CXO INSIGHT JANUARY 2026

www.cxoinsightme.com

16 TECHNICAL GLASS CEILING

Exploring what’s holding enterprise AI back

34 RESILIENCE AT SCALE

Veeam’s Anand Eswaran on redefining data resilience at enterprise scale

40 THINK BIG, START SMALL, SCALE FAST

AWS’s Tom Soderstrom highlights what successful innovation and execution at scale look like in the AI era

36 THE END OF THE EXPLOIT WINDOW

Qualys on how AI-powered attacks are challenging vulnerability management and defence strategies

44 FOUR STEPS TO QUANTUM-PROOF GCC ENTERPRISES

Gigamon shares priorities for quantum readiness and long-term data protection defence in 2026

50 The latest gears and gadgets to keep you ahead of the curve

THE TECH WORLD IN 2026

Industry leaders share insights and predictions on what lies ahead

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THE ROAD AHEAD

Every year we ask “What’s next?”—and every year the answer becomes a little less theoretical.

In the past, this question invited speculation about what to try, what to test, what to explore. As we move into 2026, it is about ownership and what leaders are willing to stand behind once technology becomes operational.

Across this issue, one theme is unmistakable – execution has replaced experimentation, and leadership has become the defining variable. As AI moves into core operations and digital systems carry real commercial and regulatory weight, the expectations placed on technology leaders have shifted. The role now requires judgement, accountability, and the ability to connect technology decisions directly to business outcomes.

What stands out is how consistently this view is shared across industries and sectors. The conversations are no longer about chasing models or expanding toolsets. They are about discipline. About governance. About building organisations that can scale technology without losing control. In many cases, they are also about knowing what to stop.

There is also a growing regional confidence running through these pages. The Middle East is no longer positioning itself as a fast follower. With national AI strategies, sovereign cloud mandates, and largescale infrastructure investments, the region is shaping how technology is deployed at scale and under real-world constraints.

This edition of CXO Insight Middle East reveals perspectives on how technology leadership itself is being redefined, and how it will be judged next.

The question remains the same. The stakes, clearly, do not.

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Jeddah Airports Company has launched “Airport View”, a new digital application for personnel at King Abdulaziz International Airport that centralises operations into one smart platform. The app offers real-time flight monitoring, instant alerts, performance dashboards and daily operational data to boost coordination, speed decision-making and improve service quality across the airport, enhancing overall travel experience and operational efficiency.

Bahrain earns top global GovTech ranking

Bahrain has been ranked second in the Middle East and 15th globally out of 197 countries on the World Bank’s 2025 GovTech Maturity Index, reflecting its strong progress in public-sector digitalisation and delivery of advanced e-government services.

Lenovo has named Tareq Alangari as Senior Vice President and President for its Middle East, Türkiye, and Africa (META) business, where he will lead regional operations from Lenovo’s headquarters in Riyadh. With more than 25 years of regional leadership experience, he joins from e& enterprise, where he most recently served as CEO for Saudi Arabia.

flydubai digitises turnaround operations across the network

flydubai has selected ZestIoT’s Turnaround Management Platform to digitise its aircraft turnaround operations at Dubai International Airport (DXB) and across its growing global network. The AI-driven system provides real-time visibility and predictive collaboration to enhance decision-making, improve operational execution and on-time departures, and elevate the passenger experience.

The global digital economy is on track to reach US$28 trillion in 2026, according to the Digital Cooperation Organisation (DCO), driven by accelerating investment in AI, data, cloud, and connectivity. Digital activity is expected to account for around 22 percent of global GDP, underscoring its growing economic weight.

Westcon-Comstor has appointed Renton D’Souza as Managing Director for the Gulf, tapping his 18-year leadership experience within the company to drive growth, expand market share and strengthen partner and vendor relationships across the region as the distributor accelerates its business momentum.

Saudi Arabia to build world’s largest government data centre

Saudi Arabia has launched the Hexagon Data Centre in Riyadh, which it describes as the world’s largest government data centre, marking a major milestone in the Kingdom’s national digital infrastructure strategy.

With a total capacity of 480 megawatts, the Tier IV-classified facility spans more than 30 million square

Bahrain partners with SandboxAQ to advance quantum-safe cybersecurity

feet and has been designed to support government operations, strategic sectors and the growing demand for data-driven services. The centre forms a cornerstone of Saudi Arabia’s efforts to strengthen data sovereignty and enable advanced digital capabilities in line with Vision 2030.

The project is led by the Saudi Data and AI Authority (SDAIA) and is intended to serve as the foundation for a broader national network of data centres. It incorporates energy-efficient technologies, including advanced cooling systems, and meets US Green Building Council LEED Gold standards, alongside international certifications such as TIA 942 and ISO/IEC 22237.

Dr Abdullah bin Sharaf Al-Ghamdi, President, SDAIA, said, “The Hexagon data centre will be followed by the establishment of other centres. This centre is a qualitative strategic boost toward making the Kingdom a global centre for data, ensuring data

National Cyber Security Centre of Bahrain has partnered with SandboxAQ to help build a quantum-safe economy, marking a significant step in the Kingdom’s long-term cybersecurity modernisation efforts.

The initiative aims to prepare Bahrain for emerging threats posed by cryptographically relevant quantum computers, including so-called “harvest-now, decrypt-later” attacks. As part of the agreement, Bahrain will deploy SandboxAQ’s AQtive Guard platform across more than 60 government ministry environments, providing visibility into cryptographic vulnerabilities and helping prioritise remediation as risks evolve.

The programme aligns with Bahrain’s broader national strategy to protect sovereign data,

US$2.67 billion

The projected cumulative economic value of Saudi Arabia’s national data centre strategy

sovereignty and security, and enabling innovation and a digital economy.”

According to SDAIA, the wider data centre strategy is expected to generate more than SAR 10 billion ($2.67 billion) in cumulative economic impact and deliver SAR 1.8 billion ($479.9 million) in annual savings, while supporting non-oil growth and improved digital services across the Kingdom.

critical infrastructure and digital services as advances in quantum computing and AI reshape the threat landscape.

His Excellency Shaikh Salman bin Mohammed Al Khalifa, CEO of Bahrain’s National Cyber Security Centre, said, “This partnership marks

a significant milestone in our mission to secure our sovereign data, intellectual property, and other digital assets from both internal and external cyber threats.”

SandboxAQ said the collaboration will support Bahrain’s efforts to stay ahead of future cyber risks as encryption standards evolve.

Abu Dhabi accelerates push towards AI-native government

Abu Dhabi’s Department of Government Enablement (DGE) has outlined a year of significant progress in 2025, marking a decisive step in the emirate’s ambition to become the world’s first AI-native government by 2027.

In January, DGE launched the Abu Dhabi Government Digital Strategy 2025–2027, backed by an AED 13 billion investment to fully digitise government operations, deploy more than 200 AI solutions, migrate services to sovereign cloud infrastructure and implement a unified ERP system. The programme is expected to contribute AED 24 billion to the economy and create more than 5,000 jobs.

“In Abu Dhabi, we are building the government of the future, where AI is intrinsic to its foundation. And in 2025, we proved how this isn’t a distant vision, it’s our daily reality and

1.9 million

The number of government service cases resolved through conversational AI

already changing the lives of millions,” said Ahmed Tamim Hisham Al Kuttab, Chairman of DGE.

A central pillar of this transformation is the TAMM super app, now serving 3.8 million users across more than 1,150 services in over 90 languages.

The platform resolves 95 per cent of requests through AI and has completed more than 1.9 million service cases using conversational AI. The launch of TAMM AutoGov, described as the world’s first AI public servant, marks a shift from reactive to anticipatory government services, automatically handling licence renewals, medical appointments and other recurring needs without users having to initiate requests.

“By eliminating over 36 million customer visits annually and resolving 90 per cent of requests within one day, we are creating a government that doesn’t just protect people’s time, it gives it back,” said Dr Mohamed Al Askar, Director General of TAMM.

Looking ahead, DGE plans to expand proactive AI-powered services and further strengthen sovereign digital infrastructure in 2026.

Amazon pledges US$35 billion AI investment in India

Amazon has announced plans to invest more than US$35 billion across its businesses in India by 2030, reinforcing its long-term commitment to the country’s digital economy and technology ecosystem.

The investment builds on nearly US$40 billion already invested in India over the past 15 years. Amazon said the next phase of spending will focus on AI-driven digitisation, export growth and job creation, supporting India’s ambitions to strengthen its digital infrastructure and global competitiveness.

Ooredoo and Darktrace partner to boost AIdriven enterprise cybersecurity in Qatar

du has achieved a UAE-first milestone with the successful deployment of 5G-Advanced technology on its live network, setting a new benchmark for performance and sustainability in next-generation connectivity.

The rollout positions du as the first operator in the UAE to implement 5G-Advanced, delivering enhanced network capacity, improved spectrum efficiency and ultra-low latency. The deployment includes advanced antenna technology designed to boost coverage while significantly reducing power consumption, supporting the operator’s sustainability objectives.

According to an economic impact assessment by Keystone Strategy cited by Amazon, the company’s cumulative investments have helped digitise more than 12 million small businesses, enabled US$20 billion in cumulative e-commerce exports, and supported around 2.8 million direct, indirect, induced and seasonal jobs in 2024.

“We are humbled to have been a part of India’s digital transformation journey over the past 15 years, with Amazon’s

We have invested at scale in growing the physical and digital infrastructure for small businesses in India, creating millions of jobs, and taking Made-inIndia global

growth in India perfectly aligned with the vision of an Atmanirbhar and Viksit Bharat,” says Amit Agarwal, Senior VP Emerging Markets, Amazon. “We have invested at scale in growing the physical and digital infrastructure for small businesses in India, creating millions of jobs, and taking Madein-India global.”

Amazon said its India operations are expected to support 3.8 million jobs by 2030, as it expands fulfilment, delivery and technology infrastructure.

The upgraded network is expected to enable new enterprise and consumer use cases, including massive IoT, smart city applications and mission-critical services, while strengthening the UAE’s leadership in advanced digital infrastructure.

Saleem AlBlooshi, Chief Technology Officer, du, said, “5G-Advanced is a monumental leap forward for du and

the UAE’s telecom sector. This milestone reflects our ongoing efforts to deliver worldclass connectivity and support the nation’s vision to be a global technology leader. It also reaffirms our focus on building a green, sustainable network for the future.”

The milestone reinforces du’s commitment to innovation as the UAE continues to scale next-generation digital services.

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du achieves UAE first with 5G-Advanced deployment

du has achieved a UAE-first milestone with the successful deployment of 5G-Advanced technology on its live network, setting a new benchmark for performance and sustainability in next-generation connectivity.

The rollout positions du as the first operator in the UAE to implement 5G-Advanced, delivering enhanced network capacity, improved spectrum efficiency and ultra-low latency. The deployment includes advanced antenna technology designed to boost coverage while significantly reducing power consumption, supporting the operator’s sustainability objectives.

The upgraded network is expected to enable new enterprise and

consumer use cases, including massive IoT, smart city applications and mission-critical services, while strengthening the UAE’s leadership in advanced digital infrastructure.

Saleem AlBlooshi, Chief Technology Officer, du, said, “5G-Advanced is a monumental leap forward for du and the UAE’s telecom sector. This milestone reflects our ongoing efforts to deliver world-class connectivity and support the nation’s vision to be a global technology leader. It also reaffirms our focus on building a green, sustainable network for the future.”

The milestone reinforces du’s commitment to innovation as the UAE continues to scale nextgeneration digital services.

Egypt targets production of 15 million mobile phones in 2026

Egypt is targeting the production of 15 million mobile phones in 2026, as part of a broader push to expand local manufacturing, support exports and strengthen the country’s ICT sector, according to Amr Talaat, the country’s Minister of Communications and Information Technology.

The MCIT minister said the target follows expected production of 10 million

devices in 2025, with locally manufactured phones reaching an average local valueadded component of around 40 percent.

He noted that 15 international mobile phone brands are currently manufacturing their devices in Egypt, reflecting growing confidence in the country’s electronics production capabilities.

The minister said part of the planned output would be directed towards

US$7.4 billion

The value of Egypt’s ICT exports in 2025

export markets, supporting Egypt’s broader industrial and trade objectives.

Talaat added that the mobile manufacturing push sits within the wider Digital Egypt strategy, which focuses on localising technology production, expanding digital exports and positioning Egypt as a regional ICT hub. ICT exports reached US$7.4 billion, with a target of US$9 billion, driven by growth in digital services and outsourcing.

He also highlighted Egypt’s strategic role in global connectivity, noting that 21 international subsea cables pass through the country, linking Asia and Europe.

“IN ABU DHABI, WE ARE BUILDING THE GOVERNMENT OF THE FUTURE, WHERE AI IS INTRINSIC TO ITS FOUNDATION”

His Excellency Ahmed Tamim Hisham Al Kuttab, Chairman of the Department of Government Enablement – Abu Dhabi

“MICROSOFT HAS BEEN PART OF INDIA’S FABRIC FOR MORE THAN THREE DECADES. AS THE NATION MOVES CONFIDENTLY INTO ITS AI-FIRST FUTURE, WE ARE PROUD TO STAND AS A TRUSTED PARTNER IN ADVANCING THE INFRASTRUCTURE, INNOVATION AND OPPORTUNITY THAT CAN POWER A BILLION DREAMS”

TECHNICAL GLASS CEILING:

WHAT’S HOLDING ENTERPRISE AI BACK

Application modernisation is now the strongest predictor of whether AI investment delivers value or quietly drains budgets. Organisations that fail to update their application foundations are not holding position; they are losing ground as competitors accelerate.

That conclusion sits at the heart of the Cloudflare 2026 App Innovation Report, which surveyed 2,351 senior leaders across NAMER, EMEA and APAC, all from organisations with more than 1,000 employees and direct influence over infrastructure decisions. The findings draw a clear line between companies modernising their application stacks and those constrained by technical debt.

The strongest signal is the relationship between modern infrastructure and AI outcomes. Organisations that have modernised their applications are three times more likely to see a clear return on investment from AI initiatives. This is reinforced by near-unanimous agreement at leadership level: 93 percent of respondents said that updating software was the single most important factor in improving their organisation’s AI capabilities. The report places the condition of applications and infrastructure ahead of model choice or experimentation in determining success.

AI strategy itself is also evolving, and the numbers underline that shift. The emphasis is no longer on initial deployment but on embedding AI into core systems. Ninety-one percent of organisations identified as leaders have already integrated AI into their existing application portfolios, while 74 percent plan to deepen those integrations over the next year. AI is being operationalised inside business-critical workflows, rather than run as isolated pilots.

Security outcomes follow the same pattern. According to the report, organisations that align security programmes with application modernisation are four times more likely to reach advanced levels of AI maturity. The contrast with lagging organisations is sharp. Those delaying modernisation report 85 percent lower confidence in their infrastructure and are far more likely to upgrade only after experiencing a security incident, locking themselves into reactive decision-making.

The share of leaders who say modern software is essential to improving AI capability

The increase in likelihood of reaching AI maturity when aligning security with application modernisation

Matthew Prince, CEO and co-founder of Cloudflare, described a modern and secure foundation as “non-negotiable” for AI success. “If you aren’t modernising your business to embrace AI and prevent the next wave of cyber-attacks, you aren’t just standing still, you’re rapidly falling behind. The winners of this era of the Internet will ultimately be defined by their infrastructure.”

Operational complexity is another pressure point quantified in the report. Ninety-six percent of respondents said they struggle with overly complex technology stacks. Leading organisations, however, are responding with consolidation rather than further expansion. Eighty-five percent are actively cutting redundant tools and addressing shadow IT to simplify environments and move faster.

Taken together, the statistics position application modernisation as a business-critical decision rather than an IT housekeeping exercise. The data suggests that legacy infrastructure now carries a measurable cost across AI performance, security confidence and execution speed. For enterprises competing in an AI-driven market, that cost is becoming harder to absorb.

93% 4x 96%

The proportion of organisations held back by complex, fragmented tech stacks

WHAT’S NEXT?

As experimentation gives way to execution, industry leaders share what will matter most as technology leadership sharpens its focus on accountability, value, and measurable outcomes

Words by Adelle Geronimo

ANKABUT

The shift from tech to business leadership

As AI becomes embedded in core enterprise operations, technology leadership is entering a fundamentally different phase—one defined less by systems delivery and more by strategic influence. By 2026, the ability to connect technology decisions directly to commercial outcomes will define effective leadership.

Ankabut expects AI and digital leaders to move decisively beyond traditional technical roles. “AI and digital leaders will need to evolve from primarily technical experts into fully rounded business leaders,” says Adli Dehelia, Executive Director for Service Development, Ankabut. He notes the advantage of combining fluency in commercial strategy, finance, and portfolio management with deep industry understanding. Their influence will extend across the organisation, from educating boards on AI and digital topics to shaping enterprise-wide priorities and acting as strategic partners to CEOs.

Enterprise delivery models will shift in parallel. Projectbased thinking will give way to platform- and product-

AI and digital leaders will need to evolve from primarily technical experts into fully rounded business leaders

centric approaches, enabling faster execution and clearer links between technology investment and revenue growth. Organisations will scale back large application modernisation programmes in favour of building robust, governed data platforms that enable AI at scale, while outsourcing non-differentiating IT services.

Security leadership will also evolve. “Security leaders will function as growth facilitators, not just risk managers,” says Dehelia. He highlights the value of embedding secureby-design principles into products, data platforms, and AI solutions, and using risk analytics to inform market expansion and ecosystem participation.

According to Dehelia, the Middle East will play a defining role in 2026, driven by large-scale investments in AI, cloud, and data-centre infrastructure, early adoption of 5G and edge computing, and governments acting as digital orchestrators. The region will also attract global talent, develop local skills, and serve as a regulated test bed for emerging technologies—positioning it as a leading innovation hub in the global technology ecosystem.

ASUS

AI, security, and sustainability become business fundamentals

As enterprises prepare for 2026, ASUS sees a decisive shift from technology experimentation to real-world implementation, as organisations focus on scaling digital maturity and measurable impact. Cybersecurity, cloud infrastructure, sustainability, and artificial intelligence are no longer optional initiatives but core to business growth and competitiveness.

Devices that can handle demanding AI workloads while maintaining efficiency, security, and dependability are needed now more than ever as they play a major role in making daily processes smoother

AI adoption is expected to accelerate through agentic AI, edge AI hardware, and Arabic-optimised AI models, driving more intelligent, automated workflows across enterprises. This evolution places new demands on enterprise devices, which must support intensive AI workloads while remaining efficient, secure, and dependable. Tolga Özdil, Regional Commercial Director, Middle East, Turkey & Africa, ASUS, explains, “Devices that can handle demanding AI workloads while maintaining efficiency, security, and dependability are needed now more than ever as they play a major role in making daily processes smoother.”

Sustainability is also emerging as a defining priority for 2026. With governments and enterprises pushing for responsible consumption and carbon reduction, ASUS is embedding energy efficiency, repairability, and recyclability into its product strategy to help organisations align IT investments with environmental goals.

Looking ahead, ASUS anticipates a more sector-specific technology approach, supported by customised security, manageability, and deployment frameworks for industries such as healthcare, BFSI, and hospitality. According to Özdil, “We aim to assist Middle Eastern businesses in leveraging intelligence at scale and confidently advancing into 2026.”

AVEVA

AI moves up the decision chain

This year, generative AI will no longer be treated as an experimental capability but as a core driver of measurable business value across industrial enterprises, according to Jim Chappell, Global Head of AI and Advanced Analytics at AVEVA.

Chappell notes that organisations are already shifting their focus from proof-of-concepts to performance, as spending on large language models more than doubled in the first half of 2025.

GenAI is increasingly embedded into platforms, workflows, and products, delivering productivity gains of up to 30 percent when integrated effectively. The next phase, Chappell argues, lies in task-specific AI agents that address defined operational pain points with clear ROI metrics, moving the question from “does it work?” to “how does it deliver value?”

AVEVA also expects composite AI to become central to industrial outcomes, combining LLMs with

Strategic AI will depend on unified data, seamless interaction across the ecosystem, and conscious cultural change

predictive, vision, and time-series models through open standards. “Value will come from building the right stack, for example, outlier detection for constraint checking, predictive models to drive performance and Gen AI for natural language queries,” says Chappell.

Beyond 2026, AI’s role is set to move up the decision chain. As industrial data becomes unified across ecosystems, executives will increasingly rely on AI to model scenarios, optimise operations, and compress decision cycles. “Strategic AI will depend on unified data, seamless interaction across the ecosystem, and conscious cultural change,” Chappell says.

DXC TECHNOLOGY

New benchmarks for tech leadership

DXC Technology believes that by 2026, the role of technology leadership will shift decisively from deploying tools to reshaping organisations around artificial intelligence. As AI and digital systems move deeper into core operations, the company argues that the real constraints on progress are no longer technical, but organisational.

According to Thys Bruwer, Consulting, Data & Analytics Leader for Middle East & Africa at DXC Technology, many organisations are still approaching

AI with outdated assumptions. “This year, technology leaders will be judged far less on what they deploy and far more on how they reshape the organisation around it,” he says. “What we’ve seen over the last year is that most AI roadblocks haven’t been technical, rather they’ve been cultural and structural.”

DXC expects AI to move firmly into regulated, highimpact domains such as R&D, compliance, and ESG reporting by 2026, requiring leadership models that extend beyond IT. In this environment, technology leaders must act as orchestrators, aligning business, data, and technology teams to scale AI responsibly.

The company also predicts a strong shift towards private AI models as concerns around data sovereignty, governance, and intellectual property intensify. Bruwer adds: “The winners in 2026 will be those that invest

This year, technology leaders will be judged far less on what they deploy and far more on how they reshape the organisation around it

selectively, with trusted partners, and align AI initiatives tightly to measurable business outcomes.”

In parallel, DXC sees cybersecurity leadership evolving into a strategic, board-level discipline—where risk, cost, and return are discussed as core business decisions rather than technical afterthoughts.

ENDAVA

Accountability as a new differentiator in AI leadership

As AI moves deeper into core business operations, Endava expects 2026 to mark a clear turning point in technology leadership. According to David Boast, leadership is shifting away from ownership of technology stacks towards ownership of outcomes— defined in business value, responsibility, and long-term impact.

“Technology leadership is already evolving, not simply owning tech stacks but owning outcomes, and doing so responsibly,” Boast says. As digital initiatives grow more complex, responsibility for outcomes increasingly extends beyond IT teams to business leaders and technology partners, supported by shared-risk delivery models aligned around performance rather than project completion.

For Boast, 2026 introduces a second, non-negotiable mandate: trust. “Ethical AI is no longer a policy footnote, it’s a leadership competency,” he says, underscoring the growing scrutiny around AI-driven decisions.

He adds: “That competency demands clear accountability, transparent decision pathways, humanin-the-loop controls for high-impact decisions, and the ability to explain outcomes to customers, regulators, and boards.”

With expectations of ROI rising across every dirham, riyal, and dollar spent, Boast notes that ambition still exceeds performance in many organisations. From his perspective, the organisations that succeed will be those that define value clearly, build governance to sustain it, and prepare the whole business—not just IT—for AI-driven change. The remaining question, he suggests, is not whether outcomes will materialise, but how quickly and how far they will reach.

Outcomes over hype

This year points to a decisive shift in how enterprises will deploy and scale technology, according to Salman Kazmi, Area Vice President, META, BMC Helix. From his perspective, the focus is moving away from fragmented experimentation towards platforms that deliver measurable, enterprise-wide outcomes. Technologies such as agentic AI, AIOps, and smart service orchestration will be central to this shift, enabling organisations to connect data, operations, and automation across the enterprise.

For Kazmi, discipline will matter as much as innovation. Organisations should utilise platforms that integrate data, operations, and automation across various areas. “At the same time, businesses need to reduce the use of disjointed tools and experimental AI projects that do not have defined business results or quantifiable ROI.” In 2026, he expects technology investment decisions to be increasingly shaped by operational impact rather than experimentation alone.

Ethical AI is no longer a policy footnote, it’s a leadership competency

He also sees cybersecurity taking on a more influential role in business strategy. “By 2026, security leaders will transform into strategic advisors who facilitate growth by measuring risk in business language,” says Kazmi. “Security will transform into a growth enabler rather than a limitation, particularly in regulated industries.”

Businesses

need to reduce the use of disjointed tools and experimental AI projects that do not have defined business results or quantifiable ROI

Looking ahead, Kazmi believes the Middle East will play a defining role in this evolution. He sees the region moving from technology adoption to large-scale implementation, driven by national digital initiatives and AI-centric strategies, and setting expectations for scalable, results-oriented digital transformation.

INFORMATICA

A year defined by disciplined AI, not novelty As organisations look ahead to 2026, Informatica expects the conversation around artificial intelligence to shift away from speed and scale, and towards

discipline and trust. After a year dominated by experimentation, many organisations are recognising that excitement alone does not guarantee outcomes.

For Informatica, the next phase of AI adoption will be shaped by confidence in data — understanding what data can be trusted, where it comes from, and how it should be used. Disconnected AI pilots that struggle to reach production are likely to be scaled back, replaced by fewer initiatives that are closely tied to real business processes.

“The winners won’t be those chasing every new model release, but those building confidence that AI can be relied on day after day, not just in demos,” says Levent Ergin, Chief Strategist for Climate, Sustainability and AI, and Global Head of ESG Strategic Alliance Partnerships at Informatica.

The winners won’t be those chasing every new model release, but those building confidence that AI can be relied on day after day, not just in demos

Ergin also sees the Middle East playing a distinct strategic role in the global technology landscape, driven by nationally aligned approaches to data, AI, and digital infrastructure. These shared foundations make it easier to build cohesive data ecosystems and future-proof innovation.

Looking to 2026, Ergin believes technology leadership must evolve as AI moves deeper into core operations. With algorithms influencing customers, employees, and financial outcomes, he argues that risk, compliance, and accountability must be designed in from the outset — and that data strategy will increasingly define what AI can, and cannot, responsibly deliver.

JAGGAER

The shift to pragmatic AI

After an extended period of experimentation, Informatica sees 2026 as a year of reckoning for enterprise AI. As Gopinath Polavarapu, CDAO at JAGGAER, explains, “After a year or more of

After a year or more of experiments, pilots and proofsof-concept, most companies are finally acknowledging that they aren’t as ready as they thought

experiments, pilots and proofs-of-concept, most companies are finally acknowledging that they aren’t as ready as they thought.” Organisations are confronting the reality that AI cannot deliver transformation when the data foundation is fragmented or outdated. As he puts it, “They’re realising that AI can’t transform anything if the data underneath it is messy, siloed or outdated, and that the impressive demos don’t mean much when they meet real-world processes.”

That realisation is driving the rise of sector-native intelligence. “The days of trying to stretch one big, generic model across every problem are nearing an end,” Polavarapu says. In practice, domain-specific models built for areas such as financial compliance or clinical records consistently outperform generalpurpose alternatives because they reflect the language and constraints of the domain.

He also points to the emergence of Physical AI, where robots become intelligent endpoints operating across cloud, edge and sovereign environments.

“It’s not science fiction anymore; it’s simply the next hardware layer in the same way smartphones once were.”

Finally, Polavarapu urges caution around the growing hype cycle. “It sounds impressive, but for now it’s more aspiration than reality,” he says of full agentic orchestration, noting that task-specific agents work today, while large-scale autonomous coordination still requires further refinement.

LOGITECH

Technology decisions move beyond IT

As organisations embed AI and digital systems deeper into day-to-day operations, Logitech believes technology leadership will undergo a fundamental shift by 2026 — moving decisively beyond infrastructure management into a broader, more strategic role.

According to Murad Ali, Head of GCC at Logitech for Business, technology leaders will increasingly be judged not just on uptime and deployment, but on governance, employee experience, and long-term sustainability. As AI becomes embedded into everyday

Leaders

need to govern how AI will be embedded into daily operations to ensure that data is used responsibly

workflows, leadership accountability will expand to include trust, security, privacy, and ethical use. “Leaders need to govern how AI will be embedded into daily operations to ensure that data is used responsibly,” Ali says.

This shift is also changing how technology decisions are made. Ali notes that buying decisions are no longer confined to IT alone, but are now shaped collectively by HR, facilities, real estate, and sustainability teams. With hybrid work now firmly established, organisations must focus on delivering equitable experiences regardless of location — a challenge that places employee wellbeing and productivity at the centre of technology strategy. Looking ahead to 2026, Ali sees AI working quietly in the background, improving productivity without adding complexity, while organisations double down

on scalable, interoperable platforms and scale back fragmented, single-purpose tools. From his perspective, the leaders who succeed will be those who treat workplace technology as a long-term business enabler — one that balances performance, sustainability, and human experience.

OPSWAT

Cybersecurity’s next pressure point Cybercriminals are becoming more calculated in where and how they strike, according to Hussam Sidani, Vice President for the Middle East and North Africa at OPSWAT. He notes how attackers are increasingly shifting their focus to critical infrastructure sectors

Cybersecurity can no longer be framed as a purely technical challenge

operating on razor-thin margins, including healthcare, water services, and regional energy providers.

These organisations often face a difficult reality. Long funding cycles and ageing operational technology mean they rarely have the flexibility to modernise infrastructure and strengthen cybersecurity at the same time. For attackers, this creates high-impact opportunities, particularly where downtime is not an option and service disruption carries serious consequences.

Sidani warns that supply chain exposure will further intensify these risks. As organisations rely more heavily on external specialists and remote technicians, trust relationships outside direct control are becoming prime attack vectors. “Cybersecurity can no longer be framed as a purely technical challenge,” he notes, pointing to the growing importance of mindset, culture, and consistent processes alongside tools.

The excitement of 2025 was tempered by hard truths, forcing leaders to think more critically not only about how they adopt transformative technology, but why

Looking ahead, Sidani believes the organisations that succeed will be those willing to question longheld assumptions and confront complacency. From his perspective, “The future of cybersecurity won’t be built on innovative products alone. It will be built on people who think differently, regulators who enforce meaningfully, and leaders who recognise that trust must be tested and continuously verified.”

PURE STORAGE

A time for purpose-built progress

This year will mark a decisive shift in how organisations approach technology—away from experimentation and towards pragmatic, purpose-built execution, according to Fred Lherault, CTO EMEA and Emerging Markets at Pure Storage. After the enthusiasm of 2025, leaders are being confronted by hard realities, including MIT’s widely cited finding that 95 percent of AI projects never progress beyond the pilot stage. Reflecting on this turning point, Lherault says, “The excitement of 2025 was tempered by hard truths, forcing leaders to think more critically not only about how they adopt transformative technology, but why.

This more disciplined mindset is reshaping multiple domains. In cyber resilience, Lherault believes the long-held assumption that a single vendor can secure an entire enterprise is no longer viable. The scale and frequency of attacks now require interconnected frameworks that can identify, halt, and recover from incidents quickly, rather than relying on isolated point solutions.

Energy will also emerge as a defining constraint in 2026, influencing both data centre architecture and location decisions. Lherault argues that the industry must rethink how efficiency is measured, stating that “Terabytes per Watt (TBe/W) should become a standard metric, offering a simple, vendor-neutral, and accurate benchmark that reflects real-world energy use.”

SANDBOXAQ

The next phase for enterprise AI

There will be a clear move away from broad, languageonly AI experimentation toward technologies that are directly tied to value creation. While many organisations have pursued cost savings through large language models, he notes that outcomes have often been mixed. The next phase, will be defined by AI that can tackle harder, domain-specific problems and unlock new products and discoveries, according to Stefan Leichenauer, VP Engineering at SandboxAQ.

“The big story in 2026 won’t just be ‘AI’ in general, but AI that’s tightly coupled to value creation by solving real, hard problems,” he says. He points

Leichenauer points to large quantitative models working with domain-native data across areas such as cybersecurity, finance, materials science, and biopharma as the technologies most likely to deliver breakthroughs. At the same time, he believes organisations should begin scaling back languagemodel-only initiatives, including chatbots and LLM pilots that struggle to justify themselves.

Leichenauer also expects security leadership to become inseparable from growth strategy as AI adoption accelerates. As cyber risk increasingly overlaps with revenue, regulation, and reputation, security leaders will need to enable safe, fast innovation rather than simply block risk.

From his perspective, the Middle East will play a defining role in this transition. “The strength of the Middle East is its ability to quickly move beyond the pilot stage into real, live environments at the national level,” he says, positioning the region as both a scale market and a global reference point for responsible deployment in 2026.

SENTINELONE

Security leaders become growth architects

The big story in 2026 won’t just be ‘AI’ in general, but AI that’s tightly coupled to value creation by solving real, hard problems

As AI and digital systems move deeper into core operations, technology leadership will undergo a decisive shift by 2026. According to SentinelOne, the next phase of enterprise technology will place CIOs and CISOs at the centre of value creation and risk management, rather than system administration.

Looking ahead, he expects accelerated adoption of KubeVirt as organisations seek alternatives to traditional virtualisation platforms, alongside increased cloud repatriation driven by AI and data sovereignty concerns. Taken together, Lherault sees 2026 as a year when organisations move decisively from experimentation to action, building infrastructure that is resilient, efficient, and strategically confident.

Security now becomes a competitive advantage rather than a barrier to innovation

Meriam ElOuazzani, Regional Senior Director for the Middle East, Turkey, and Africa at SentinelOne sees technology leaders evolving into strategic stewards with direct responsibility for how AI is governed, secured, and applied across the business. “Technology leader roles will shift from system operators to strategic risk and value stewards.” In this model, leadership extends beyond IT performance to protecting the organisation from disruption while enabling innovation that is safe, controlled, and commercially sound.

Agentic AI will be a defining force in 2026, shaping both operations and security. ElOuazzani emphasises the need for discipline as organisations scale AI, cautioning against uncontrolled initiatives that lack accountability. “Security now becomes a competitive advantage rather than a barrier to innovation.” When AI is deployed with clear ownership and strong protections around data, models, and prompts, it can enhance resilience rather than introduce risk.

From her perspective, the Middle East is positioned to play a pivotal global role. With strong government mandates around sovereign cloud and regulated innovation, the region will help define how advanced technologies can be deployed securely and responsibly at scale.

SOPHOS

Accountability will define cybersecurity In 2026, the cybersecurity landscape will be shaped by a convergence of regulatory pressure, AI-driven threat acceleration, and rising expectations around accountability—particularly across the mid-market, according to Sophos.

MDR services will be forced to prove—not just claim—that humans are still in the loop

One of the most significant shifts, Sophos predicts, will be the extension of regulatory scrutiny beyond large enterprises. Mid-sized organisations will be held to measurable, ongoing standards across identity protection, monitoring, incident response, and AI governance. Compliance will no longer be an annual exercise, but a continuous operational responsibility. As Rob Harrison, SVP of Product Management at Sophos, says, “Managed Detection and Response (MDR) services will be forced to prove—not just claim—that humans are still in the loop.”

Harrison expects many organisations to struggle with these demands due to limited internal expertise, driving greater reliance on external partners for regulatory readiness, executive reporting, and safe AI adoption.

AI, in his view, will become foundational to cybersecurity operations—but not as a replacement for human judgement. As AI-driven detection becomes table stakes, buyers will demand transparency around who is monitoring their environments and where decisions are made. “The strongest MDR providers will be those that use AI to augment analysts, accelerating investigation, prioritisation, and response, rather than replacing them. MDR will differentiate on accountable outcomes, not autonomous claims,” he says.

SUBMER

The future of infrastructure is speed

As organisations look towards 2026, Khalid Aljamed, General Manager for the Middle East, Turkey & Africa at Submer, believes infrastructure strategy will define how quickly AI, digital economies, and national ambitions can move from vision to execution.

At the centre of this shift is what Aljamed describes as the move to “Instant-On” infrastructure, driven by modular, standardised architectures that can be deployed in weeks rather than years. This approach, he argues, fundamentally changes the pace of innovation. “This ‘plug-and-play’ approach significantly slashes Time-to-Market, allowing AI projects to move from conception to computation in record time,” says Aljamed.

He is equally clear on what organisations should leave behind. According to Aljamed, “The era of the ‘custom-built’ data centre is fading.” Bespoke construction models, he warns, expose organisations to supply chain delays, labour shortages, and extended

build cycles that put revenue creation and national timelines at risk.

Security and geopolitics are also becoming inseparable from infrastructure decisions. In 2026, Aljamed sees speed of deployment as a strategic advantage, stating that “the ability to deploy secure, sovereign infrastructure quickly is a major Geopolitical Advantage.” Rapid, modular infrastructure allows regions to create immediate “Safe Harbors” for data without slowing economic momentum.

The era of the ‘custom-built’ data centre is fading

From Aljamed’s perspective, this shift also redefines technology leadership. “By 2026, the primary metric for technology leadership has shifted from ‘System Reliability’ to ‘Velocity of Deployment,’” he says, arguing that leaders must now adopt a “Day Zero” mentality—one that aligns infrastructure execution with the speed of the Middle East’s economic and industrial transformation.

RESILIENCE AT SCALE

Anand Eswaran, CEO, Veeam Software, discusses how unifying visibility, governance, and recovery is redefining data resilience at enterprise scale

For years, data resilience lived quietly in the background of enterprise IT. Backup, recovery, and continuity mattered, but they were operational safeguards rather than strategic enablers. AI has changed that equation.

As organisations deploy machine learning models, generative systems, and autonomous agents into core workflows, data is no longer static. It is accessed continuously, reused across contexts, and acted upon at machine speed. In this environment, resilience is no longer about whether data can be recovered. It is about whether it can be

trusted, governed, and reversed when something goes wrong.

This is the backdrop against which Veeam Software completed its $1.725 billion acquisition of Securiti AI. The deal signals a shift in how Veeam defines its platform — from a recovery engine to a unified data platform designed to see, secure, govern, and recover data at AI speed.

“Veeam’s focus has always been data resilience,” says Anand Eswaran, CEO of Veeam. “Over the last two or three years, AI has fundamentally changed how organisations need to

think about the data lifecycle.”

This is what gives the acquisition its significance. Eswaran argues that AI has exposed the limits of managing data through separate systems for visibility, security, governance, and recovery.

“The only way to address the high failure rate of AI projects is to unify visibility, security, privacy compliance, governance, and resilience into a unified platform,” he says. Bringing Securiti AI into Veeam enables that unification at the platform level, extending Veeam’s data resilience

focus upstream into data security, governance, and trust — long before recovery is ever required.

Fragmentation is the real risk

Over time, the enterprise data stack evolved, but in fragments. Discovery, access control, compliance, and recovery were handled by separate tools. Each addressed a narrow problem, but none were built to operate as a single system.

“Historically, companies relied on different platforms and tools for visibility and intelligence to understand their data, separate tools to secure data and apply the right controls, and different tools again for resilience,” Eswaran says.

AI exposes the limits of this separation. Models and agents access data continuously, often without direct human oversight. If organisations cannot see where sensitive data resides, how it is classified, or who and what is accessing it, they cannot control risk.

This is where Securiti AI’s Data Security Posture Management (DSPM) capability becomes foundational to the Veeam platform. Rather than operating as a standalone discovery or compliance layer, it is integrated directly into Veeam’s data plane.

In practical terms, this allows Veeam to continuously discover, classify, and contextualise data across structured and unstructured sources — production systems, backups, and AI pipelines — within the same platform that protects and recovers

it. Data security posture is no longer assessed periodically or in isolation. It becomes a real-time input into how data is governed, accessed, and recovered.

“There is no AI without trusted data, and there is no trust in AI without data security and data resilience,” Eswaran says.

For customers, this changes how resilience is applied. Instead of treating backup and recovery as a last line of defence, organisations can identify risk before data is ever consumed by an AI system. Sensitive data can be classified early, policies enforced automatically, and access constrained dynamically — reducing the likelihood that AI systems are trained on data they should never have seen.

Rethinking resilience in the AI era

By integrating Securiti AI with the Veeam platform, resilience becomes both preventative and corrective.

“With Veeam and Securiti combined into a unified platform, customers gain deep, end-to-end visibility into their data,” Eswaran says. “They can understand every aspect of their data — who is accessing it, which agents are touching it, and which data is being used to train which models.”

That visibility feeds directly into enforcement. Changes in sensitivity, access patterns, and risk exposure can be acted on dynamically, rather than through manual review cycles.

The integration also tightens the link between governance and recovery. Because the platform understands data lineage and classification, recovery actions can be precise. Organisations can restore clean, compliant versions of datasets, models, or embeddings, rather than rolling back entire systems blindly.

Resilience now extends beyond data itself into AI behaviour.

Integrated data context gives organisations the ability to undo those decisions safely.

Compliance is another area where integration matters. Data privacy and sovereignty regulations vary by country and industry, and manual interpretation is increasingly impractical.

“We have a dedicated team of legal experts who translate these regulations into product logic,” Eswaran says. “These requirements are codified directly into the platform.” Those requirements are enforced continuously, with violations flagged immediately so organisations can respond before exposure escalates. The same applies after incidents. With ransomware now a routine threat, organisations must manage both recovery and regulatory response.

“Our unified platform helps establish the right security posture upfront,” Eswaran says. “But if a breach occurs, it also supports incident response and post-incident compliance obligations.”

The inflection point

According to Eswaran, the current landscape reveals a convergence of three challenges that organisations can no longer treat in isolation.

The first is visibility. “You cannot govern what you cannot see,” he says, pointing to the dominance of unstructured data and the lack of understanding around where data resides, how it moves, and who is accessing it.

The second is trust. “AI projects fail not because of models or GPUs, but because they are fed untrusted and poorly governed data.”

The third is resilience. “It is not just enough to recover your data,” Eswaran says. “You need to have a position on the ability to go back in time if an agent went wrong, if a model went wrong.”

There is no AI without trusted data, and there is no trust in AI without data security and data resilience

“If an AI agent behaves incorrectly, they can roll that agent back to a safe state,” Eswaran says. “If a model becomes poisoned, they can restore it to a trusted version.”

In AI-driven environments, failure is not limited to corrupted files. It includes corrupted decisions.

He notes that visibility, trust, and resilience can no longer be addressed through disconnected tools or teams. “The only way to address these challenges is through a unified platform that brings together visibility, security and trust, and resilience,” he says. “Understanding your posture across all three dimensions is the only way to enable safe AI at scale.”

THE END OF THE EXPLOIT WINDOW

By Saeed Abbasi, Senior Manager, Security Research, Qualys Threat Research Unit (TRU)

CISOs and software vendors have spent decades in a familiar cycle. While vulnerabilities lurked within technology stacks, industry professionals at least had a window in which to act – the time between the disclosure of a vulnerability and the first instance of its exploitation. That provided a fighting chance to those writing and applying patches – a fighting chance in the race with the would-be attackers who were weaponizing code.

A recent incident brought this era to a close.

A report from Anthropic showed the GTG-1002 campaign was not just business as usual. It is a watershed

Technical debt is no longer a line item; it is an open invitation to attackers

moment in offensive cyber operations. A Chinese statesponsored group leveraged Anthropic AI’s LLM suite, Claude, to autonomously execute 80 to 90 percent of the attack lifecycle. For the agent, there was no need to invent exotic zero-days. It

simply orchestrated open-source tools and exploited known bugs at machine speeds. It automated the reconnaissance, writing of exploit code, lateral movement, and exfiltration. The leveraging of AI in the GTG-1002 campaign compressed weeks of tradecraft into seconds. Defenders everywhere must now confront a brutal truth: the exploit window has collapsed to zero. We should now equate “vulnerable” with “hacked”.

The shadow assailant

GTG-1002 targeted organisations in finance, chemical manufacturing, and government, peaking at thousands of requests per second. But here is the scariest part: this was the “noisy” version. Attackers used a monitored commercial API.

The real danger we now face is the prospect of future campaigns that leverage an uncensored, opensource LLM running on private, local infrastructure – without API logs, vendor safeguards, or prospect of traceability. This technology democratises elite cyber warfare capabilities that once required vast teams and budgets but now only require GPU instances. A sole threat actor can now launch sophisticated, multifaceted campaigns at scale.

So, traditional detect-and-respond playbooks are now defunct. Wait to patch until a maintenance window and you have already lost. An AI agent can probe, breach, and pivot across your network before your SOC even receives the first alert.

The new playbook

Reactive defense will not serve CISOs in an AI-accelerated threat landscape. Here are the three crucial mandates for today’s security teams:

1 Tame the attack surface

Technical debt is no longer a line item; it is an open invitation to attackers. End-of-life systems are now guaranteed compromises, so CISOs must automate their patching pipelines and ruthlessly prioritise vulnerabilities based on real-time risk and threat intelligence. If patching is impossible or impractical, isolate the asset. There

is no middle ground. Anything less cedes control to the adversary.

2

Zero trust first

Corporate perimeters have become too porous to be relied on for protection. GTG-1002 enjoyed unchecked lateral movement. Your network must be hostile to unauthorised travel. Implement rigorous micro-segmentation, identity-based access controls, and continuous verification. Do not wait. Audit your architecture today. How many flat segments expose your crown jewels to a single foothold?

3 Machine vs. machine

Human agents are not equipped to fight algorithms. The only defense against a machine-speed attack is a machine-speed response. Human operators must supervise rather than participate in real-time defense. We must leverage AI for that defense by adopting continuous, autonomous exposure validation and AI-driven remediation that can identify and close gaps before an attacker’s agent finds them.

A breather

Despite the sophistication of autonomous threats, current technology comes with operational limits. AI hallucination remains a major constraint, where adversaries’ agents falsely report access or invent nonexistent packages, forcing attackers to build complex verification layers that slow the kill chain.

Benchmarks like SWE-bench reveal that fully autonomous execution on novel tasks still only achieves around 30 percent success and hardware limitations on context windows hinder long-term campaign coherence. This inconsistency gives defenders an advantage, albeit a fleeting one, as this friction will not be a safety net for long.

The forgiving Internet belongs to a bygone era before the AI arms race. GTG-1002 has shown us how quickly AI can act and that CISOs must now reassess their posture and allocate resources to automation if they are to lead their organisation into a resilient future.

THE RISE OF ‘READY-TO-WORK’ AI AGENTS

By William O’Neill, Area VP – GCC, ServiceNow

After an extraordinary period of test and learn, enterprises are now asking tougher questions – it isn’t if AI can transform work, but now how to make it actually usable. For too long, employees have been forced to navigate fragmented systems and siloed applications.

Even the most advanced AI projects can falter when they’re bolted onto legacy infrastructure or hidden behind outdated interfaces. Gartner predicts that through this year, 60 percent of AI projects will fail due to a lack of AI-ready data which is often the result of this very fragmentation.

The Gartner statistic tells an important story marking a bigger shift in the enterprise landscape. The race for algorithmic sophistication is giving way to something deeper which is the recognition that the real power of AI lies in how it transforms everyday experiences. The future of enterprise technology will be defined by this evolution where AI becomes the interface through which work gets done and value is created. Instead of forcing users to jump between dashboards, apps, and portals, enterprises need an intelligent front door to work. This is where the rise of agentic AI and a unified interface, the AI experience, come together.

Imagine a workplace where employees can simply talk, type, or even show what they need to get work done. They no longer need to learn new systems or adapt to complex tools as the AI meets them where they are. This shift to AI as the UI is a way to humanise technology.

Make AI ‘ready to work’

The next generation of AI agents will be intelligent, role-aware digital teammates that work alongside humans rather than replace them

An intuitive interface means little without robust foundations. To be truly ‘ready to work,’ AI agents must be integrated with enterprise systems, connected to quality data, and aligned to secure workflows. Too often, organisations race to deploy surface-level AI tools that sit on top of disconnected systems, creating more friction than they solve.

‘Ready to work’ agents, by contrast, are context-aware, deeply integrated, and capable of acting independently within trusted boundaries. They can retrieve data, make recommendations, complete actions, and collaborate with employees in real time.

This is the future that platforms are pointing towards, where AI becomes the intelligent entry point to every workflow. It unites people, data, and AI within a single multimodal environment. Employees can engage through text, voice, or even visual cues, and the AI understands their intent, draws from relevant enterprise data, and acts within the flow of work.

When AI and UX converge in this way, the enterprise gains both productivity and adoption. Employees start to want to use AI because it feels natural, seamless, and part of how work gets done.

Working side-by-side

The next generation of AI agents will be intelligent, role-aware digital teammates that work alongside humans rather than replace them. They can draft proposals, manage approvals, and complete actions across thirdparty systems all while operating transparently and within clear governance frameworks.

As enterprises scale their use of AI though, managing dozens of agents across different systems introduces new challenges. This is everything from maintaining security and

compliance to making sure there is consistent governance and accountability. Without a central command point, these agents can quickly become fragmented, creating risk and operational blind spots. To address this, organisations need a unified approach that brings transparency, control, and visibility across their AI ecosystem. Emerging capabilities, such as central AI operations hubs or control towers, are helping enterprises deliver that. Every agent, from voice assistants to web bots, can now operate securely and remain aligned with company policies. In this new paradigm, AI agents don’t sit in the background. They’re xactive participants in daily collaboration. It’s the digital equivalent of having a colleague who never tires and never loses context.

Lessons from EMEA

Leading enterprises are showing what’s possible when AI, data, and workflows converge to create more intuitive, human-centred experiences.

At Adobe, AI agents are being used to connect data and workflows across the organisation, helping teams anticipate and prioritise requests, automate resolutions, and deliver real-time insights. The result is a more personalised and proactive employee experience that scales efficiently.

EY has taken a similar approach, embedding agentic AI within everyday processes to simplify work

and make it more responsive. This enables teams to adapt quickly, focus on higher-value tasks, and experience AI as a natural part of how work gets done.

These examples show that it’s this combination of deep integration and intuitive interaction that drives adoption and lasting impact.

Building trust through experience

While the successes and ROI of the experience approach are clear, employee trust remains the linchpin of any successful AI initiative.

Rolling out a new interface for AI requires cultural as well as technical change. Employees must be involved from the outset and given opportunities to experiment, learn, and see immediate benefits. Quick wins, such as automating everyday requests or simplifying approvals, can demonstrate value early and build confidence in the technology.

Crucially, an AI-driven UI must make work simpler, not more complex. When the interface is natural, multimodal, and contextually aware, it encourages curiosity and exploration rather than resistance. This is what drives adoption at scale — not mandates, but experiences that feel effortless.

The age of the AI interface

As the agentic era takes hold, enterprises that succeed will be those that recognise AI’s true power lies in how we interact with it. This moment in time represents a structural rethinking of how organisations operate and is much more than a design shift. The user interface has always been the defining feature of the relationship between people and technology, and now, AI is that interface. When AI becomes the connective tissue across data, systems, and people, it unlocks new levels of speed, precision, and creativity. The enterprises that will ultimately stand out will be those that make this connective both visible and intuitive, designing experience around people, powered by the help of ‘ready to work’ agents.

THINK BIG, START SMALL, SCALE FAST

Tom Soderstrom, AWS Executive in Residence, discusses what successful innovation and execution at scale look like in the AI era

Enterprise technology conversations have shifted decisively over the past two years. The focus is no longer on whether organisations should adopt cloud, automation, or AI, but on how they turn those technologies into measurable outcomes. Across industries, leadership teams are discovering that access to technology is no longer the limiting factor. Execution is.

For Tom Soderstrom, AWS Executive in Residence, this change reflects what he sees consistently

in discussions with senior leaders around the world. Having spent years on the enterprise side before joining AWS, Soderstrom now works with organisations navigating the transition from adoption to operational impact.

His perspective is shaped by experience rather than abstraction.

“If you’re on the leading edge, you lead. If you’re on the bleeding edge, you bleed,” he says. “I was on the bleeding edge. I made some good things and some stupid things, but you learn from them.” Those lessons, he notes, increasingly have less to do with technology choices and more to do with organisational behaviour.

“When we talk to executives today, it’s rarely about technology,” Soderstrom says. “It’s about culture. It’s about the company culture, how they can move faster and implement things faster, and get their people trained faster.” The challenge is particularly acute in organisations that have grown large and successful. “If you were a small company that became successful,

The biggest challenge to AI is unrealistic expectations, followed closely by trust

so now you grew larger and larger and older and older, you have a hard time innovating,” he adds.

At the leadership level, priorities have narrowed. Soderstrom says that in his conversations with CEOs and managing directors, one theme dominates. “The number one priority is speed — speed to market, speed to profitability, speed to compliance, speed to training and new skills.”

Translating that urgency into execution, however, remains difficult in organisations built to minimise risk.

Why big bets slow everything down One of the most persistent blind spots Soderstrom sees is scale. Under pressure to transform, many

enterprises attempt change through large, multi-year initiatives. The result is often delay rather than momentum. “It’s very difficult to do something big, fast, and well,” he says.

Expectations around delivery have shifted. Where it was once acceptable to demonstrate results several years down the line, leadership teams now expect visible progress far sooner. The organisations making headway are not those lowering ambition, but those breaking it into smaller, measurable efforts.

This is where Soderstrom’s shorthand for execution discipline becomes relevant: think big, start small, scale fast. Thinking big establishes direction, but starting small anchors ambition in reality. “The starting small is the really important part,” he says. “You start with something that generates a business outcome that helps the company, that you can measure and then tell a story about.”

Those early results matter because they change behaviour. “That generates energy and excitement and the rest of the organisation comes along,” Soderstrom explains. Momentum, in his experience, is built through evidence rather than aspiration.

The mechanics of experimentation

Two operating principles underpin this approach. The first is working backwards from the desired outcome rather than leading with technology. “What is the business outcome I want?” Soderstrom asks. “And now I work backwards to try to figure out how do I get there?” Framing the problem this way ensures technology serves delivery rather than driving it.

The second principle is decision design. Too many organisations treat everyday choices as irreversible. “Most companies think that everything has to be decided by the top manager,” he says, which slows progress and concentrates authority unnecessarily. In reality, most decisions are reversible.

“Most decisions are two-way door decisions. You can walk through

the door. If this wasn’t worth it, you come right back.”

Cloud infrastructure makes this practical. “You don’t invest really anything. You just pay for what you use and come right back,” Soderstrom says. When decisions are small and risk is explicit, responsibility can be pushed closer to the people solving the problem, allowing organisations to move faster without losing control.

These dynamics are particularly visible in enterprise AI adoption.

Over the past year, generative AI has moved from experimentation to board-level mandate, often accompanied by pressure to demonstrate rapid returns. Soderstrom sees this tension regularly. “The biggest challenge to AI is unrealistic expectations, followed closely by trust,” he says. Trust operates on several levels. “There’s people-to-people trust. There’s people-to-software-agent trust. And then there’s agent-toagent trust,” he explains. Without

trust, adoption stalls regardless of technical capability.

Soderstrom’s advice mirrors the broader execution playbook. “Pick some real business problems, something small,” he says. “Pick something internal that’s not very risky.” Form small, cross-functional teams that include business, IT, and security, and set short timelines. “I used to give it two weeks, and they had to come up with a demo — something I can see.”

The goal is learning and

adoption rather than polish. “Chief AI Officers, what they are really measured on in the end is adoption in the company of AI,” he says. Return on investment follows later. “Getting return on investment right away doesn’t happen but small investments and visible progress help reset expectations.”

Concerns about talent inevitably surface alongside these discussions. Soderstrom challenges the assumption that organisations lack the people required to move

If you can solve today’s problems with tomorrow’s technology, you can solve tomorrow’s problems — and that’s what energises people and helps large organisations actually want to change

forward. “You have the people you need,” he says. “They don’t have the skills they need.” Training, he argues, works best when it is tied directly to real work. “Don’t send them off to training and then they come back with nothing to work on. Give them on-the-job training.”

As organisations push further into AI and automation, the pressure to move faster is unlikely to ease. Boards will continue to ask for progress, returns, and evidence that investment is translating into advantage. What Soderstrom sees, however, is that the organisations making progress are not the ones chasing scale first, but those willing to experiment deliberately and adjust quickly.

He says, “When people get hands-on with the next technology and see how it applies to real problems, it stops being abstract. If you can solve today’s problems with tomorrow’s technology, you can solve tomorrow’s problems — and that’s what energises people and helps large organisations actually want to change.”

4 STEPS TO QUANTUM-PROOF GCC ENTERPRISES

TBy Damian Wilk, GM – Emerging Markets, Gigamon

he conversation around quantum computing often positions it as a concern for a distant future. However, for organisations across the region, the security implications of quantum advancements are a presentday challenge. A tactic known as “harvest now, decrypt later” is already in play, where malicious actors collect encrypted data today with the intent of decrypting it once quantum computers achieve sufficient power. For government bodies, financial institutions, and companies safeguarding valuable intellectual property, this means data intended for long-term confidentiality is already at risk. The urgency to build quantum readiness is immediate, and it requires more than simply updating cryptographic algorithms; it demands a fundamental shift in visibility and strategy.

The global shift towards post-quantum cryptography is accelerating. A key challenge for organisations is the insufficient visibility into the application of encryption across their systems. In intricate hybrid and multi-cloud settings, risks may stay concealed. Outdated encryption algorithms expired digital certificates, and noncompliant encryption practices can be hidden within encrypted data streams. A core tenet of security is

The transition to postquantum cryptography will unfold over several years as standards mature and systems evolve. Throughout that journey, visibility will determine success

moving beyond strategic planning to measurable progress, beginning with comprehensive cryptographic visibility.

The Gulf’s digital agendas rely heavily on resilient infrastructure, trusted financial systems, and sophisticated public services. Protecting the sensitive data that underpins these elements is crucial. This data often has long confidentiality requirements, necessitating a security approach that looks decades into the future. Regional authorities are actively shifting from strategy development to practical implementation, underscoring the need for enterprises to follow suit.

Deep observability offers a comprehensive approach to obtaining in-depth insights. It gathers data from network packets, flows, and metadata. In contrast to standard monitoring, it can scrutinise encrypted traffic without needing to access the underlying content. This capability facilitates the identification of all encryption methods in operation, the detection of vulnerabilities, and the assessment of new post-quantum configurations. Solutions that provide this degree of visibility make it easier to prepare for quantum security challenges.

Implementing insights from deep observability into concrete security enhancements requires a structured, four-step process:

that you cannot protect or upgrade what you cannot observe.

For the GCC, this issue warrants immediate and focused attention.

The significant scale of critical infrastructure, advanced financial systems, and ambitious national digital transformation initiatives means the stakes are particularly high. Data assets here often require confidentiality spanning many decades. There is clear government momentum, with initiatives such as the UAE Cybersecurity Council’s recent advancements in its national post-quantum readiness programme. The next crucial step for enterprises is to translate this policy intent into verifiable, operational action. This means

1

Achieving complete visibility across all environments

The first step is to establish a unified view across all digital assets. This includes on-premises data centres, private clouds, and public cloud instances. The goal is to identify every active encryption method and pinpoint any legacy systems still in operation. This foundational visibility allows organisations to understand their complete cryptographic footprint, highlighting areas of strength and potential weakness.

2

Applying intelligent analysis to encrypted traffic

With complete visibility,

organisations can then apply advanced analytics. This involves using sophisticated tools to detect anomalous encrypted traffic patterns, suspicious protocol downgrades, or other signals that might indicate “harvest now, decrypt later” data collection activities. Intelligent analysis prioritises remediation efforts based on the business risk associated with specific data and its required confidentiality lifetime.

3

Aligning teams around shared evidence

Effective quantum readiness requires seamless coordination among security, IT operations, and compliance departments. Deep observability provides a common set of facts and network-derived intelligence, fostering collaboration and simplifying audit processes. This is particularly relevant for highly regulated sectors such as banking, healthcare, and energy,

where robust governance and clear evidence of compliance are non-negotiable. Shared evidence reduces friction and accelerates remediation cycles.

4

Continuously validating change

The transition to postquantum algorithms may impact network performance due to factors like larger handshake sizes or increased processing demands. Continuous monitoring is essential to ensure service resilience and continuity throughout the migration period. This involves tracking rollout completeness, catching any fallback to weaker ciphers, and monitoring the realworld impact of new cryptography on latency and compute overhead, thereby maintaining operational stability.

The transition to post-quantum cryptography will unfold over several years as standards mature

and systems evolve. Throughout that journey, visibility will determine success.

For organisations, deep observability provides a decisive advantage. It enables leaders to understand their cryptographic exposure, prioritise investments intelligently, demonstrate compliance with emerging regulations, and maintain trust as digital transformation accelerates. Quantum computing will not arrive overnight-but its implications are already here. Organisations that invest now in visibility and readiness will navigate the transition with confidence. Those that delay may find themselves forced into reactive migrations or grappling with the consequences of compromised long-term data.

In the quantum era, security will belong to those who can see clearly. Deep observability is not just another tool-it is the foundation for resilience, accountability, and digital trust in an uncertain future.

WHEN AI AGENTS SPRAWL

ABy Sid Bhatia, Area VP & General Manager – META, Dataiku

s a renowned early adopter of emerging technologies, the United Arab Emirates (UAE) is routinely among the first to encounter their downsides. During the COVID pandemic, the country’s enterprises were among the first to embark on the Great Cloud Migration. In preserving business continuity and economic progress, organisations soon discovered the resultant lack of control over their own systems architectures. What was once proprietary became shared, fractured, and ill-defined. IT sprawl was born. Today, the UAE faces a similar sprawl with the latest emerging tech – agentic AI. While AI has market momentum, we should be cleareyed about its maturity. AI agents need a strong hand on the tiller if organisations are going to chase opportunities into choppy waters. Robust governance must mandate care and collaboration in experimentation; it must demand 360-degree visibility through the elimination of operational silos; and it must insist upon meaningful metrics that guide future governance. Agent sprawl arises from the absence of these provisions, and like IT sprawl before it, it will be a sinkhole for resources and a multiplier for risk.

The problems

If we are to avoid inefficiency and risk, we must consider how IT sprawl came to dominate some

enterprise stacks. Redundant SaaS apps, for example, led to rising costs and off-radar security vulnerabilities. Agent sprawl leads to similar cost inefficiencies by duplicating AI workflows, and it becomes a compliance risk by using the wrong data in the wrong way.

Governance is, more than anything, a way of having all departments row the boat in the same direction. The finance and HR teams may both be trying to eliminate paper. IT sprawl would have seen each pursue separate solutions to the same problem. Now that AI has become more accessible, it is more likely that team silos will lead to similar shadow AI agents.

Every hour a shadow agent sits idle is an hour of wasted GPU cycles. Every idle agent represents many wasted development hours. Meanwhile, infrastructure bills continue to pile up while a range of hidden costs escalate. Shadow agents can slip the notice of security audits, just like shadow apps have. When operating outside a sphere of governance, agents could access sensitive data outside mandated controls. This not only increases risk but multiplies it across agent instances.

The solutions

Just as governance works for IT sprawl, it can help with agent sprawl. First, governance teams must bring formerly isolated

stakeholders together to define what business use-case each agent satisfies. They must be clear how the agent operates and decide who will take ownership. By establishing these things at the outset, the organisation guarantees accountability, while ensuring that duplication of effort will be unlikely.

The stakeholder council should meet regularly to ensure all operational agents are still required. Those that are not can be retired, repurposed, or merged with others. Governance standards will dictate that only agents that have delivered measurable value will be scaled. To make these decisions possible, it is crucial that stakeholders have access to enterprise-level

Compliance is the bedrock of trust, and a lack of trust can spell failure for much more than just the agentic AI journey

dashboards that allow them to establish the right metrics and act upon them easily.

Strong governance will introduce standardisation in agent lifecycles,

pipelines, lineage tracking, and audit logs. This will protect investments in agentic AI by ensuring agents can be reproduced on demand, but also that they remain compliant. Compliance is the bedrock of trust, and a lack of trust can spell failure for much more than just the agentic AI journey.

A life well lived

The lifecycle of an agent must be carefully, and centrally, managed. While prototyping itself should be effortless, all agents must be validated before they are pressed into service, after which they must operate under the appropriate access permissions. The metrics used to evaluate agentic AI must

cover four areas: efficiency in terms of the usage of computing resources; accuracy and error rates; the presence of redundant, idle, or unowned agents; and productivity in terms of labor saved. These metrics serve as the core KPIs of agentic AI, allowing the best decisions to be made on the future of each agent. The bestperforming ones can be shared across teams and deployed to orchestrate core workflows. Others can be retrained or retired. These anti-sprawl processes will gradually increase AI capital and have agents contribute sustainable value to the business. Over time, its uncluttered AI infrastructure will grant the enterprise what it desires most – a competitive edge.

INSIDE THE MODERN FINANCE STACK

Sunil Paul, Co-Founder and MD at Finesse, examines how CFOs should strengthen core systems and controls to meet rising expectations in an increasingly intelligent era

Like most business functions, finance is undergoing an intelligent overhaul. Across industries, the CFO role has expanded beyond stewardship and reporting into one that is far more exposed to volatility, scrutiny, and expectation. Boards now look to finance not just for accuracy, but for assurance — around compliance, liquidity, and the quality of information used to make decisions. This shift has been gradual, but it is now unmistakable.

Today, regulation has become more digital and continuous. Economic uncertainty has pushed cash and liquidity firmly onto the board agenda. At the same time,

businesses are operating faster, while many finance functions remain constrained by fragmented systems and manual workflows. These pressures help explain changing CFO priorities. A recent study by Grant Thornton notes that 74 percent of CFOs are increasing their technology investments by at least six percent, while 78 percent are prioritising financial operations and processes, with analytics and business intelligence among the key focus areas.

In practice, this evolution has renewed focus on the finance core and the need to strengthen the fundamentals. ERP systems continue to provide the backbone,

but they now need to operate alongside embedded governance, digital compliance, and financial controls that function in real time. E-invoicing mandates and tighter audit expectations have accelerated this shift. When controls and compliance are part of everyday finance activity, trust in the numbers improves — internally and externally.

Liquidity is the next area where expectations have shifted. Cash management, treasury operations, bank connectivity, payments, and exposure management are no longer specialist concerns. They are central to how organisations manage risk and resilience. This has also changed how performance is managed. Many finance teams are moving away from static annual budgets towards more continuous planning, forecasting, and consolidation, providing a clearer view of performance as conditions change.

Navigating this environment also requires better use of data. Business intelligence and finance analytics are now expected to deliver timely dashboards, KPI tracking, and profitability insight that decision-makers can rely on. Automation plays a practical supporting role in areas such as payables, receivables, reconciliations, and reporting. In doing so, finance teams reduce friction and shorten reporting cycles, creating space for analysis and judgement. Where foundations are stable, more advanced analytics can then improve forecast accuracy, support cash flow prediction, and surface anomalies earlier.

At Finesse, this context underpins our approach to an Intelligent Office of Finance. We work with CFOs navigating these shifts, helping align finance systems, controls, visibility, and insight. In practice, the finance functions making the most progress today are not chasing reinvention for its own sake but strengthening their foundations. When systems are connected and fundamentals are sound, finance becomes a trusted co-pilot in business growth.

OPPO: Reno 15 Series

OPPO has launched the Reno15 Series in the UAE, introducing three models—the Reno15 Pro 5G, Reno15 5G and Reno15 F 5G.

The new lineup places a clear emphasis on imaging and durability, with hardware-led upgrades supported by on-device AI processing. The Reno15 Pro

camera designed for high-detail capture and flexible cropping, while all three devices include a 50MP ultra-wide front camera with a 100-degree field of view, aimed at group and social photography.

Low-light performance is addressed through OPPO’s updated dual rear flash system and a front screen flash, supported by AI-driven portrait processing. The Reno Portrait Engine and skin tone optimisation algorithms are designed to preserve natural texture and accurate colour representation across a range of lighting conditions. AI Portrait Glow further enables postcapture lighting correction for

In terms of design and build, the Reno15 Series uses a onepiece sculpted glass back with a redesigned camera housing, paired with an aerospace-grade aluminium frame. Display sizes range from 6.32 inches on the Pro model to 6.59 inches and 6.57 inches on the Reno15 5G and Reno15 F 5G, all featuring

All models carry IP66, IP68 and IP69 ratings for water and dust resistance, positioning the devices for use across varied outdoor environments in the

ELITEBOOK X G2 SERIES

HP Inc. has introduced the EliteBook X G2 Series, a new lineup of business laptops designed for on-device AI performance, enterprise security and mobile productivity.

The EliteBook X G2 Series includes multiple configurations tailored to different workloads. The EliteBook X G2q model is based on the Snapdragon X2 Elite processor and offers up to 85 TOPS of NPU performance for concurrent AI tasks. The EliteBook X G2i uses Intel Core Ultra Series 3 processors, delivering up to 50 NPU TOPS and 180 platform TOPS for graphics-intensive applications. A third variant, the EliteBook X G2a, features AMD Ryzen AI processors with up to 55 TOPS NPU performance.

All models use Copilot+ PC integration and include enterprise-grade security features, including hardwareenforced protections. The design emphasises portability, with sub-1 kg configurations noted for lightness and

ACER: Predator Connect

Acer unveils the Predator Connect X7S 5G CPE, a high-performance gateway that combines 5G mobile broadband with next-generation Wi-Fi 7 connectivity for demanding network environments.

The Predator Connect X7S supports 5G connectivity with downlink speeds of up to 4.67 Gbps using a Nano-SIM slot, enabling broadband-level internet without fixed fibre access. It integrates tri-band Wi-Fi 7 across the 2.4 GHz, 5 GHz and 6 GHz bands, delivering combined throughput up to approximately 5,764 Mbps, and is designed to reduce latency and maintain performance even with many connected devices.

Advanced Multi-Link Operation (MLO) technology dynamically uses multiple bands to stabilise connections, while Hybrid Quality of Service (QoS)— compatible with the Intel Killer Prioritisation Engine— allocates bandwidth to latency-sensitive applications like gaming and streaming.

The unit also offers a backup 2.5 Gbps Ethernet WAN port, allowing automatic failover from 5G to wired internet to help maintain continuous service. Multiple antennas support robust signal reception throughout the home network.

mobility. Display options reportedly include 14-inch panels with high-resolution OLED and support for 120 Hz refresh rates. Other enhancements cited in coverage include support for robust connectivity, team collaboration tools, and improved serviceability for IT environments.