demanding as the scope grows. Success depends on unifying data, establishing trust and making information available to applications consistently. Organisations also need to connect AI initiatives with specific operational priorities. Strong data foundations help

Success depends on unifying data, establishing trust in it and making it available to applications at the right time." to changing requirements while delivering predictable service levels.

promising experiments develop into applications that deliver measurable business value.

How is enterprise AI reshaping data infrastructure priorities across your region?

What prevents organisations from turning AI experimentation into measurable business value at scale?

How can enterprises modernise legacy data environments for AI workloads?

Infrastructure decisions traditionally centred on application performance,

The obstacle is often the data strategy. Organisations can invest in GPUs, models

Interview excerpts

OCTOBER 2026

Modernisation should create a foundation for continuous innovation. Organisations need infrastructure that can evolve with business

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requirements while reducing the disruption associated with periodic technology refreshes and data migrations. Adaptability is particularly important for AI because future performance and capacity needs can be difficult to predict. Infrastructure governed by agreed service levels can help customers manage that uncertainty and focus on the outcomes their applications require. Unification is another priority. Fragmented environments make information harder to discover, prepare and deliver, limiting the data available to AI applications. Enterprises should consider modernisation across the full data lifecycle, including protection, governance and preparation. A simpler operating model can also reduce the management burden on technology teams.

What role does a unified data platform play in GPU utilisation, application performance and AI economics? A unified data platform helps connect the stages that determine whether information is ready for AI. Discovering and consolidating data, protecting it, establishing trust and preparing it for applications all affect how effectively compute resources are used. Delays anywhere in that process can leave GPUs waiting for information and slow application performance. Consistent data delivery helps organisations make better use of expensive

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infrastructure and supports more predictable operations. Governance matters alongside speed. Organisations need to understand what information is available, whether its use is permitted and what preparation is required before it enters an AI application. Our broader direction at Everpure is to address those requirements across the data lifecycle. Storage provides an

Enterprises should also look for infrastructure that delivers agreed service levels and a data platform that can protect, govern and prepare information for AI." essential foundation, while the wider platform must help customers turn data into usable, trusted information.

How can organisations accelerate AI adoption while meeting data sovereignty, privacy and regulatory requirements? Data sovereignty, privacy and regulatory compliance need to form part of the AI strategy from the beginning. Organisations must understand where information resides, how it is governed and whether it can safely enter an AI pipeline. Clear visibility provides the context needed to make informed decisions. Customers need to identify sensitive information, understand applicable restrictions and maintain control over its use across different environments. Confidence in those controls

becomes increasingly important when moving from experimentation into production. Addressing governance early can reduce uncertainty and help organisations progress with greater confidence. A trusted data foundation supports AI adoption by making compliance and control part of how applications are developed and operated.

Why should cyber resilience and data protection form part of every enterprise AI strategy? AI increases the importance of enterprise data and makes its integrity more consequential. Compromised or altered information can affect an application’s output, leading to unreliable recommendations or inappropriate actions. The concern grows as organisations introduce agents capable of acting on information. Confidence in the underlying data becomes essential when systems move beyond generating responses to participating in business processes. Protection must therefore address both integrity and recovery. Organisations need to safeguard information and retain the ability to restore trusted data following an incident. Rapid recovery helps maintain critical operations and limits disruption to applications that depend on that information. Everpure has integrated protection and recovery capabilities into its data platform and servicelevel commitments. Our aim

OCTOBER 2026

COVER STORY

OCTOBER 2026

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is to help customers build resilience into the foundations supporting their AI initiatives.

Which industries are leading AI adoption across the region, and what can others learn from them? Governments are playing a leading role, particularly in the Gulf, where AI forms part of broader national transformation strategies. We also see growing adoption across telecommunications, healthcare, banking and other financial services. A key lesson is to approach AI as an organisation-wide transformation. Successful adoption depends on how data, processes, technology and cyber resilience work together. Introducing an application is one step; integrating it into operations requires a wider foundation. An organisation’s own information, together with the context surrounding it, can become a significant competitive advantage. Customers need to understand how that data can support their priorities and where AI can deliver practical value. Clear objectives and trusted information provide a stronger basis for scaling adoption.

What will define successful AI infrastructure strategies over the next three years? Successful strategies will focus on integrating AI into operations and measuring its contribution. Organisations will need to assess whether investments improve processes, deliver a return and create tangible business

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Executive Profile Omar Akar, Area Vice President, Everpure – Middle East, Central and Eastern Europe, Turkey, CIS, and Africa. Omar has over 21 years of experience in the IT industry across Europe,

Middle East, and Africa. He currently leads Everpure’s operations across the Middle East, Central and Eastern Europe, Turkey, the CIS region, and Africa, partnering with organisations to accelerate their digital transformation, drive innovation, and unlock greater value from their data. Omar helps customers advance their multi-cloud journeys, modernise their applications, and build a strong, futureready foundation for AI through next-generation storage and data management solutions. Prior to joining Everpure, Omar spent two years at Huawei, managing the Middle East business for Cloud, AI, and Infrastructure solutions. Before that, he dedicated 15 years to Dell Technologies (previously EMC), assuming various leadership roles across Turkey, the Middle East, and Africa. Throughout his career, Omar has been passionate about supporting organisations in their digital transformation journeys, driving innovation, and enabling customers to achieve their strategic goals through technology.

outcomes. A unified data strategy will sit at the centre of that work. Access to compute, models and applications must be supported by the ability to discover, govern, prepare and deliver information effectively. Infrastructure will also need to adapt as workloads and business requirements change. Simplicity, resilience and predictable service levels will become increasingly valuable. Customers need an operating model that allows technology teams to support innovation without adding unnecessary management complexity. The strongest strategies will connect those infrastructure capabilities with clearly defined business priorities.

Our broader direction at Everpure is to address those needs across the data lifecycle, rather than focus solely on storage."

What does it mean to you personally to contribute to the region’s AI ambitions? I feel proud to contribute at a time when the UAE, Saudi Arabia and the wider Gulf are pursuing ambitious plans for AI. Supporting that transformation gives our work a purpose that extends beyond individual technology deployments. Our goal is to grow with the region and help organisations build the foundations required to achieve their ambitions. Data infrastructure plays an important role because it supports how information is prepared, protected and used to deliver business value. I also feel a personal responsibility to contribute. Helping customers strengthen their capabilities and make progress with AI connects our work to broader national priorities. Being part of that journey is both meaningful and motivating.

OCTOBER 2026

INTERVIEW

Logitech

LOGITECH CONNECTS GLOBAL WORKPLACE STRATEGY WITH REGIONAL PARTNER OPPORTUNITIES Jedd Williams outlines the role of local customer insight, consistent product availability and partner enablement in expanding Logitech for Business’s workplace portfolio across the Middle East and Africa.

Workplace technology strategies must accommodate different working cultures, employee preferences and deployment requirements across markets. Logitech for Business is addressing those needs through a portfolio spanning personal workspace devices and video collaboration, supported by global account coordination and regional partner expertise. Speaking to CNME at Logitech’s RISE event in Cairo, Jedd Williams, Chief Commercial Officer, Logitech for Business, shared insights into the company’s global enterprise strategy and its relevance to the Middle East and Africa. With the event bringing together global leadership, regional partners and technology specialists, Williams highlighted the importance of local customer feedback, partner collaboration and workplace solutions that address the needs of diverse markets.

OCTOBER 2026

Interview excerpts How does Logitech’s global enterprise strategy translate into priorities for the Middle East and Africa? Our strategy focuses on both personal workspaces and team workspaces. Logitech for Business has evolved from a business centred on video collaboration into a broader portfolio that also includes mice, webcams, keyboards and headsets. Globally, personal workspace solutions account for approximately 60% of our revenue, with video collaboration contributing around 40%. Both areas are important to helping customers address their business challenges. Pricing is another priority. Competitors offer strong products, but some come at a premium. We believe our portfolio offers competitive performance at price points that help customers deploy workplace technology at

scale. Bringing together quality, affordability and a broad portfolio supports our approach across markets, including the Middle East and Africa.

How do global and regional teams align to deliver consistent workplace technology and customer experiences for multinational organisations? We re-established our global accounts team to help larger customers purchase and deploy technology consistently across their international operations. A multinational organisation may decide to standardise on a particular product, only to discover that it is unavailable in part of the world. Avoiding that frustration is a key priority. Our focus is on making products globally available and providing a consistent experience wherever customers deploy them. The global accounts

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Jedd Williams, Chief Commercial Officer, Logitech for Business.

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OCTOBER 2026

INTERVIEW

team helps coordinate that approach across markets, supporting customers that want a common workplace technology standard.

How does regional customer feedback influence Logitech’s global product and business decisions?

Regional input is very important to us. Events such as RISE provide an opportunity to understand local market dynamics through direct conversations with partners and customers. Global integrators and resellers give us a valuable overview, while local partners and customers help us understand specific requirements that need action. Markets differ, so our strategy must evolve to reflect those differences. A visit to India, for example, reinforces how customer needs can vary from one region to another. Our global team can develop an overarching strategy, but regional teams bring it to life. Customer relationships, local knowledge and execution on the ground are where that strategy delivers results.

How do you apply global best practices while adapting to local workplace needs? Listening to local partners and customers helps us understand how to support their requirements. A keyboard or video system may be the same product across markets, but the way people use it can differ

OCTOBER 2026

according to workplace culture and working patterns. Partner enablement therefore needs to include use cases that reflect local conditions. I refer to this approach as “story selling”: focusing on the customer problem we are trying to solve, rather than leading with camera resolution, field of view or individual AI features. Hybrid working illustrates why local context matters. During a recent visit to Brazil, I heard how heavy traffic influences employees’ decisions to attend the office only a few days a week. Understanding factors such as commuting, office attendance and working from home helps us make our approach relevant to each market.

How do diverse customer behaviours influence Logitech’s business strategy and product development? I am a strong believer in diverse teams. Gender, ethnic and cultural diversity bring different perspectives, helping teams understand a wider range of customer needs. Listening to customers is essential because today’s workforce includes people with different preferences, habits and expectations. Generational differences, for example, can influence the headset styles people feel comfortable wearing. Younger workers who have grown up with gaming may have different preferences from older colleagues. Our consumer heritage

gives us useful insight into those behaviours. Consumer approaches do not automatically apply to Logitech for Business, but relevant insights can inform product development. The objective is to build products that fit the people using them and the environments in which they work.

How does RISE connect regional partners with Logitech’s global leadership and strategic direction? RISE brings regional partners together with members of our global team, creating an opportunity to listen, gather feedback and align our priorities. During my session, I asked how many partners were selling personal workspace solutions, including mouse, webcams and keyboards. Only a few hands went up in a room of around 150 partners. Asking that question helps us understand where partners focus today and where there may be opportunities to expand their businesses. We want to help partners develop their thinking and their businesses, while allowing their feedback to influence our own decisions. Global strategy should inform regional strategy, and regional teams must shape its execution around their customers and market conditions. Success means partners leave with greater confidence in Logitech, a clearer understanding of the opportunity and an easier path to doing business with us.

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Logitech

LOGITECH STRENGTHENS PARTNER ECOSYSTEM TO ACCELERATE GROWTH ACROSS EMERGING MARKETS Angelos Stefanidis discusses partner specialisation, RISE’s regional expansion and the demand for secure, AI-enabled collaboration as organisations rethink hybrid workplaces.

Logitech is deepening investment in its partner ecosystem across emerging markets, with a focus on helping channel businesses address opportunities in enterprise, education and healthcare. Partner enablement, specialisation and locally aligned marketing investment form a central part of that approach. Speaking to CNME during Logitech for Business’s RISE partner gathering in Cairo, Angelos Stefanidis, Head of Business – IMEA (India, MEA, Central Asia), Logitech, discusses the company’s channel priorities and the technology trends shaping workplace investment. Stefanidis also explains how RISE is evolving from local events into a larger regional gathering, bringing partners together to experience technology and exchange market insights.

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Interview excerpts How is Logitech’s channel strategy evolving to strengthen partner ecosystems across emerging markets? We want to bring technology to the markets in which we operate more quickly. Our ecosystem spans unified communications and collaboration, audiovisual solutions and personal workspaces. We invest directly with partners in local markets, including those where we do not have a direct presence. Enterprise, education and healthcare are important areas of focus. Many of our partners share those priorities, so we align our product offering and marketing investments with their strategies and the needs of each local market.

How does RISE support Logitech for Business’s growth ambitions and create opportunities for partners? RISE brings partners together in one location and gives them hands-on access to our technology, from headsets and webcams to AI-enabled video and audio collaboration systems. Some partners have not previously had the opportunity to see or experience these solutions directly. We use the event to enable and motivate partners, explain incentives and simplify the programme structure so doing business with us becomes easier. We align our resources with shared priorities and provide opportunities for specialisation, helping certified and authorised Logitech partners differentiate themselves in their markets.

OCTOBER 2026

INTERVIEW

Angelos Stefanidis, Head of Business – IMEA (India, MEA, Central Asia), Logitech.

OCTOBER 2026

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Which trends are shaping the future workplace across emerging markets? Hybrid work, AI, sustainability and security are the main trends. Following the pandemic, organisations moved from fully remote working towards a return to the office. Many markets are now settling into hybrid arrangements, although the number of days employees spend in the office varies. AI is embedded in our approach to hardware, software and the user interface. The aim is to make video, audio and personal workspace technology easier to use. Sustainability also influences how we design products, source materials and approach packaging. Product longevity matters because customers need to consider the full lifecycle and total cost of ownership of the technology they buy. Security remains a significant priority across enterprise, midmarket and smaller business customers. We see those same trends in markets such as the UAE, Saudi Arabia and South Africa, where customers are adopting and deploying workplace technology.

How is AI changing workplace collaboration, productivity and employee experience? Customers want technology that is easy to use, simple to set up and secure. Interoperability is also important. We work with platforms such as Microsoft Teams, Google Meet and

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Zoom so customers can use Logitech products across their collaboration environments. Meeting equity is another priority. Tabletop cameras can help remote participants see people in the meeting room more clearly, while Logitech Scribe supports sharing whiteboard content with people joining remotely. Awareness of these capabilities still varies, which makes partner education important. Partners need to experience the technology themselves before demonstrating its value to customers. Meeting room systems with integrated sensors can also provide information on temperature, CO2 levels and occupancy. Those capabilities help organisations understand their workplace environments and support decisions about how meeting spaces are used.

for our partner channel events three years ago, following the rollout of the Logitech partner programme in emerging markets. Initially, we held local events in different markets to explain our strategy and the programme. This year, we have scaled that approach into a larger regional gathering. Partners across different countries often share similar strategies, challenges and concerns. Bringing them together gives them an opportunity to network, exchange experiences and hear feedback from other markets. A regional event also allows us to bring technology and global leadership together in one place. We plan to hold the gathering in a different location next year, with partner feedback helping shape how RISE develops.

How are customer priorities shifting as hybrid work matures?

Could future editions bring India into the regional RISE gathering?

Security remains a top priority, alongside ease of deployment. Customers also want access to data that helps them make informed decisions about future investment. Sensors, management platforms and software can provide information for IT, HR and procurement teams. Organisations are rethinking the workplace, and data is becoming an important foundation for decisions about future office design.

We are considering integrating India next year. India is a major market for us, and we held a dedicated event there in June under the name Arohan, which reflects a similar idea of rising or elevating. We retain the RISE theme in the Middle East and Africa because partners identify with it. Participation is linked to being part of our ecosystem and delivering results through the partner programme. Our aim is to give partners a reason to come, learn about technology and engage with our global leadership on the region’s role in Logitech’s growth plans.

How has RISE evolved since its launch? We introduced the RISE theme

OCTOBER 2026

SPECIAL INTERVIEW

Logitech

LOGITECH PUTS USERS AT CENTRE OF SMARTER WORKPLACE COLLABORATION Murad Ali discusses how AI-enabled devices, intuitive design and workplace analytics can simplify meetings, improve employee experience and help businesses assess technology investments.

Rising expectations for seamless collaboration are prompting organisations to rethink workplace technology, from personal devices to shared meeting spaces. Ease of use, security and consistent experiences across office and remote settings are becoming central to adoption, while workplace analytics offer greater visibility into usage and investment value. Speaking to CNME at Logitech’s RISE event in Cairo, Murad Ali, Head of Middle East & Central Asia, Logitech for Business, explains how the company combines its understanding of consumer behaviour with enterprise collaboration needs. Ali discusses the role of AI, integrated devices and intuitive design in reducing friction and helping employees focus on their work.

OCTOBER 2026

Interview excerpts How are AI-powered technologies helping organisations create smarter and more adaptive workplaces? AI has made users more capable and more demanding. Technology providers need to move faster to support those expectations and deliver solutions that accommodate new ways of working. Our latest products bring AI into collaboration through smarter cameras, clearer audio and richer workplace data. Beyond improving the meeting experience, insights into room conditions, lighting, occupancy and meeting duration can help organisations understand how their spaces are being used. Such information helps businesses assess their return on investment and make better decisions about workplace technology. The aim is to make collaboration smarter, easier and more accessible.

What should businesses prioritise when adopting flexible and scalable collaboration solutions? Security should be a priority, alongside choosing the right technology partner. Businesses need solutions that work effectively with their existing collaboration platforms and provide dependable support. We work closely with partners including Google, Zoom and Microsoft. Our role also involves helping customers and channel partners identify the right solutions for their requirements, drawing on our experience across personal workspaces and meeting rooms. After-sales support, product durability and environmental considerations also matter. Organisations should consider the materials used, packaging and product longevity alongside performance and ease of use.

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that complexity reduces interruptions and helps people focus on their work. Automation can also support what happens after a meeting, including capturing minutes and action points and distributing them with less manual effort. The value comes from making the entire experience easier, from joining a meeting to following up on decisions.

How can organisations deliver an equally effective collaboration experience for employees in the office and working remotely?

Murad Ali, Head of Middle East & Central Asia, Logitech for Business.

How can intuitive workplace technology improve productivity and the employee experience? People use smartphones and smart applications every day, so they expect workplace technology to be equally straightforward. Nobody wants to spend time troubleshooting equipment simply to make a call or start a meeting. A user should be able to sit down, access a touch panel and begin collaborating without needing to understand the systems or data flows behind it. Removing

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People are accustomed to accessible applications and high-quality cameras on their smartphones and personal devices. Returning to the office should provide a comparable or better experience. Our camera and audio technologies are designed to improve the meeting experience and support continuity between personal devices and office environments. Employees should be able to move between those settings without unnecessary disruption. Understanding users is central to that approach. People sit at the centre of our product design, with technology supporting the way they want to work.

How is Logitech supporting collaboration beyond traditional meeting rooms? Deeper integration is making collaboration more flexible. Users increasingly expect to start a call on one device

and continue on another seamlessly. Meeting analytics are also becoming more valuable. Organisations need to understand how their collaboration technology is being used, what happens after meetings and where further investment would be worthwhile. Our focus extends beyond video resolution and audio clarity to providing insights that businesses can use to improve their collaboration environments and assess the value of their investment.

How are rising consumer expectations shaping Logitech’s business strategy, regionally and globally? Our experience in consumer technology helps us understand the expectations people bring into the workplace. A consumer is also an employee who may be using our products at a desk or in a meeting room. People want technology that is simple, requires less effort and allows them to concentrate on their work. We have applied that understanding to our business portfolio, including integrated video bars that reduce the need for multiple separate devices. Our consumer and business portfolios complement each other. Knowledge gained from one helps inform the other, and both remain important to our strategy. We continue developing products across both areas, guided by the same goal: making technology easier for people to use.

OCTOBER 2026

INTERVIEW

Tidiane Lo

PREPARING ENTERPRISE STRATEGY FOR AI ERA Tidiane Lo explores the interconnected investments behind AI adoption and why technology leaders must balance current performance with future readiness.

AI adoption is bringing infrastructure, cloud, data, networking and cybersecurity into a shared strategic conversation. For enterprise leaders across Africa and the Middle East, the challenge extends beyond selecting technologies to preparing organisations for changes in how work gets done and decisions are made. Speaking to CNME, Tidiane Lo, Vice President, GTM, Westcon-Comstor Middle East and Africa, examines the opportunities emerging from this convergence and the importance of embedding governance, security and human judgement into AI transformation. Lo also shares the inspiration behind Preparing for the Next Opportunity, a personal account of his career journey, and considers how readiness for unexpected opportunities can inform enterprise strategy in a rapidly changing technology landscape.

Interview excerpts What inspired you to document your journey across Africa and the Middle East in Preparing for the Next Opportunity? OCTOBER 2026

Interestingly, the original idea came from a colleague. Following an announcement about the expansion of my role, she sent me a congratulatory note and suggested that my career journey could almost be a book. That stayed with me. But I didn't want to write a book about titles or promotions. I wanted to tell the story behind what people see : the preparation, the decisions, the people, the mistakes, the sacrifices and sometimes simply being ready when an unexpected opportunity appeared. The book is not a collection of lessons or best practices. It is my story. If one sentence or one experience helps someone see their own journey differently, then it has achieved one of its objectives. And if not, at least the reader will know me and the journey behind the professional profile a little better.

static. What made a business successful five years ago may not be what makes it relevant five years from now. My role increasingly requires me to balance two horizons: delivering today's performance while preparing for tomorrow's opportunities. That means staying close to vendors, partners and customers, understanding where technology is moving, and being willing to challenge our own assumptions before the market does it for us. I often say that managers focus on today's performance; leaders must also prepare tomorrow's opportunities. In technology, where change happens so quickly, that second responsibility has never been more important.

How has rapid technological change influenced your leadership approach and strategic decisionmaking?

AI is clearly at the center of the conversation, but I see the opportunity as a combination of technologies rather than AI in isolation. AI will drive significant investment in infrastructure, data, cloud, networking and,

Technology has taught me that leadership cannot be

Which emerging technologies do you believe will create the greatest opportunities across Africa and the Middle East?

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also need to create an environment where people don't automatically see AI as something that will replace them, but as something that can augment what they do. At the same time, governance, security and responsible adoption cannot be afterthoughts. The principle connects strongly with the theme of my book: you cannot predict every opportunity, but you can prepare yourself for it. The organisations investing in their people and capabilities today will be much better positioned when tomorrow's opportunities arrive.

Tidiane Lo, Vice President, GTM, Westcon-Comstor Middle East and Africa.

What do you hope technology professionals and emerging leaders will take away from your story?

critically, cybersecurity. As organisations become more digital and AIenabled, securing identities, applications, data and increasingly complex environments becomes even more important. Across Africa and the Middle East, there is also an opportunity to move beyond legacy models. We have seen this before with mobile technology and cloud. AI can potentially accelerate that further, particularly in markets where technology can address challenges around scale, skills and access. For the channel, the opportunity will be in turning these technologies into meaningful business outcomes rather

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than simply adding another acronym to the portfolio.

How can technology leaders prepare their organisations and workforces for AI-led transformation? The first step is to recognise that AI transformation is not simply an IT project. It is a business and people transformation. Organisations need to invest in skills, but also in curiosity. We should encourage people to experiment with AI, understand where it can improve productivity and decision-making, and identify where human judgement remains essential. Leaders

That careers rarely follow a perfect plan. Many of the defining moments in my journey came from opportunities I could not have predicted. What mattered was being prepared enough to recognise them and courageous enough to step forward. I also hope readers understand that success is never an individual story. Behind every achievement are people who opened doors, challenged you, supported you and sometimes told you what you needed to hear rather than what you wanted to hear. Finally, I hope they remember that titles are temporary. Impact, integrity, relationships and the people you help become successful will ultimately say much more about your leadership than the title on your business card.

OCTOBER 2026

INTERVIEW

PNY Technologies Europe

PNY ADVANCES AI FACTORIES FOR ENTERPRISE DEPLOYMENT Laurent Chapoulaud, VP EMEA Marketing Professional Solutions, PNY Technologies Europe, discusses integrated infrastructure, GPU efficiency, and growing demand for scalable, sovereign AI capabilities across the Middle East.

Enterprises are moving beyond AI experimentation towards production deployments, increasing demand for infrastructure that combines accelerated computing, storage, networking and software. Performance remains a priority, alongside GPU utilisation, data sovereignty, energy efficiency and longterm operating costs. Laurent Chapoulaud, VP EMEA Marketing Professional Solutions, PNY Technologies Europe, discusses PNY’s endto-end AI Factory approach, the role of NVIDIA RTX PRO Blackwell and opportunities across the Middle East as organisations invest in local AI capabilities.

Interview excerpts What will PNY showcase at AI for Everything, and which technologies best reflect your current AI strategy? At AI for Everything, PNY will showcase its comprehensive end-to-end AI Factory approach, designed to help organisations accelerate their

OCTOBER 2026

AI ambitions from infrastructure deployment to production-ready AI environments. Our strategy is built around delivering the complete AI ecosystem required for modern AI workloads. Visitors will discover NVIDIA RTX PRO Blackwellpowered workstations and servers, as well as NVIDIA DGX and HGX platforms that provide the computing power needed for AI training, inference, and advanced data processing. Beyond compute, we will highlight the critical technologies that enable scalable AI deployments, including highperformance storage and data management solutions, advanced networking infrastructures based on InfiniBand and Ethernet technologies, and enterpriseready AI software stacks and services. As a Datacenter Solution Distributor, PNY also brings together a broad ecosystem of technology partners to support every layer of the AI infrastructure. This includes data center infrastructure solutions from Vertiv, networking technologies from NVIDIA, Broadcom and Celestica, storage

platforms from VAST Data and DDN, and software and enterprise services from NVIDIA, Canonical, and F5. By combining these technologies with our expertise and support services, PNY enables customers and partners to build, deploy, and scale AI factories tailored to their business objectives. Our goal is to simplify the adoption of AI by providing a complete, validated, and high-performance ecosystem that accelerates innovation and time to value.

How are enterprises moving from AI experimentation to production changing demand for GPU-powered infrastructure and highperformance computing? We are witnessing a significant shift in the AI market. Just a few years ago, most organisations were focused on testing AI through proofs of concept and limited pilot projects. Today, enterprises are moving beyond experimentation and deploying AI solutions at scale across their operations.

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networking, storage, software, and services to accelerate deployment while optimising total cost of ownership. The ability to scale AI efficiently and sustainably has become just as important as delivering the highest levels of performance.

What role do NVIDIA RTX PRO Blackwell and data centre solutions play in PNY’s approach to supporting AI training, inference and enterprise workloads? Laurent Chapoulaud, VP EMEA Marketing Professional Solutions, PNY Technologies Europe.

This evolution is being driven by the rapid adoption of AI agents, retrievalaugmented generation (RAG) applications, private AI assistants, computer vision solutions, and digital twin platforms used for simulation and optimisation. These workloads require a level of performance, reliability, and scalability that goes far beyond what was needed during the experimentation phase. As a result, demand for GPU-powered infrastructure and high-performance computing continues to grow. Organisations are investing in high-memory GPUs capable of supporting increasingly complex models, while also strengthening the underlying infrastructure required to operate AI environments

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efficiently. This includes highperformance networking, scalable storage architectures, and data center solutions designed to address the growing power and cooling requirements of AI workloads. What is particularly interesting is that the conversation has changed. The question is no longer, “How do I test AI?” but rather, “How do I industrialise AI while controlling costs and ensuring long-term scalability?” Enterprises are now evaluating their AI infrastructure based on factors such as inference throughput, operational efficiency, scalability, and energy consumption, rather than focusing solely on raw GPU performance. This is why we see growing interest in integrated AI Factory architectures. Organisations need complete, validated ecosystems that combine compute,

NVIDIA RTX PRO Blackwell technologies play a central role in PNY’s AI strategy by providing a flexible and scalable platform that addresses a wide range of enterprise workloads. While AI training remains a key priority for many organisations, enterprises are increasingly focused on AI inference, model fine-tuning, visualisation, rendering, simulation, and virtual workstation environments. RTX PRO Blackwell is uniquely positioned to support all of these use cases within a single architecture. One of the key advantages of the RTX PRO Blackwell platform is its ability to support the entire AI journey. Organisations can begin with AI development and prototyping on RTXpowered workstations, expand to departmental AI and inference deployments, and ultimately scale to larger production environments as their requirements grow. This creates a seamless path from experimentation

OCTOBER 2026

INTERVIEW

to operational AI without requiring organisations to completely redesign their infrastructure at each stage. At the same time, GPU performance alone is no longer enough. Successful AI deployments require a complete data center ecosystem that combines compute, networking, storage, software, and supporting infrastructure. This is where PNY's expertise as an end-to-end AI Factory provider becomes essential. By integrating NVIDIA technologies with enterprisegrade storage, highperformance networking, data center infrastructure, and AI software stacks, we help customers build environments that are optimised for performance, scalability, and operational efficiency. For many organisations, bringing AI closer to the data is becoming a strategic priority. RTX PRO Blackwell enables enterprises to deploy AI where it delivers the greatest value, whether at the workstation, departmental, or data center level, while maintaining control over data security, compliance, and costs. Ultimately, our goal is to help customers accelerate the transition from AI experimentation to production. NVIDIA RTX PRO Blackwell, combined with PNY’s complete portfolio of data center solutions, allows organisations to deploy AI faster, scale more efficiently, and achieve a sustainable cost structure that supports longterm AI adoption and business growth.

OCTOBER 2026

How does PNY help organisations optimise GPU utilisation, scalability and infrastructure costs as AI workloads become more demanding? As AI projects move into production, organisations face a new challenge: maximising the value of their infrastructure investments while maintaining the flexibility to scale. At PNY, we help customers address this challenge by taking a holistic approach to AI infrastructure design and optimisation. The first step is ensuring that infrastructure is properly sized for the workload. Not every AI project requires the same level of compute resources, and selecting the right GPU platform is critical to balancing performance, efficiency, and cost. By aligning infrastructure with actual business requirements, organisations can avoid both underutilisation and unnecessary overspending. We also believe that AI success depends on more than GPU performance alone. Storage, networking, software, and infrastructure components must be designed together from the outset to avoid bottlenecks and ensure optimal resource utilisation. By integrating these layers from day one, we help customers build environments that deliver consistent performance while remaining scalable as workloads evolve. Another key aspect of our approach is supporting both on-premises and hybrid AI deployments. Many organisations want to take advantage of cloud flexibility while maintaining control over sensitive data, regulatory compliance, and operating costs. By enabling customers to deploy AI resources where they create the

greatest value, whether in local data centers, at the edge, or in hybrid environments, we help them maintain data sovereignty while avoiding unpredictable cloud expenses. Ultimately, optimising AI infrastructure is about achieving the right balance between performance, scalability, and total cost of ownership. Through our end-to-end AI Factory approach, PNY helps organisations build AI environments that can grow with their needs, maximise GPU utilisation, and deliver sustainable long-term value from their AI investments.

What growth opportunities does PNY see across the Middle East as governments and enterprises accelerate investment in AI infrastructure and local AI capabilities? We see significant growth opportunities across the Middle East as organisations accelerate investments in AI infrastructure and sovereign AI capabilities. As enterprises move from experimentation to production, demand is growing for complete AI ecosystems, including AI factories, accelerated computing, storage, networking, and data center solutions. The UAE and Saudi Arabia are establishing themselves as major AI hubs, creating strong momentum across the region. Through our long-standing partnership with NVIDIA, our expanding data center portfolio, and our regional partner ecosystem, PNY is well positioned to help customers build and scale the AI infrastructure needed to support their long-term innovation goals.

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Amadeus

AMADEUS MAPS GULF’S CONNECTED TRAVEL OPPORTUNITY Jamel Chandoul explores how AI assistants, integrated mobility platforms and personalised loyalty rewards can shape seamless travel across the Gulf.

Connected mobility is becoming central to the Gulf’s travel ambitions, bringing AI-powered assistants, autonomous transport and integrated booking platforms into sharper focus. Delivering a seamless journey will depend on collaboration across airlines, airports, transport authorities and technology providers, alongside traveller trust, affordability and convenience. Jamel Chandoul, Regional Senior Vice President, EMEA Travel Sellers, Amadeus, discusses how digital platforms can connect different modes of transport, support more sustainable choices and make loyalty rewards more relevant throughout the journey. Chandoul also examines the infrastructure and partnerships needed to translate demand for smarter travel into practical, connected services across the region.

Interview excerpts What would it take for the Gulf to become a global proving ground for autonomous vehicles and drone taxis? www.tahawultech.com

The Gulf is arguably already moving from proving ground to early deployment market. Globally, our research found that 48% of travellers would consider autonomous vehicles and 45% would consider drone taxis, but in the UAE these technologies are no longer purely hypothetical. Dubai has moved into commercial autonomous taxi operations, has set a target for 25% of journeys to be autonomous by 2030, and has committed air-taxi programmes progressing toward commercial deployment. The next stage is about scaling trust and integration. Success will depend not just on the vehicles themselves, but on regulation, safety, digital infrastructure and how easily new services connect with airports, airlines, public transport and existing mobility platforms. The Gulf has an advantage because governments, transport authorities and private operators can collaborate at ecosystem level rather than introducing these services in isolation.

How is Amadeus preparing EMEA travel partners to meet the rising demand for AI-powered travel assistants? The demand signal is very clear. Globally, 68% of travellers say they are likely to use an AI-powered travel assistant, rising to 74% among business travellers, while 86% see AI as useful before a trip and 84% during it. In the UAE and Saudi Arabia, regional research suggests AI adoption is already particularly advanced, with nearly three-quarters of travellers having used AI to research or plan a 2026 holiday. For Amadeus, preparing travel partners means making the underlying travel content, availability and servicing capabilities accessible in ways that AI-powered interfaces can use. The Amadeus Mobility platform brings together realtime content from multiple providers, while solutions such as Cars Quick-Connect and Transfers Quick-Connect simplify connectivity for travel sellers. The objective is ultimately to make AI useful

OCTOBER 2026

INTERVIEW

Jamel Chandoul, Regional Senior Vice President, EMEA Travel Sellers, Amadeus.

OCTOBER 2026

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across the whole journey, from recommendations and booking through to real-time changes and personalised support. Trust must also underpin adoption. Our regional research shows that travellers are comfortable using AI for discovery and recommendations, but are still more cautious about handing over complete control of a transaction. The nearterm opportunity is therefore likely to be AI that assists and anticipates, while keeping the traveller in control.

With over 60% of travellers willing to pay more for sustainable options, how far can that appetite realistically shift the Gulf’s ground transport mix? Traveller demand can accelerate the shift, but price and practicality will remain decisive. Globally, 62% of travellers say they would pay more for sustainable mobility, but 46% say only “a little more,” compared with 16% willing to pay significantly more. The findings tell us sustainability matters, but it still has to compete with affordability and convenience. Such nuance is especially relevant in the Gulf. Around 83% of UAE and Saudi travellers say they consider environmental impact when booking travel, yet the motivations for adopting electric mobility are broader than sustainability alone: lower running costs are the leading EV driver in the UAE, while advanced technology is particularly important in Saudi Arabia. Practical barriers also include charging infrastructure and the effect of extreme heat on EV energy consumption.

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So the strongest route to changing the transport mix is likely to be making lower-emission options competitive on cost, technology and convenience, rather than expecting travellers to choose them simply because they are greener.

How close is the industry to delivering real-time, cross-modal loyalty rewards instead of simple points collection? The technology and consumer appetite are increasingly there, but the industry still needs greater integration between providers. Our research shows that nearly seven in ten travellers consider loyalty important when choosing mobility providers, while 47% of those who value loyalty want real-time offers during their trip, 37% want personalised rewards and 34% want seamless point redemption across different transport modes. The Gulf is a particularly interesting market because consumers are already familiar with sophisticated ecosystembased loyalty models. The regional loyalty market is expected to reach around US$3.4 billion in 2026, and programmes such as Etihad Guest, Careem Plus and Saudi Arabia’s Qitaf already extend rewards beyond a single transaction or category. The next step is connecting these ecosystems more deeply. Amadeus Mobility can support this by allowing traveller loyalty information to move with the booking, helping providers recognise status and present customised rates, services or rewards. The end goal is loyalty that responds to where someone is in their journey, rather than simply awarding points after it ends.

What role should Gulf airlines, airports and government transport bodies play in scaling Mobility-as-a-Service platforms? Gulf airlines, airports and government transport bodies have to act as ecosystem partners rather than individual service providers. Globally, 87% of travellers say integrated mobility services are useful, and 56% would consider Mobility-as-aService platforms that bring different transport modes into a single planning, booking and payment experience. Dubai already offers a strong indication of what that can look like. RTA’s S’hail platform brings metro, tram, taxis, ride-hailing and micromobility into a common journey-planning layer, while public transport, shared mobility and taxi usage reached more than 802 million trips in 2025. To scale that model across the Gulf, government transport authorities can provide the regulatory framework, common standards and infrastructure; airports can become multimodal interchange points rather than simply aviation hubs; and airlines can extend their role beyond the flight by integrating first- and last-mile mobility into the wider passenger journey. Technology providers such as Amadeus can help connect that content and make it bookable and serviceable through a consistent digital layer.

OCTOBER 2026

INTERVIEW

Ecocoast

ECOCOAST CONNECTS MARINE PROTECTION WITH REAL-TIME ENVIRONMENTAL INTELLIGENCE Joachim de Jenlis discusses how the Xylem partnership, advanced sensors, and local engineering support can help GCC operators respond faster to coastal risks

Reliable environmental data can give ports, desalination facilities and power plants valuable time to respond to marine contamination before it disrupts operations. Ecocoast’s partnership with Xylem adds monitoring capabilities to its marine protection and regeneration portfolio, connecting physical measures with continuous insight into water conditions. Successful deployment also depends on local expertise. High temperatures, salinity and marine fouling place additional demands on instruments, making integration, calibration and maintenance central to dependable monitoring. Speaking to CNME, Joachim de Jenlis, CEO of Ecocoast, explains the operational value of early alerts, growing demand for continuous monitoring and the potential to integrate connected buoy data into existing port and plant systems. Jenlis also highlights why building long-term coastal records will help operators understand changing conditions and identify unusual events.

OCTOBER 2026

Interview Excerpts What does the partnership with Xylem enable Ecocoast to deliver differently for environmental monitoring projects across the GCC? It means that we can offer the full package now. Our portfolio already protects and regenerates marine environments, such as silt curtains that contain sediment during dredging, booms that contain oil and debris, reef systems that bring habitat back. With Xylem, we add the monitoring component to that. The other part is the people. Some of the engineers now building these systems for us worked at Xylem for 15 years before they joined Ecocoast. The technology itself has been available in this region for a long time, and anyone could buy the sensors. What was missing was a team on the ground who knows how to specify them for the Gulf region, get them in the water and

keep them running without waiting for parts from abroad.

How can real-time monitoring improve the way ports, utilities and coastal developments respond to environmental risks? Looking at what’s happening in the region right now, oil spills aren’t a theoretical risk anymore. For critical infrastructure, that’s a real problem. Desalination and power plants depend on clean seawater coming in. If contamination reaches the intake, you get reduced output, damaged systems, or in the worst case, a shutdown. With periodic sampling, you’ll find out the operational way. Output drops or someone on a boat sees a sheen. By then, it’s already inside the process, and the only question left is how much damage was done. With a hydrocarbon sensor close to the intake, it works the other way around. An alert comes in, and someone can close the intake, switch source, or get containment

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What role will technologies such as connected buoys, advanced sensors and remote monitoring platforms play in the future of coastal protection?

Joachim de Jenlis, CEO of Ecocoast.

before it reaches the plant. That’s what real-time monitoring does. It doesn’t prevent incidents, but it gives you the time to respond to them.

Which marine and coastal applications are seeing the strongest demand for continuous environmental intelligence across the region? We are seeing the strongest demand from plants at the moment, so desalination and power. If a plant supplies a city, you cannot afford an unplanned shutdown, and a monitoring system costs a fraction of a single day of lost production. Then ports and terminals, for similar reasons, and coastal development.

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Dredging and reclamation come with environmental permits and conditions on water quality. If you cannot show what the water was doing, work can stop.

How important are local integration, maintenance and technical support when deploying environmental monitoring systems in GCC conditions? Very important. It’s the difference between a system that works and one that worked. Conditions here are harder on instruments than people expect. Water above 35°C for weeks at a time, high salinity, and fouling that can affect a reading within weeks. It comes down to time. A part shipped from Europe or the US takes weeks, plus customs. From Umm Al Quwain or Yanbu, it’s days instead.

A buoy today is a platform rather than a single instrument. It carries water quality, currents, waves, tides and weather, streams live, and you can open it on your phone from anywhere. Ten years ago, that was a research setup. Now you simply specify it. Where it goes next is integration. At the moment, a client looks at a monitoring dashboard separately from everything else they run. That will change, and the data will feed into the systems operators already use to run a port or a plant. The other part is the record. Northern Europe has coastal data going back decades, which is why an operator there can say that a summer is unusual, or that a bloom is early. Here, most sites have no continuous record at all, simply because nobody was measuring. You cannot spot something unusual without knowing what normal looks like for that site, and normal is shifting as the Gulf warms. So, every site monitored continuously now is building something you cannot buy back later. Our role in that is a practical one. Put reliable systems in the water, keep them accurate, and make sure the data means something.

OCTOBER 2026

OPINION

Backbase

CLOSING TICKETS, LOSING LOYALTY: WHY BANKS STILL GET CONVERSATIONAL AI WRONG Success should be measured by problems resolved, effort reduced and trust earned.

It’s been a decade since regional banking pioneers began their journeys towards conversational AI with the introduction of their first chatbots. While early iterations had their missteps, lessons were quickly learned, capabilities improved and use cases expanded. Fast forward to today, and it would appear that conversational AI agents are delivering on their promises. Customers seeking balance enquiries, transaction information and routine service requests are increasingly unlikely to ever connect to a human agent. By metrics such as containment and deflection, that’s a win. But scratch a little below the surface, and what seems like a success for banks, can look rather different for their customers. There is a contradiction here worth examining. Banks have spent years optimising conversational technology around containment, deflection and cost-toserve. These are important measures of operational efficiency, but they tell us surprisingly little about

OCTOBER 2026

the quality of the customer relationship. Conversational AI can successfully prevent a customer from reaching an employee and still leave them frustrated. And therein lies the rub. Closing the ticket and strengthening the relationship are not the same thing.

Technology is no longer the excuse A decade ago, the inability of AI to meaningfully bolster customer relationships was understandable. Rigid decision trees and predefined intents meant that when customers moved outside the script, the illusion of conversation and personalised service quickly collapsed. Today however, quantum leaps in natural language processing mean models can interpret ambiguity, maintain context and service far more complex requests. Making an AI agent sound more human

Closing the ticket and strengthening the relationship are not the same thing.”

is therefore no longer a breakthrough. Nor should it be the objective. A business enquiring about a seemingly fraudulent transaction does not particularly care whether the response sounds warm and conversational. They care whether the bank can identify the transaction, understand why they are concerned and help resolve the problem. The difference between a conversational AI agent that says, “I can help you understand how transaction disputes work” and an assistant that says, “I found the transaction. Would you like me to dispute it?” has relatively little to do with eloquence. In short, the true conversational AI bottleneck in banking has shifted from the model to what sits behind the conversation.

Context matters more than personalisation Industry gurus have romanticised personalisation for years, but personalisation on its own can be little more than a cosmetic improvement. Knowing a customer's name,

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Justin Arnoldi, Managing Director EMEA and APAC, Backbase. preferred language, product holdings, or propensity to buy a credit card, may make an interaction more relevant. It does not necessarily make it more useful. What really matters is context, and that goes much

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deeper. If a customer asks why a payment has not arrived, useful AI needs to understand which payment they mean, its current status, what happened when they contacted the bank yesterday and what options are available to resolve it. If

the issue needs to move to an employee, that context should move with it. Asking the customer to explain everything again simply transfers the friction from one channel to another. This is why the next phase of conversational banking is less a model challenge than an orchestration challenge. The intelligence customers encounter at the front end needs live access to customer data, transaction information, banking workflows and the appropriate controls governing what it can do. Without this, a sophisticated model sitting on fragmented systems risks only exposing that fragmentation. The same principle applies when AI begins taking action. Knowing what the customer wants is only the first step. The system also needs to know whether an action is permitted, which workflow should execute it, what approvals are required and when the interaction needs human judgement. These foundations are what turn conversational AI from an impressive interface into something capable of actually banking. That’s the distinction. Customers don’t necessarily hate banking bots. But they almost certainly will hate bots that can’t bank.

Where the GCC tests this hardest The GCC brings the challenges of context and orchestration into sharper focus. Customers across

OCTOBER 2026

OPINION

the region often switch seamlessly between Arabic dialects and English within a single interaction. They also tend to have multiple relationships with each financial institution, spanning salary and savings accounts, credit cards, loans, wealth management and more. When issues arise, the cause is often not the model itself, but the underlying data, workflows, language coverage, hand-offs and controls that support the conversation. The regional context also sharpens the build-versusbuy decision. Hyperscalers have made it easier to build support agents, but they do not eliminate the need for robust governance and data orchestration. Banks must still determine whether the system can access the right context, adhere to policy, complete the required workflow and explain its actions. That is the buildversus-buy question that really matters. Workforce planning adds another layer of complexity. Automation targets and national hiring commitments, including Emiratisation and Saudisation, often sit with different teams. Yet their effects converge on the same operating model and P&L. The question is not simply how quickly a bank can reduce service costs. It is which tasks AI should handle, which should remain the responsibility of employees, and where human judgement matters most. For these reasons, AI

OCTOBER 2026

initiatives rarely fail during the pilot stage. They fail in production, when the complexities of regional nuance, institutional context and operational delivery begin to compound.

From answering questions to anticipating needs These considerations warrant a new way to think about conversational AI maturity. The progression is not simply from a basic chatbot to an increasingly intelligent chatbot. It is from answering, to advising, to acting and ultimately to anticipating. Answering is where much of banking automation began. A customer asks a question and receives information. Advising introduces richer context, allowing AI to interpret the customer's circumstances and suggest an appropriate next step. Acting takes the next leap, connecting that intelligence to banking workflows so that, within clearly governed boundaries, the system can execute what the customer needs. Anticipating is where the relationship changes most significantly. Instead of waiting for a customer to discover that an upcoming payment will leave their account short, the bank can recognise the issue beforehand. Rather than simply explaining the situation, it could identify available funds elsewhere and ask whether the customer wants to move them.

Each step requires greater context, orchestration and trust. Banks therefore should not rush towards maximum autonomy. The opportunity is to progressively expand what AI can do as the underlying data, workflows and governance mature alongside it.

Customer service to customer relationship Market leaders are already heading in this direction, and Boubyan Bank offers a tangible example. Its digital assistant, Musaed, has evolved from a chatbot into a voice-enabled service that customers can access through the banking app or contact centre. Customers can ask questions in formal Arabic or Kuwaiti dialect and receive spoken guidance on accounts, cards and financing. That local language capability makes the experience distinctive as customers can approach the bank in the language they use every day, with less need to adapt to a scripted interface. It is a practical step towards making digital banking feel more accessible and familiar. The opportunity for Middle East Banks is now to connect such ease of interaction with the context and ability to act that customers need. Success should be measured by problems resolved, effort reduced and trust earned. Closing a ticket may save the bank money. Giving customers confidence that their bank understands them and can help, is what earns their loyalty.

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OPINION

ServiceNow

HOW TO CALCULATE ROI TO DETERMINE AI VALUE AI spending jumped 110% in a single year. Most organizations still can't say what they got for it.

Executive boards are experiencing a quiet shift. Last year, the prevailing critique of AI was that it appeared everywhere except the income statement. That’s no longer true. AI has arrived on the income statement...but likely as a line-item expense for most companies. AI spending jumped 110% in a single year, according to the ServiceNow Enterprise AI Maturity Index 2026. By 2027, AI is projected to consume more than 20% of the average IT budget. Although the investment is real, the ability to account for it isn't keeping pace. This widening asymmetry is propelling executive skepticism. Boards of directors aren’t just reacting to the high cost of tokens. They're also frustrated by an inability to answer a more fundamental question: Is AI generating economic value? The organizations that can answer that question affirmatively are already pulling ahead. Most of these AI Pacesetters — the mature organizations our research identifies as leaders — have created implementation plans with defined metrics and timelines for AI transformation. Only 17% of other organizations have done the same.

OCTOBER 2026

To calculate return on investment (ROI) in AI requires a departure from traditional software accounting. Rigid procurement metrics won't get you there. What's needed is a dynamic operational framework built for the way AI actually creates value.

The problem of nondeterministic value The primary obstacle to measurement is that AI value is inherently nondeterministic. Conventional enterprise software operates on linear transactions: A contract is signed, a platform is deployed, a process is automated. Cause and effect are visible. AI doesn’t work that way. Applications, particularly those using large language models (LLMs) or predictive analytics, operate in a gray area. The cost of an LLM that sharpens executive decisionmaking is known to the penny. The return resists a standard invoice. This isn’t entirely new territory. Corporations have

Transparency is what makes the number credible.”

always struggled to isolate the exact economic output of a manager, single software engineer, or corporate strategist. Salaries are known, but individual contributions are understood only in aggregate. The current environment differs not in the nature of the uncertainty, but in the scale of the capital deployed. At present spending levels, AI demands rigorous empirical scrutiny. Vague assertions of "technological necessity" are no longer sufficient. The Enterprise AI Maturity Index puts a number on this gap. While overall AI maturity increased in 2026, many organizations have yet to implement AI-powered workflows. The tools are arriving faster than the connective tissue is being deployed to govern and measure them. The fix starts at the top. To mitigate this issue, executive leadership must intervene to establish a unified corporate taxonomy — defining exactly how the enterprise quantifies both cost and value — and enforce it across all business units.

The operational framework To course-correct,

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organizations must evaluate every AI deployment across four operational pillars: Adoption: What percentage of the target workforce is actually using the tool? Low adoption doesn't always mean the technology failed; it often means the deployment skipped the change management that makes new tools stick. Either way, you can't extract value from a tool people aren't using. Utility: Of the people who are using this new tool, how many are getting something out of it? Adoption tells you reach; utility tells you whether the tool is working as intended. A customer service agent who opens the AI assistant every day but ignores its suggestions isn't a utility success story. Impact: Did the business metric you were trying to move — response time, case volume, error rate — show measurable improvement? This is where most organizations fall short, not because the impact isn't there, but because no one defined the target metric before deployment. If you didn't establish a baseline, you can't demonstrate change. Value: What is that improvement worth in financial terms? Translating operational outcomes into financial reality requires making assumptions. Those assumptions should be explicit, documented, and reviewed. Transparency is what makes the number credible.

The moving frontier This measurement crisis is, at

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Vijay Kotu, Chief Analytics Officer, ServiceNow.

37 its core, a leadership failure. When data science teams and finance departments calculate ROI using conflicting methodologies, the numbers diverge. And the moment they clash, strategy loses internal credibility. Leadership also needs to recognize that any framework built today carries a built-in expiration date. Currently, enterprises dedicate significant analytical resources to calculating the precise ROI of text summarization or basic search augmentation. Within two years, this exercise will be obsolete, not because the technology loses utility, but because it becomes standard infrastructure. Consider enterprise internet search. Modern

corporations don’t calculate the ROI of a browser search query. It stopped being a competitive advantage the moment it became a baseline expectation. As the technological frontier advances, the definition of value inevitably shifts. Leadership’s job is to build an AI scorecard and to keep evaluating it beyond deployment. The leading enterprises have stopped debating whether AI works. They're executing on specific parameters, measuring what moves, and focusing on what performs. That analytical specificity is what separates AI programs that build durable value from those that remain expensive experiments.

OCTOBER 2026

OPINION

GSMA

BUILDING FOUNDATIONS OF INTELLIGENT ECONOMY Fayez Abu Awad, Policy Director MENA at GSMA, discusses how AI, advanced connectivity and strategic digital infrastructure investments can accelerate economic transformation across Qatar and the wider Middle East.

Qatar and the wider Middle East’s ambitions for intelligent economies depend on translating investment in AI, advanced connectivity and digital infrastructure into measurable productivity and growth. Success requires coordinated policies, trusted data governance and a skilled workforce, alongside clear business priorities. Fayez Abu Awad, Policy Director MENA at GSMA, examines how these foundations can help the region develop locally relevant AI capabilities, strengthen enterprise competitiveness and retain greater economic value from digital investment. He also shares his expectations for MWC Doha 2026 and outlines the decisions business leaders should prioritise to turn technological progress into lasting commercial results.

Interview excerpts What role do you expect AI to play in accelerating Qatar’s and the wider region’s shift towards intelligent economies over the next five years? AI will be one of the defining forces shaping the region’s

OCTOBER 2026

economies over the next five years but its significance should not be measured by expenditure or adoption rates alone. The proper test is whether it enables an economy to become more productive, more innovative and better able to deploy its human and institutional capabilities. The region already has considerable momentum. Around 39% of MENA enterprises make advanced use of generative AI, while AI, mobile connectivity and devices are expected to account for nearly 45% of regional digital-transformation spending. Yet investment is only the beginning. The countries that derive lasting value from AI will be those that combine it with sound data governance, trusted regulatory frameworks, advanced connectivity and people who can build, manage and challenge these systems. Qatar and the region at large

An intelligent economy is not one that deploys the greatest number of systems; it is one that uses technology to make better decisions.”

also have an opportunity to shape AI according to their own economic and social priorities, rather than remaining principally consumers of technologies developed elsewhere. That means fostering Arabiclanguage capabilities, supporting solutions relevant to local industries and ensuring that universities, businesses, policymakers and the technology sector work in much closer concert. National planning for an undertaking of this scale demands rigorous coordination and clear strategic direction. International alignment and harmonisation will certainly reflect the complexity involved in the national efforts. AI is ultimately an instrument, not an end in of itself. An intelligent economy is not one that deploys the greatest number of systems; it is one that uses technology to make better decisions, create more valuable services and enlarge human potential.

How are advances in 5G, 5G-Advanced, and nextgeneration connectivity reshaping the way enterprises across the Middle East operate and compete? www.tahawultech.com

Fayez Abu Awad, Policy Director MENA at GSMA.

technology project. The real gains arise when connectivity forms part of a coherent business and operating strategy. Policy matters here as well. Spectrum availability, licensing and the wider investment environment must keep pace with the demands placed upon networks. In the longer term, the most competitive markets will not simply be those with the fastest networks, but those that combine advanced connectivity with sufficient certainty for businesses to invest, experiment and scale.

Which digital infrastructure investments, from data centres to cloud and edge computing, are most critical to the region’s long-term competitiveness?

The most consequential change is that connectivity is becoming less visible as a technology and more fundamental as an economic capability. Enterprises should not have to organise themselves around the limitations of the network. They should be able to connect assets, operate across locations, launch services and respond to customers with speed and confidence. That alters the basis of competition. With nearly half of mobile connections in GCC markets already on 5G, advanced connectivity

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will increasingly be regarded as a basic condition of doing business rather than a distinction in itself. Competitive advantage will come from what enterprises are able to build upon it: more responsive operations, new services, better customer experiences and business models that were previously impractical. 5G Standalone, 5G-Advanced, private networks and newer Internet of Things capabilities can provide organisations with considerable flexibility. But their value will be diminished if each is treated as a separate

The region has already demonstrated that it is prepared to invest seriously in digital infrastructure. The next question is more demanding: what sort of economy will that infrastructure enable? Data centres, cloud platforms, edge computing, fibre, subsea connectivity and advanced mobile networks are all essential components. But installed capacity is not, by itself, a measure of economic success. The more meaningful test is whether these investments make it easier to establish and scale technology businesses, attract international investment, develop local intellectual property, conduct research and retain high-value digital

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OPINION

activity within the region. We therefore need to think about digital infrastructure as an ecosystem rather than a collection of assets. Energy, international connectivity, skills, data governance and regulation are now elements of the same competitiveness equation. A country may possess excellent physical infrastructure and still underperform if access is difficult, talent is scarce or policy fails to evolve with technology. The policy objective should be to sustain investment while providing the predictability required for long-term decisions. MWC26 Doha, particularly alongside the ITU Plenipotentiary Conference, offers the region an opportunity to move the conversation beyond what has been built and towards the economic and regulatory conditions needed to make full use of it.

What are your expectations for MWC Doha 2026, and which trends do you believe will dominate the conversation at the event? I expect MWC26 Doha to reflect a more mature phase in the technology debate. The conversation is moving beyond enthusiasm for individual technologies and towards the strategic choices they require from business and government leaders. AI, 5G-Advanced, cloud, cybersecurity and the longer-term path towards 6G will naturally feature prominently. Yet the most useful discussions will

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not consist of predicting which technology comes next. They will ask where investment is most urgent today, which capabilities must be developed, and what policy and commercial conditions are needed for the next generation of services to emerge. The co-location with the ITU Plenipotentiary Conference gives the event unusual significance. Bringing the industry and international policy communities together creates the prospect of a more direct exchange between those who build and finance technology and those who shape the frameworks within which it develops. Skills must also occupy a central place in the discussion. Sophisticated networks and AI infrastructure have little value without people able to operate, secure and apply them productively. The defining question for MWC26 Doha may therefore be not what is the next technology but what decisions must we take now if we are to be ready for it.

What should business leaders across the region be doing now to turn these technology developments into measurable growth? The greatest risk for many business leaders is not moving too slowly; it is attempting to pursue too many priorities at once. AI, cloud, 5G, cybersecurity and automation are all advancing rapidly, and the temptation is to treat every development as immediately

strategic. The result can be a crowded portfolio of initiatives with remarkably little transformation. Leaders therefore need to exercise disciplined selectivity. They should ask where technology can materially improve the economics of the business, strengthen the customer proposition or create a credible source of new revenue. They should also distinguish between capabilities that are fashionable today and those likely to remain important in three or five years. Technology alone, however, does not transform an organisation. Structures, skills, incentives and culture often move more slowly. If employees do not understand the purpose of a new system, if managers continue to make decisions in the same way, or if incentives reward established behaviour, even excellent technology will have limited effect. Leadership must attend as carefully to organisational absorption as to technological acquisition. Across MENA, enterprise digitaltransformation spending is expected to average around 9.8% of revenues from 2025 to 2030. At that level of investment, discipline is indispensable. Growth will not come from having the longest list of digital initiatives. It will come from making a smaller number of sound choices, supporting them properly, measuring their results and changing course when the evidence demands it.

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19th November 2026

VOGO Abu Dhabi Golf Resort & Spa

#AIGovernanceAwards2026

05:30 PM onwards #tahawulTech

Building trusted AI for responsible growth AI is moving from experimentation to decisions and actions that affect businesses, governments and communities. Strong governance is now essential to scale innovation with accountability, security and trust. AI Governance Conference and Awards 2026 will convene senior leaders from business, government, technology, risk and policy to examine the frameworks, controls and leadership models shaping responsible AI across the Middle East. Join the conversation. Share your expertise. Recognise excellence.

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OPINION

AVEVA

INDUSTRIAL AI BECOMES INDUSTRY’S CONTINUITY LAYER By capturing and connecting industrial expertise, AI can help companies preserve operational memory as a generation leaves its post and business complexity intensifies, says Kim Custeau, EVP Portfolio Management, AVEVA.

Industrial plants today are seeing a demographic change that will test how well they preserve operational knowledge. As a generation of experienced workers moves towards retirement, with them goes institutional memory of industrial workflows: whether a specific alarm can wait, which undocumented repair workarounds keep a batch on track, or when an irregular hum is a response to unusual weather and when it’s potentially more dangerous. We can see industrial economies losing expert knowledge as they face a silver exodus of retiring baby boomers. The US labor force is projected to shrink by 5.9 million workers by 2030, or 3.7%. The EU had nearly 40 million employees aged 55 or older in 2023, up from 23.8 million in 2010. The trend plays across industries worldwide, from utilities to manufacturing and chemicals.

AI-infused systems as business’ continuity layer With no growth forecast in the labor force, this knowledge

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loss threatens industrial productivity and human safety. In response, economic growth will increasingly need to depend on artificial intelligence (AI) to accelerate productivity. AI-infused systems can capture and preserve industrial knowhow in a repeatable way while boosting revenue growth by up to 3 times per worker. Although some employers have been quick to cite automation as a reason for job cuts, ADP data points to a more complicated picture: As AI moves deeper into everyday business systems, it is reshaping employment and changing job profiles with new skills becoming necessary even when roles do not disappear. With that demand comes a premium on critical thinking and nuanced judgement, not least because of the need to continually audit and evaluate increasing volumes of insights. Paradoxically, as the experts retire, their knowhow is needed more than ever. Industrial AI bridges this knowledge gap by functioning as a continuity layer for

organisations, lowering entry barriers for workers and enabling them to upskill quickly. The tech also handles much of the heavy lifting by performing repetitive tasks such as indexing decades of operating histories, matching tags across datasets, flagging anomalies in real time. When accessed through humanised, natural-language interfaces, these tools make it easier to consult critical manuals or build low-code dashboards to quickly grasp operational metrics. Teams can quite simply do more with less. Supporting this transformation is industrial intelligence, which deciphers and applies industrial data using domain expertise enriched with AI to enhance decisions and accelerate sustainable growth. Technologies such as knowledge graphs, digital twins and industrial AI assistants enable this process quickly orchestrating and analysing that data and presenting it visually and in context to improve productivity and efficiency. Similarly, they can capture

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43 Kim Custeau, Executive Vice President, Portfolio Management, AVEVA.

and codify expert know-how, connecting the plant floor to engineering, executive levels and even external partners. Signals move down the value chain fast enough to shape decisions, which can flow back to operations just as quickly. As efficiency increases, value cycles become shorter.

Unlocking efficiency and productivity gains Workers at ENEL understand how sharing trusted operational data and AIinfused insights in real time delivers considerable gains. The Italian multinational, which brings energy and services to more than 55.4

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million homes and businesses across five continents, used a cloud-based platform to share clean operational data and AI-infused insights across the enterprise. The payoff in hard terms: new capacity available in real time with €47 million saved and the equivalent of 5,000 metric tons of carbon dioxide avoided. As new plants join the network, analytics from each unit are folded into the same window, making workflows less fragmented and decisions easier to repeat. South of the equator, teams at the Brazilian engineering company AP Consultoria e Projetos show how AI works as a continuity layer beyond

the plant floor. By improving project visibility within an AI-infused cloud-based engineering environment, multidisciplinary teams can collaborate around a single source of truth, streamlining collaboration and improving project efficiency. Results include a 90% reduction in analysis time for pipe support type and position by 90% and reducing total project delivery time by nearly 50%. The company also reduced project rework by 29% and accelerated documentation by 60%. With centralised engineering data, and decisions, teams improved visibility and coordination,

OCTOBER 2026

OPINION

helping drive more consistent execution across projects.

End-to-end overviews with humans in the lead

AI can help avoid the knowledge cliff, but these gains depend on strong data foundations and humancentered workflows. To deliver reliable guidance, AI models must be fed trusted, contextualised and structured industrial data. That requires a connected digital thread spanning engineering, operations and asset information, preserving the context needed to turn data into industrial intelligence. Only with well governed end-to-end data in context can teams make sense of the overabundance of information today’s organisations already hold.

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The differentiator is the context: asset behavior, process history, operating constraints and human decisions were made and why. Second, human-in-thelead workflows ensure that AI augments rather than replaces human expertise. The greatest value comes when AI-driven insights are embedded directly into operational workflows, putting recommendations in front of workers when they need to make a decision. Modern HMI/SCADA systems provide a critical interface between operational data, digital twins and human decision-makers, helping translate AI-driven insights into action. A clear chain of custody linked to human oversight also supports the explainability and

transparency that legislation increasingly requires. Third, as research shows, culture and leadership considerations are central to the successful adoption of AI. Nearly all staff are now digital employees, and involving them in career-enhancing opportunities through continuous learning and open experimentation can help build trust and counteract fears around displacement. Other considerations include cybersecurity, energy efficiency and a strategic approach to innovation.

Scaling expertise through industrial intelligence Experience remains a valuable asset in industry and one of the hardest elements to replace at a time when industries must increasingly navigate what is recognised as a nonlinear, accelerated, volatile and interconnected world. In such a dynamic situation, the future of industry lies in scaling industrial intelligence, where human judgment and domain expertise combine with AI’s abilities to analyse data, surface insights and support timely decisions. It’s tempting to fear the silver tsunami as a damaging shortage of labor. A more strategic perspective is to approach it as a test of whether an organisation can capture and transfer operational knowledge. When expertise is embedded in data and workflows, business continuity becomes a source of resilience and competitive advantages over the long term.

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IFS Loops

PRODUCTISING AI AGENTS: LESSONS LEARNED IN CROSSING CHASM When looking at the adoption of AI in the workplace, the issue isn’t people building agents – almost everyone is. It’s getting the use and deployment to stick with in companies. New research from MIT shows that 95% of gen AI pilots fail to produce measurable financial impact (MIT / NANDA Initiative, 2025). 80% of deployment effort is consumed by data, governance, and workflow integration, not AI. That single figure should reframe how every team approaches this work. What this statistic is showing is the whole story. While it’s easy to blame model quality, and assume that the final interaction point is where the problem lies, it simply isn’t true. The real issue lies in poor workflow integration, missing governance, and metrics that were never aligned to a business outcome in the first place. After deploying agents in real enterprise and industrial environments, here are the eight lessons that separate the pilots that quietly die from the agents that actually run in production.

Start with right problem The fastest way to kill an agentic project is to fall in

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love with the word “agentic” before you have defined the outcome you are chasing. We see teams stand up ten agents at once, convinced that breadth signals ambition. More often it signals ten simultaneous failures, because none of them was given the chance to prove value first. The discipline that works is almost boring in its simplicity: pick one highimpact, low-risk workflow and earn the right to scale by demonstrating value there. Before you commit, get honest about process variance — the places where human judgment still has to enter the loop — because those are exactly the points an agent cannot paper over. And ask the question most teams skip in their excitement: could a simple if-then rule handle this? If the answer is yes, use the rule. Agents are expensive, opaque, and hard to govern; reserve them for genuine complexity, not problems that deterministic logic already solves.

Data a real bottleneck If 80% of deployment effort goes to data engineering, stakeholder alignment, and workflow integration, then the honest conclusion

is that the bottleneck was never the model. It is data readiness and on this point, practitioners are in nearunanimous agreement. In practice this plays out in three ways. The first is standardisation: agents need data converted into uniform formats they can interpret reliably across sources, and that work has to happen before you scale, not after the cracks show. The second is breaking down silos, because an agent operating on partial information will fail in ways that are difficult to detect and embarrassing to explain — fragmentation is the single biggest barrier we encounter. The third is continuous validation. Robust API management, version control, and pipeline checks are not glamorous, but they are what keep agents running once the launch-day attention fades.

Build governance before you build agents Governance is not a phase you bolt on after the demo impresses someone. It is the foundation you pour before anything else stands on it, and in our experience it comes down to six commitments. Every agent needs a named owner, a written

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OPINION

job description, and a defined scope settled before deployment — not negotiated after something goes wrong. Promotion to production should move through staged gates, from dev to UAT to pre-prod to prod, with a human signing off at each one. Escalation paths have to be mapped explicitly, so it is clear which decisions the agent makes on its own and which it must hand to a person. You should plan for retirement from the start, defining exit criteria before an agent becomes so entrenched that no one dares turn it off. Accountability must be assigned to a human, because “the LLM said so” is never an acceptable answer when something breaks. And finally, patterns need to be standardised — common permission tiers, connector policies, and reusable structures — or you will wake up one day to find agent sprawl you can no longer reason about.

Somya Kapoor, Chief Executive Officer, IFS Loops.

after deployment, rather than treating launch as the finish line. And you invest in evaluations: benchmarks that codify what good looks like for each task the agent performs, so that “is it working?” becomes a measurable question instead of a gut feeling.

Onboarding an agent is more like hiring than deploying software

Observability and hallucination control

“Onboarding agents is more like hiring a new employee versus deploying software.” — Business leader interviewed by McKinsey That reframing changes the work in concrete ways. You give an agent a job description the same way you would a new hire — clear scope, the tools it is allowed to use, and the behavior you expect of it. You build feedback loops that verify performance at each step of the workflow and let you refine continuously

A 2% hallucination rate is perfectly fine for a chatbot and catastrophic for a claimsprocessing or financial agent. The acceptable failure rate is set entirely by what the agent touches, and that should shape how much observability you build in. It starts with logging far more than conversations. You need full traceability of inputs, tool calls, reasoning steps, and outputs, because the day a regulator or an auditor asks why an agent made a

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particular decision, the answer has to be reconstructable. Beyond logging, you have to evaluate at every step rather than only inspecting the final output, that is how you catch errors early and refine logic continuously, even after the agent is live. And you need real guardrails against prompt drift, model drift, and scope creep: defined escalation triggers and rollback procedures established before you ever touch production, not improvised during an incident.

Keep humans in the loop — by design Autonomy is something an agent earns, not something you grant on day one. The path runs through four deliberate stages, and skipping any of them tends to end badly. It begins with a pilot, where you define the critical decision points at which

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the agent must escalate to a human and let it earn autonomy incrementally from there. Rollout comes next, and the goal is collaboration rather than substitution — workflows redesigned so people and agents work together, with handoffs mapped explicitly so nothing falls through the gaps. Only once performance is proven and auditable do you scale, expanding autonomous operation while tracking accountability clearly the whole way. And running through all of it is governance: a clear delineation of who bears responsibility when the agent makes an error or causes harm, documented before an incident forces the question, not after.

Model is not competitive advantage This lesson tends to surprise people, because it contradicts where most of the industry’s attention goes: 42% of enterprise implementations found their model choice to be fully interchangeable (Stanford, 2026). If the model is not the moat, where is the durable advantage? It lives in the quality of your orchestration layer, the strength of your governance frameworks, the depth of your workflow integration, and the institutional knowledge of operating agents at enterprise scale that you can only accumulate over time. So the smarter investment is not the latest foundation model — it is the infrastructure underneath it: reusable

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agent components, validated architectural patterns, shared permission tiers, and connector policies. Get that foundation right and almost any capable model will perform well on top of it.

Security enables — it doesn’t just block The most counterintuitive lesson is also one of the most reliable: the security requirements that look like project killers at the outset are usually the very things that make it possible to put agents near sensitive data in production at all. Done well, security operates as four reinforcing layers. Prompt filtering blocks injection attempts, jailbreaks, and scope violations before the agent ever acts on them. Data protection classifies information by sensitivity and enforces least privilege, so an agent can reach only what its role genuinely requires. External access control puts every tool call, API hit, and outbound action through a defined permission gate. And response enforcement validates the agent’s outputs before they reach downstream systems or users — because the output is itself a trust boundary, and treating it as one is what keeps a single bad generation from propagating through everything connected to it.

Enterprise AI Agent Readiness Checklist Before you ship, you should be able to answer yes to all of the following: ✓ Have you defined a specific, measurable

business outcome before building? ✓ Have you fixed data silos, standardised formats, and validated your pipelines? ✓ Have you built governance — ownership, gates, escalation — before agents go live? ✓ Have you established full observability across inputs, tool calls, reasoning steps, and outputs? ✓ Have you kept humans in the loop at critical points and let autonomy be earned incrementally? ✓ Have you invested in the orchestration layer rather than the newest foundation model? ✓ Have you applied all four security layers: prompt, data, access, and response? ✓ Have you planned for agent retirement from day one?

Bottom line The agents themselves are rarely the hard part. The hard parts are the orchestration, the governance, the data foundation, and the integration into enterprise infrastructure — the unglamorous work that determines whether anything reaches production at all. The enterprises that pull ahead will be the ones that stop treating agentic AI as an experiment and start treating it as operational infrastructure. That is the shift underway right now: from automating tasks to entrusting decisions.

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OPINION

NTT Data

BEYOND OIL: AI IS RESHAPING MIDDLE EAST’S ENERGY LANDSCAPE

The Middle East’s historic role as the global energy heartbeat is entering a new chapter. While the region continues to provide over 31% of the world’s oil, its true competitive advantage is shifting from resource extraction to intelligent orchestration. As the sector accelerates toward aggressive diversification and renewable integration, the mandate for the boardroom is clear: the transition is no longer just about energy capacity; it is about energy intelligence. Today, we are witnessing a paradigm shift where AI is emerging as the primary engine of transformation, reshaping energy providers from commodity suppliers into high-performance, data-centric technology enterprises. In this new era, the Internet of Things (IoT) serves as the indispensable nervous system, a critical, enabling layer that feeds the AI models necessary to manage, predict, and optimise complex energy ecosystems with unprecedented precision. The region is currently hardwiring artificial intelligence into its national energy blueprints. We are moving beyond simple automation toward autonomous energy

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management. From advanced smart grids in the UAE to decentralised, AI-optimised microgrids in Saudi Arabia, the infrastructure is becoming aware. This intelligence is not merely an operational upgrade; it is a strategic necessity. As industrial AI adoption scales, the ability to synthesise continuous data streams from sensor-driven environments such as pipelines, turbines, and grid nodes will allow operators to move from reactive maintenance to prescriptive strategy. By leveraging these data-centric systems, leaders can now anticipate market volatility, optimise output in real-time, and align generation with complex, fluctuating demand profiles.

From Real-Time Data to Predictive Intelligence Connectivity is only the starting point. The real value emerges when data is operationalised through AI and scaled across integrated platforms that unify systems, workflows, and decisionmaking. The integration of AI into energy operations is accelerating, with the regional AI-in-energy market projected to grow at

a 22% CAGR through 2033. This growth is driven by the necessity of managing renewable energy variability. Solar and wind power are inherently intermittent, creating massive complexity for traditional grids. AI-driven forecasting models, powered by granular, real-time data, provide the predictive visibility required to stabilise these networks, maximising green energy throughput without compromising operational resilience. As these capabilities mature, the next phase of value creation will be driven by platformisation. Energy leaders are moving beyond isolated deployments toward integrated digital platforms that unify data, AI models, and operational workflows across the value chain. These platforms enable collaboration across operators, technology partners, and regulators, creating an ecosystem where intelligence is shared, scaled, and continuously optimised. In this model, competitive advantage will increasingly depend on the ability to orchestrate a connected, data-driven energy ecosystem at scale.

Securing the Digital Foundations of Energy As energy systems become

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more intelligent, they also become more exposed. The digitalisation of the grid expands the operational technology (OT) attack surface, making energy infrastructure a primary target for increasingly sophisticated cyber threats. With DDoS attacks in the region surging by 183% year-on-year in early 2024, cybersecurity is now a matter of national resilience and economic continuity. Strategic resilience requires a security-by-design philosophy. Intelligence platforms must treat security, data integrity, and network

reliability as foundational elements of the architecture embedded at the device level, monitored through automated threat intelligence, and reinforced by robust governance. The goal is to build an environment where the system is not only efficient but self-healing and inherently defensible.

mitigation of risks in a risk-free digital environment. • Integrating AI at the Edge: Distribute intelligence closer to the source to enable autonomous, splitsecond decision-making, reducing latency and increasing overall system responsiveness.

The New Priorities for Energy Leadership To thrive in this new landscape, leaders must pivot their investment strategies toward a future-proof, holistic framework: • From Asset Management to Data Orchestration: Treat connected infrastructure as the primary data source and AI as the engine for strategic decision-making. • Embracing Digital Twins: Implement virtual simulations that mirror the entire energy value chain, allowing for the stress-testing of scenarios, the optimisation of capital expenditure, and the proactive

Hani Nofal, Executive, Head of Technology Solutions, MEA, NTT DATA.

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Turning Digital Ambition into Long-Term Advantage For the Middle East, the divide is emerging between operators building intelligent, selfoptimising systems and those still managing infrastructure reactively. The future of energy leadership will be defined not only by resources, but by the sophistication of intelligence managing them. Connected infrastructure provides the data foundation, but AI and integrated platforms are the forces that will define the next generation of energy leadership. The focus for industry leaders has shifted from digital adoption to digital acceleration. It is now about how rapidly they can architect an intelligent ecosystem capable of turning data into a sustainable, strategic advantage. The Middle East’s position as a global energy leader will not be defined only by the resources beneath the ground, but by the intelligence applied above it, where data, AI, and advanced systems transform energy into a more resilient, sustainable, and dynamic force for the future.

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OPINION

ASUS

BIGGER ISN’T ALWAYS BETTER: WHY SMBS ARE RETHINKING IT

Every growing business wants to move faster. Many of those pulling ahead are starting with a smarter approach to technology. For years, building a dedicated IT department was the way to go for creating a strong foundation. Today, AI, flexible IT services and a new generation of devices give SMBs access to enterpriselevel capabilities through a more streamlined setup. For owners working with smaller teams, tighter budgets and quicker decision cycles, that opens up a practical path to growth.

Automate Routine, Accelerate Growth Gartner forecasts IT spending in the MENA region to reach $169 billion this year. As SMB owners scale up their operations, they focus more on building smarter setups rather than IT departments. AI is now used to automate repetitive tasks, letting teams focus on more important work. With AI doing the heavy lifting, decisions are made faster and data is no longer processed manually. These technologies now primarily drive IT capabilities, removing the barriers that were once only available for large companies.

OCTOBER 2026

The UAE already ranks first globally in AI adoption. Since SMBs make up over 94% of UAE businesses, they are closing the gap on enterprises faster than at any point in recent history. With the increasing AI adoption in daily workflows, SMBs can expand without the need for someone on payroll. There is a competitive advantage here if the right tools support it.

The New Wave of IT Expertise This does not mean that SMBs are abandoning IT, they are simply rethinking where it comes from. In fact, IT outsourcing is a $66.5 billion market, and SMBs now utilize managed service providers (MSPs) and hybrid models for IT services that include general consulting and cybersecurity. Rather than building and managing in-house teams, businesses can turn to IT outsourcing to access the right expertise without the overhead cost for full-time staff. This allows SMBs to harness enterprise-grade capabilities without paying enterprise costs. It is almost similar to cloud computing, which was introduced a few years ago and is now reshaping

IT support in the same way. Moreover, outsourced IT services reduce downtime thanks to readily available specialists who monitor and resolve issues before they escalate.

Private, Powerful and Built In A significant shift in business computing is the rise of AI PCs. Built with a dedicated Neural Processing Unit (NPU), these devices can perform AI tasks on-device without connecting online. For SMBs, these devices can help in automating tasks like realtime transcription, document summarization, and data analysis. Also, businesses that handle confidential data can be assured that tasks remain private. The AI PC market size was valued at $109.66 billion last year, proving that there is a rise in demand for such devices. SMBs with limited budgets can always invest in an AI PC to modernize without overcomplicating their setups.

Built for Momentum: What Fast-Growing SMBs Get Right SMBs that are moving the fastest right now are the ones that integrate AI into their

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Tolga Özdil, Regional Commercial Director, Middle East, Turkey & Africa (META), ASUS. operations. Nearly half (48%) of the small businesses in the UAE have started using AI. It is evident that the speed at which they need to scale up depends on the quality of their tools and the flexibility of their setup. Thus, businesses that take too long to adopt will be the ones who will be left behind.

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As systems get smarter, their processes get faster, and the gap between those who adopt AI and those who don’t only grows wider. Also, security for SMBs shouldn’t be an afterthought. With 47% of SMBs reporting having experienced a cyberattack, security should be embedded into all AI tools they use.

The argument that SMBs need to grow before investing in IT capabilities is no longer valid, as what they actually need is an accessible and flexible infrastructure, which is already available. With AI-ready devices, on-demand expertise and built-in security, SMBs can move at the speed of their ambition.

OCTOBER 2026

RESEARCH Dataiku

UAE LEADS IN AI AGENT DEPLOYMENT BUT FACES CONTAINMENT GAP 62% of UAE CIOs say their organisation has more than 50 AI agents in production, while the UAE has the highest proportion globally, reporting more than 500

Agentic AI has moved firmly into large-scale production across the UAE, according to new global research from Dataiku, the Platform for AI Success. Conducted by Harris Poll, the research shows that 62% of UAE CIOs estimate that more than 50 AI agents are actively running in production within their organisation, while 15% report operating more than 500, the highest proportion across the eight markets surveyed, and substantially higher than the 9% global average. UAE organisations are also investing in the expertise required to support this expansion. Among CIOs whose organisations are creating or planning embedded roles for AI experts or forward engineers, 22% expect to recruit more than ten people over the coming year, the highest compared to other countries in the study. Encouragingly, the scale of deployment has not been associated with greater reported harm. While 80% of UAE CIOs have encountered an agent that violated business

OCTOBER 2026

intent, policy, or expectations, while continuing to operate within its technical parameters, most say the behaviour was caught before it caused damage. Almost two-thirds (62%) report that the incident was caught before causing customer, financial, compliance, or operational impact, the highest proportion globally, and compared with 48% overall. Only 18% say such an incident resulted in actual impact, the lowest figure across the markets surveyed and substantially below the 31% global result. UAE organisations are also planning for disruption in the technologies underpinning their agent strategies. Almost two-thirds (63%) plan to use more, or different, models to strengthen business and AI continuity, while 62% are considering open-source alternatives as a hedge

An agent you can spot in one system but can't stop everywhere else isn't contained, it's just been noticed”

against future unavailability. These measures could help organisations build AI sovereignty and insulate themselves against realworld disruptions such as the temporary suspension of Anthropic’s Fable 5 and Mythos 5 models under a U.S. government order. However, the research shows that preventing immediate harm and containing a problematic agent across the enterprise are very different capabilities. Only 5% of UAE CIOs say their organisation could reliably identify and contain a problematic agent across environments within one to two hours, among the lowest results in the study and half the worldwide figure of 10%. A further 27% could intervene later that day, meaning more than two-thirds could not reliably contain the agent on the same day. For 45%, containment would take between 24 and 48 hours, and almost one-quarter (23%) say they would require two days or more, one of the highest figures in the study. "CIOs in the UAE are

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Sid Bhatia, Area Vice President and General Manager, Middle East, Turkey, and Africa, Dataiku.

running agents at a scale few markets have reached, and they're unusually good at catching bad behaviour before it does damage. But detection and control are different capabilities, and the research shows a real gap between them. An agent you can spot in one system but can't stop everywhere else isn't contained, it's just been noticed,” said Florian

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Douetteau, CEO and cofounder of Dataiku. The containment gap comes as AI agents increasingly operate across different platforms, data environments, and business applications. Only 18% of UAE CIOs report having a fully unified view of agents across these environments, while just 12% say agent lifecycle management is standardised

throughout their organisation. Without that unified view and standardised lifecycle, an agent detected in one environment could continue operating elsewhere before teams are able to intervene. At the same time, pressure on UAE technology leaders to deliver measurable results is intensifying, with 100% of UAE CIOs surveyed reporting greater board pressure to demonstrate measurable AI ROI compared with 2025. Meanwhile, 93% say their CEO has indicated that their job security depends on AI outcomes. Against this backdrop, 90% would stake their job on delivering measurable AI results. “The UAE has established a strong foundation for agentic AI, with enterprises deploying at scale, investing in specialist expertise, and preventing a high proportion of agent incidents from causing real-world harm,” said Sid Bhatia, Area Vice President and General Manager, Middle East, Turkey, and Africa at Dataiku. “The next stage is to connect those safeguards across the enterprise. That means giving CIOs a unified view of their agent population, clarity on who has the authority to act, and the ability to intervene immediately, regardless of where an agent was built or which system it uses. Rapid containment will be critical to protecting the UAE’s progress as agentic AI becomes embedded across the economy. For CIOs, there is also a significant personal stake in getting this right.”

OCTOBER 2026

RESEARCH Everpure

88% OF EXECUTIVES FEAR DATA SOVEREIGNTY FAILURES COULD COST THEM THEIR JOBS New Everpure research reveals a "sovereignty gap” – 64% of enterprises lack formal data sovereignty strategies to control their data and defend against geopolitical risks and AI exposure.

Everpure, the company revolutionising storage and data management, today released new global research revealing that 88% of large enterprise C-suite leaders believe a data sovereignty failure could cost them their jobs, while 91% worry about financial and reputational damage to their organisation. Despite these high stakes, 64% of organisations operate without a formal data sovereignty strategy in place, exposing a vulnerability in modern enterprise data management in today’s uncertain geopolitical environment. Data sovereignty has evolved into a defining business risk—with challenges ranging from foreign-mandated data exfiltration to potential Denial of Service (DoS) incidents. Everpure’s Global Data Sovereignty Report 2026 surveyed 2,100 enterprise leaders across eight countries to evaluate strategic intent against real operational readiness. The results reveal a stark divide:

OCTOBER 2026

Data Sovereignty Concern is Real: 90% of organisations recognise data sovereignty as a business concern, with the overwhelming majority expecting severe financial or leadership consequences in the event of a failure. 85% are willing to compromise on advanced features and functionality to work with a local or sovereign provider. 40% are already limiting their use of SaaS providers reliant on non-domestic infrastructure.

Recognition without Readiness: Despite these revelations, 64% of organisations operate without a formal data sovereignty strategy in place. 62% lack full visibility into who can access, control and manage their data.

Sovereignty is not simply about where data is stored, but having full visibility and control over it through modern data management.”

56% have no mitigation plans for geopolitical data exfiltration or service disruption. 56% admit they lack the skills and capacity to deliver sovereignty initiatives, while 36% are facing challenges with executive buy-in. Only 9% say protection from extraterritorial data access is a top priority. “Senior leaders understand their jobs are on the line over data sovereignty, yet many are still focused on the wrong risks. Sovereignty is not simply about where data is stored, but having full visibility and control over it through modern data management. Who can access data, which jurisdictions apply and whether businesscritical data or services could be disrupted are key questions every organisation should be asking,” said Alex McMullan, Chief Technology Officer, International, Everpure. The findings expose a clear “sovereignty gap” between executive recognition of risk and actual operational readiness. Many companies still treat sovereignty as a routine cybersecurity or

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compliance exercise. As a result, organisations fail to secure control of their data, and cannot defend against geopolitical threats that could result in significant consequences. “Digital sovereignty has moved from a compliance conversation to a critical board-level concern. The challenge for executives is not just about knowing

where their data are hosted. It is about being in total control of all data access and transfers (including all metadata), guaranteed protection against extraterritorial data requests, and managing IT and vendor risks in the light of geopolitical uncertainties,” said Rahiel Nasir, Research Director and Lead Analyst, Worldwide Digital Sovereignty, IDC.

Alex McMullan, Chief Technology Officer, International, Everpure.

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Sovereignty by Design A successful sovereignty strategy requires moving from passive risk recognition to targeted operational execution. Organisations can follow a set of interconnected steps to become sovereign by design – a businessdriven, risk-aware framework where sovereignty controls and governance are applied according to the risk of each data set, application and workload. The focus shifts from national sovereignty to corporate sovereignty, an approach based on an organisation’s specific risk appetite and view on regulation. This model enables businesses to protect critical assets from key sovereignty risks without sacrificing the flexibility, innovation or scale of global SaaS and cloud providers. Everpure Data Intelligence supports this model by discovering, classifying and contextualising enterprise data across the Everpure Platform, public clouds, SaaS applications, and thirdparty storage. This facilitates sovereignty by providing total visibility of their data estate, enabling organisations to make informed decisions about how data should be governed and protected. By focusing on data and mitigating against risks, organisations can become sovereign by design – transforming sovereignty from a barrier to innovation to a source of resilience and competitive advantage.

OCTOBER 2026

INDUSTRY RADAR

IBM

IBM BRINGS BOB TO SELF-HOSTED ENVIRONMENTS FOR SOVEREIGN AI DEVELOPMENT Enterprises can deploy IBM’s agentic software development platform within controlled infrastructure to support sensitive workloads, data residency and AI governance requirements.

IBM Bob supports AI-powered software development and modernisation across customer-managed infrastructure.

IBM has introduced a selfhosted deployment option for IBM Bob, enabling enterprises to use its agentic software development platform within on-premises, private-cloud, sovereigncloud and air-gapped environments. Announced on 1 October, the option is designed for organisations that need greater control over sensitive source code, regulated data and software development workflows.

OCTOBER 2026

IBM says enterprises can bring AI capabilities to infrastructure where their code and application context already reside, supporting data residency, security and governance requirements. Bob extends beyond code generation to support software delivery and application modernisation. Self-hosted deployment gives organisations another way to adopt those capabilities when security or compliance requirements restrict their

use of public AI services. Enterprises managing intellectual property, proprietary applications and regulated customer information often need to determine where AI operates, which information it can access and how its use is governed. Such requirements can complicate adoption across businesses operating in multiple jurisdictions. IBM’s Institute for Business Value highlighted those challenges in its June

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2026 report, The Calculus of AI Sovereignty. Among surveyed executives, 68% said meeting data residency and sovereignty requirements across geographies was challenging. Customers can run supported models on premises, including within air-gapped environments isolated from external networks, using models they have licensed. Hybrid configurations also allow Bob to connect to supported external model services, giving organisations

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deployment choices based on their operational and governance needs. “Organisations need AI that operates inside environments

Organisations need AI that operates inside environments they have control over, especially when working with sensitive code and regulated data.” Neel Sundaresan, General Manager of AI and Automation, IBM.

they have control over, especially when working with sensitive code and regulated data,” said Neel Sundaresan, General Manager of AI and Automation, IBM. “Bob’s self-hosted deployment provides a way for enterprises to bring agentic AI directly to those environments so they can benefit from the technology while maintaining security, compliance, and operational control.” Enterprise modernisation frequently involves applications and data distributed across onpremises systems, private clouds and other controlled environments. IBM says Bob’s deployment flexibility allows organisations to apply AI to development and modernisation across those environments, with support for different infrastructure and model configurations. Futurum Research projections cited by IBM suggest hybrid and edge deployments could account for 44% of the AI infrastructure market by 2030, while public cloud’s share could decline to 46%. IBM links that shift to demand for sovereign control alongside continued connectivity to wider technology ecosystems. Self-hosted deployment broadens Bob’s role for organisations seeking AIassisted software delivery while retaining control over the infrastructure, data and policies underpinning their development operations.

OCTOBER 2026

INDUSTRY RADAR

HP STUDY FINDS UAE WORKERS AHEAD IN AI ADOPTION AND WORKPLACE HEALTH Research finds 78% of UAE knowledge workers use AI daily or weekly, while demand for transferable skills and employer investment in development reflects changing career expectations.

HP’s Work Relationship Index 2026 has found that 45% of UAE knowledge workers report a healthy relationship with work, compared with 29% worldwide, alongside higher levels of AI adoption and a strong focus on developing transferable skills. Released on 1 October, the research includes dedicated UAE findings for the first time. Nearly four in five respondents in the country (78%) use AI at work daily or weekly, compared with 59% globally, while 57% use AI agents, against 43% worldwide. Career flexibility is also a priority. More than threequarters of UAE respondents (76%) prioritise transferable skills over a traditional career ladder, compared with 56% globally. More than half (54%) have an income-generating side venture, compared with 32% worldwide, rising to 61% among UAE Gen Z knowledge workers.

OCTOBER 2026

Stronger workplace health has not removed concerns about career change. Some 70% of UAE respondents say leaving their job currently feels too risky, while 67% believe they may need to significantly change or reinvent their career over the next few years. “Together, the findings reflect a workforce that is open to new ways of working and focused on building skills for the future,” said Peter Oganesean, Managing Director, Middle East and East Africa, HP. Growing AI use is accompanied by awareness of changing skills

Together, the findings reflect a workforce that is open to new ways of working and focused on building skills for the future.” Peter Oganesean, Managing Director, Middle East and East Africa, HP

requirements. Among UAE respondents who describe themselves as expert AI users, 85% believe they may need to significantly change their career, compared with 54% of basic users. Meanwhile, 51% of AI agent users worry their job could be replaced by someone with AI expertise, compared with 41% of those using generative AI alone. Employer training appears to be reaching agent users more effectively. Some 72% say their company’s AI training keeps pace with technological change, compared with 58% of those using generative AI alone. A quarter of UAE knowledge workers nevertheless describe their AI proficiency as novice or basic. Access to suitable technology is closely associated with workplace health. Among UAE respondents classified in HP’s Healthy WRI Zone, 92% say their company provides the tools needed to

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Peter Oganesean, Managing Director, Middle East and East Africa, HP.

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succeed, compared with 34% in its Critical Zone. Access to devices and accessories that work seamlessly together stands at 79% and 37%, respectively. Faster and more reliable devices lead UAE workers’ technology priorities at 57%, followed by tools that support learning and adaptation at 50%. Role-specific AI tools and technology supporting strategic thinking each rank at 40%, followed by tools for prioritising work at 38% and shared knowledge systems at 37%. Communication and development remain central to workforce confidence. Six in ten UAE respondents say their organisation clearly explains how AI and new technologies may affect roles, while 30% report discussions about potential effects on roles or headcount. Company investment in development makes 82% of Gen Z respondents, 87% of Millennials and 84% of Gen X feel more secure about the future. Around three-quarters of each generation also say access to upskilling makes them less anxious about AI’s impact on their role. HP conducted the research between 15 April and 20 May 2026. UAE results draw on 300 knowledge workers surveyed through its WRI Lite study and are benchmarked against 15,003 knowledge workers in the global WRI across 15 countries. HP classifies respondents’ relationship with work using a five-point self-reported happiness scale.

OCTOBER 2026

INDUSTRY RADAR

Nutanix

NUTANIX ACQUIRES RYAX TO IMPROVE AGENTIC AI INFRASTRUCTURE EFFICIENCY Planned integration with Nutanix Kubernetes Platform and Nutanix Enterprise AI will bring resource optimisation and workload scheduling to hybrid AI deployments.

Reshma Naik, Senior Director for Presales, Middle East and Africa, Nutanix.

OCTOBER 2026

Nutanix has acquired Francebased Ryax Technologies to strengthen its ability to manage agentic AI workloads across hybrid infrastructure, with plans to integrate resource optimisation and smart scheduling capabilities into its enterprise AI and Kubernetes platforms. Announced on 1 October, the acquisition brings an AIdriven compute orchestration and management platform into Nutanix’s portfolio. Integration is planned for future releases of Nutanix Kubernetes Platform (NKP) and Nutanix Enterprise AI (NAI). Growing demand for AI inference, where trained models generate responses or predictions, is increasing pressure on enterprise computing resources. Nutanix says GPU shortages and fragmented infrastructure have prompted organisations to distribute workloads across private data centres, hyperscale cloud providers and specialist cloud providers known as neoclouds. Managing those environments can add operational complexity

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APPOINTMENT INDUSTRY RADAR

and make it harder to use hardware efficiently. Moving AI projects from experimentation into production also frequently requires infrastructure integration and manual configuration, according to Nutanix. Ryax’s platform is designed to automate the coordination of infrastructure, data, hardware and code. Nutanix plans to use its capabilities to help customers deploy and manage AI workloads more efficiently across different environments. Resource optimisation is one focus of the acquisition. Ryax enables customers to make better use of available GPUs and CPUs, with the aim of improving performance and reducing unused capacity. AI-aware scheduling is another priority, allowing workloads to be placed automatically on suitable, cost-effective hardware to balance performance and budget requirements. “Agentic AI requires a flexible architecture, simple operations and the ability to use infrastructure far more efficiently,” said Rajiv Ramaswami, CEO, Nutanix. “Our acquisition of Ryax helps to directly answer the challenges enterprises face today with agentic AI infrastructure management.” Andry Razafinjatovo, CEO, Ryax Technologies, said the platform was built to handle technical complexity across private data centres, hyperscalers and neoclouds, enabling teams to deploy, scale and manage AI

OCTOBER 2026

workflows across hybrid infrastructure. Regional demand for production AI is also shaping the infrastructure opportunity. Reshma Naik, Senior Director for Presales,

Across the MEA region, organisations are moving quickly from AI experimentation to deploying intelligent, agentic AI at scale.” Reshma Naik, Senior Director for Presales, Middle East and Africa, Nutanix.

Middle East and Africa, Nutanix, said organisations across the region are seeking to scale AI while managing cost, performance and data sovereignty requirements. “Across the MEA region, organisations are moving quickly from AI experimentation to deploying intelligent, agentic AI at scale,” said Naik. Ryax’s team will join Nutanix in France and continue developing the technology. Nutanix said the acquisition’s financial impact was not material to the company.

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15TH OCTOBER 2026 The Westin Dubai Mina Seyahi Beach Resort & Marina

6:00 PM onwards #CISO50FSA2026

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CISO50 & Future Security Awards 2026 CISO50 & Future Security Awards 2026 will bring together the region’s cybersecurity community to recognise outstanding leadership, innovation and excellence in enterprise security. The event will celebrate influential 63 CISOs, high-performing security teams, pioneering technology providers and women making an impact in cybersecurity, while spotlighting the strategies shaping a more resilient digital future across the Middle East.

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For more information about the event and to be a part of the CISO50 & Future Security Awards 2026, please click the link below https://www.tahawultech.com/ciso50-fsa/2026/

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