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ICT CHAMPION AWARDS 2026: FIELD NOTES — FROM HYPE TO HABIT
By Subrato Basu, Global Managing Partner, The Executive Board with Srijith KN Senior Editor, Integrator Media.
On 28 January 2026, Integrator Media hosted the 18th edition of the ICT Champion Awards at the Shangri–La Dubai Hotel, bringing together the region’s ICT ecosystem for an evening designed to celebrate milestones, recognise innovation, acknowledge ecosystem leaders, and foster community.
The programme—aligned with INTERSEC 2026—spotlighted organisations making measurable impact across enterprise solutions, critical infrastructure, cybersecurity, and public-sector technology.
By 7pm, the Shangri-La Dubai’s Al Nojoom Ballroom had the feel of a ‘state of the union’ for regional ICT—CXOs, partners, and platform leaders in one room, with AI dominating every board agenda. This wasn’t just an awards evening; it was a moment to take stock: are we still experimenting with AI, or are we ready to operationalise it at scale?
Across conversations at tables and in the corridors, the same theme surfaced: experimentation is easy—operational confidence is the hard part.
Opening keynote: “Is AI ready for us in the UAE—and what next?”
The evening’s tone was set by Mr. Maged Fahmy, Vice President, Ellucian MEA, who opened with a deliberately provocative question: Is AI ready for us in the UAE? What made the question stick wasn’t the technology—it was the implication that leadership models are now the constraint.
His message wasn’t framed as a technology debate—it was framed as a leadership test.
As a leader in enterprise technology for education and public-sector institutions—where trust, governance, and outcomes are non-negotiable—Fahmy’s ‘hype to habit’ message landed with particular weight.
His argument was simple: the UAE is past AI curiosity. The next phase is habit—repeatable, governed AI embedded in day-to-day work. The real question is no longer ‘Can we do a PoC?’ but ‘Can we run this reliably, measure it, and scale it?’
We’re moving from Generative AI (creating content) to Agentic AI (executing work). That shift changes leadership: fewer people doing repeatable steps, more orchestration of workflows across systems—with humans focused on judgement, risk, and exceptions.
For example, an agent can triage a service request, propose the fix, route it for approval, execute the change, and only escalate the ‘weird 3%’ to a human owner.
Leadership reality check: are we still leading like it’s 2022?
He also offered a leadership reality check: if your operating rhythm still assumes long cycles, manual coordination, and slow approvals, you’ll struggle in 2026. Strategy can’t be an annual exercise; it must become a live set of decisions, guardrails, and feedback loops.
AI gives the “how”; humans must own the “why”
His framing landed: AI increasingly gives you the how—options, sequencing, automation. But leaders must own the why—purpose, priorities, ethics, and accountability. In an agentic era, that ‘why’ is what keeps speed from becoming risk.
He also anchored AI’s value in a more human currency: time. Yes, AI drives efficiency. But the real prize is what leaders do with the time they get back: better customer interactions, faster decision-making, more innovation, and more space for creative work that machines cannot replicate.
Talent gaps, transformation, and “sovereign AI”
The keynote did not gloss over constraints. Fahmy flagged the talent gap that emerges when adoption rises faster than capability—especially in AI engineering, cybersecurity, governance, and change leadership. His call was practical: the future workforce isn’t only “AI builders,” but AI challengers—people who can validate outputs, pressure-test recommendations, and govern autonomous workflows.
He also introduced the importance of sovereign AI in the GCC context—where nations like the UAE and Saudi Arabia are thinking deeply about data residency, cultural alignment, regulatory control, and strategic autonomy. The point wasn’t simply “host it locally,” but to build AI that is trustworthy in local context: aligned to language, norms, governance expectations, and national priorities.
In practical terms, sovereign AI means keeping sensitive data and model control within national boundaries, enforcing local governance and auditability, and ensuring outputs reflect language, culture, and regulatory expectations.
Strategy ownership, authority, and misinformation
In 2026, he argued, leaders must be explicit about who owns strategy when decisions are increasingly shaped by AI systems. If an agent can recommend, negotiate, or trigger actions at speed, the organisation needs clarity on authority: approval thresholds, auditability, escalation paths, and responsibility when something goes wrong.
He also linked AI strategy directly to misinformation risk—not as a social media issue alone, but as an enterprise challenge: hallucinations, deepfakes, synthetic fraud, manipulated signals, and decision contamination. The answer, he implied, is not fear—it’s governed adoption: controls, verification, identity assurance, and clear human accountability.
He closed with a grounded reminder that landed strongly with the awards theme: the winners in 2026 won’t be defined by the “fastest AI,” but by the clearest purpose—and by the culture they’ve built to sustain transformation.
Panel discussion: “Seamless Intelligence” — when AI becomes invisible (and unavoidable)
The panel discussion, moderated by Srijith KN (Senior Editor, Integrator Media), brought the theme down from keynote altitude into product and platform reality. The session, titled “Seamless Intelligence: How AI and Dataare Powering the Next Generation of Intelligent Experiences,” featured:
- Mr. Rishi Kishor Gupta, Regional Director (Middle East & Africa), Nothing Technology
- Ms. Bushra Nasr, Global Cybersecurity Marketing Manager, Lenovo
- Mr. Nikhil Nair, Head of Sales (Middle East, Turkey & Africa), HTC
- Ms. Aarti Ajay, Regional Lead Partnerships (Ecosystem Strategy & Growth), Intel Corp
One way to read the panel: infrastructure decides what’s possible, security decides what’s safe, and experience decides what gets adopted.
The discussion converged on one powerful idea: in the next phase, the user shouldn’t “see” the intelligence—it should dissolve into the experience. The ambition is not “AI features,” but AI-native interactions that feel natural, predictive, and frictionless across devices and contexts.
Infrastructure: where does intelligence actually run?
From the infrastructure angle, the panel stressed that “AI everywhere” requires deliberate choices about where compute happens—on device, at the edge, or in the cloud—and how workloads move across that spectrum. This included clear emphasis on the hardware stack (CPU/GPU/NPU) and what it takes to scale AI responsibly.
“AI won’t scale on slogans; it scales on architecture—device, edge, and cloud—each with different cost, latency, and security trade-offs.”
Trust: security, fear factor, and the “moving data center”
From the trust perspective, the panel highlighted the growing “fear factor” around devices and autonomy: more sensors, more data, more models—more attack surface. A memorable analogy landed well: the modern connected vehicle increasingly behaves like a moving data center, raising the bar on governance, identity, and resilience.
“Every new AI capability is also a new attack surface—security has to be designed in, not bolted on.”
Human experience: AI as an experience, not a tool
On the human side, the conversation explored how AI will increasingly show up as experience—wearables, ambient assistance, multi-sensory support, and interactions that augment how people see, decide, and act. The subtext was clear: if AI is going to become ubiquitous, it must become intuitive—and aligned to what humans actually value.
“AI is becoming an experience, not an app—supporting how we see, decide, and act, often without the user noticing the machinery behind it.”
Consumer reality: “make human life smarter” and “declutter your life”
From the consumer device lens, the message was refreshingly plain: AI should help make human life smarter—not noisier. That includes automation that reduces cognitive load and helps people “declutter” their day-to-day, rather than introducing another layer of complexity.
The moderator wrapped the session with a sober economic note: as the stack expands from devices to cloud subscriptions and services, the cost of modern digital life rises—making it even more important that AI delivers tangible value, not just novelty.
“If AI doesn’t declutter your life, it’s not helping.”
Executive Board Commentary: The real shift is “delegation”—not adoption
If there was one undercurrent in the room, it’s that we’ve moved past the question of whether AI is “interesting.” The real question now is: what can we delegate—safely, repeatedly, and at scale—without degrading trust? That’s why the keynote’s emphasis on moving beyond PoCs into governed, repeatable operating models felt so relevant.
This is the step-change many organisations underestimate: adoption is a technology story; delegation is an operating model story. In an agentic era—where systems don’t just generate answers but initiate actions—the enterprise doesn’t need more demos. It needs a way to decide: what tasks can be automated end-to-end, what must stay human-led, and what requires a hybrid “human-in-the-loop” pattern?
A useful lens: the “Delegation Curve”
Think of your AI journey as a curve with three stages:
- Assist (copilot) – AI helps humans do the work faster (drafting, summarising, analysing).
- Act (agentic) – AI executes steps across workflows (triage → route → approve → action), escalating exceptions.
- Assure (governed autonomy) – AI operates with clear authority limits, auditability, and continuous controls (especially critical in regulated sectors and national infrastructure contexts).
Most enterprises are still celebrating Stage 1, experimenting in Stage 2, and under-investing in Stage 3. Yet Stage 3 is where operational confidence is built—and where reputational risk is avoided.
The missing KPI: “Trust latency”
The panel made it clear that infrastructure, security, and experience all shape whether “seamless intelligence” is adopted in the real world.
But the deeper measurement leaders should add is trust latency: how long it takes an organisation to trust an AI outcome enough to act on it without manual re-checking.
In practical terms, the most important AI metrics in 2026 won’t be model accuracy in isolation. They’ll look like:
- Time-to-trust (how quickly decisions can be taken without repeated human verification)
- Exception rate (the “weird 3%” humans must handle)
- Containment rate (how often an agent resolves end-to-end without escalation)
- Governance velocity (how quickly policy, approvals, and controls keep up with agent speed)
This is where leadership becomes the constraint—or the advantage.
Sovereign AI isn’t just residency; it’s “accountability at the boundary”
The keynote’s introduction of sovereign AI resonates strongly in the GCC because the stakes aren’t only technical. They are cultural, regulatory, and strategic.
The next phase of sovereign AI will be defined not by where data sits, but by where accountability sits—who can inspect, audit, override, and certify AI behaviour, especially when agents trigger actions across systems.
Sovereign AI done well will become a competitive advantage: it makes cross-sector adoption easier because it offers confidence by design—clear boundaries, policy alignment, and traceability.
The “AI dividend” test: what are you doing with the time you saved?
A subtle but powerful keynote point was that AI’s real asset is time.
The leadership question is what you do with it. In organisations that win, the reclaimed time becomes: better customer experience, sharper decision-making, faster innovation cycles—and more human attention where it matters.
In organisations that struggle, that time gets lost to rework, re-checking, and governance friction—because trust was never engineered into the operating model.
The new perspective to carry forward
At ICT Champion Awards, the celebration of winners implicitly reinforced the real benchmark for 2026: repeatability. Not “who has the flashiest AI,” but who can run it reliably with trust, governance, and measurable outcomes.
So perhaps the most useful question to take forward is this:
What are the first 3 workflows in your organisation that you are willing to delegate to agentic AI—end-to-end—under clearly defined authority, auditability, and exception handling?
That’s also what the ICT Champion Awards ultimately celebrated: not technology theatre, but execution maturity. The winners weren’t simply early adopters—they were organisations demonstrating innovation with outcomes, leadership with accountability, and scale with governance. In a year defined by agentic possibilities, the Awards served as a reminder that the real competitive edge is operational confidence—systems that work, controls that hold, and teams that can sustain change. Hype is easy; habit is earned.
By: Jason Ou, President at Hisense MEA
As the FIFA World Cup 2026 final approaches this week, we reflect on a tournament that transformed how millions experienced the sport, from living room stadiums to quiet spaces in packed arenas
As we count down the final hours before this week’s showpiece final, the FIFA World Cup 2026 has delivered 103 matches across 16 cities, and with it, a reimagining of what “experiencing football” means. Hisense served as the official and exclusive Video Assistant Referee (VAR) Review TV Provider for the entire tournament across the United States, Canada, and Mexico. Every controversial offside call. Every penalty review that had fans screaming at their screens. Every red card confirmation that shifted the momentum of a knockout match. The technology referees used to make those match-defining decisions ran on Hisense RGB MiniLED displays. The Video Operation Room in Zurich was upgraded specifically with these screens because VAR officials needed “clear and authentic restoration of live match footage.”
And it delivered.
Two parallel revolutions unfolded across this tournament: one that transformed homes into legitimate viewing destinations, and another that finally opened stadium doors to millions who’d been locked out for decades.
Hisense made an argument before kickoff: the home viewing experience could, in some ways, surpass what you’d get at the stadium itself. If the technology was precise enough for officiating decisions scrutinized by billions and debated across social media within seconds, it was good enough for living rooms worldwide.
For those who invested in the L9Q TriChroma Laser TV, everyday living spaces became premium match-day destinations throughout the tournament. With ultra-large displays up to 200 inches, fans followed every run, pass, tackle, and goal with remarkable clarity.
The flagship UXS RGB MiniLED TV, powered by breakthrough RGB MiniLED technology that delivers exceptional color accuracy, brightness, and contrast, brought fans closer to every moment on the pitch and created a more immersive and lifelike viewing experience for sports, entertainment, and gaming.
The Party Everyone Could Finally Join
For millions of fans living with autism, PTSD, dementia, anxiety, and other sensory processing conditions, the stadium experience had remained firmly out of reach, a party they could hear from outside but never truly join. This tournament changed that.
At this year’s tournament, all 16 host stadiums featured dedicated sensory rooms, making this the first-ever Sensory Inclusive FIFA World Cup. Hisense collaborated with FIFA and KultureCity to install these spaces across every venue in the United States, Canada, and Mexico, and they were used.
As Hisense continues pushing boundaries, making every match feel bigger, every celebration more immersive, and every memory more unforgettable, one truth has emerged from this tournament: the hierarchy of World Cup viewing has been expanded, making room for everyone who loves the beautiful game.
This week, as billions watch the final from living rooms with 300-inch screens and fans with sensory needs take their seats in the stadium, football’s promise will be fulfilled. The beautiful game. Finally, for everyone.
By: Prof. May El Barachi, Dean & Full Professor, University of Wollongong in Dubai
Artificial intelligence is no longer a future technology. It has become part of our everyday lives almost overnight. Whether we are writing emails, analysing data, generating code, creating presentations, or conducting research, AI has fundamentally changed how knowledge is created and consumed.
For higher education, this represents one of the biggest disruptions since the arrival of the internet.
Much of today’s conversation revolves around a simple question: Will AI replace educators?
I believe we are asking the wrong question.
The real question is whether universities can reinvent themselves quickly enough to prepare graduates for an AI-first world.
Having worked extensively with generative AI technologies, I see AI not as a replacement for education, but as an extraordinary opportunity to redefine it. From One-Size-Fits-All Learning to Personalized Education.
Traditional education has largely been built around standardized delivery: one lecturer, one classroom, one pace, and one curriculum for every student.
AI changes that equation.
For the first time, every learner can potentially have access to an intelligent learning companion available 24 hours a day. AI tutors can explain difficult concepts, generate additional practice exercises, adapt explanations to different learning styles, provide immediate feedback, and support students until genuine understanding is achieved.
Instead of asking students to adapt to education, education can finally adapt to students. This has important implications for accessibility, allowing high-quality learning experiences to reach individuals regardless of geography or socioeconomic background.
In many ways, AI has the potential to become the great equalizer in education.
Teaching Students How to Think; Not What to Memorize
At the same time, AI forces universities to rethink their educational philosophy.
When information is instantly accessible, memorization becomes less valuable.
Future graduates will be judged less by what they know, and more by how effectively they can solve problems, evaluate evidence, think critically, collaborate, communicate, and exercise sound judgement. This means assessment methods must evolve as well.
Rather than rewarding students for reproducing information that AI can generate in seconds, universities should increasingly emphasize authentic projects, real-world problem solving, teamwork, creativity, ethical reasoning, and applied learning. Ironically, AI may push higher education to become more human, not less.
Educators Are Becoming AI-Enabled Mentors
There is growing concern that AI will eventually replace lecturers. I see the opposite happening.
The educator’s role is becoming even more important; but it is changing.
Rather than acting primarily as transmitters of knowledge, educators are evolving into mentors, coaches, facilitators, and critical thinking partners who help students interpret information, challenge assumptions, and develop professional judgement.
To do that effectively, universities must invest heavily in AI literacy. Faculty need more than basic familiarity with AI tools. They must understand how these systems work, their limitations, their biases, and how they can be integrated responsibly into teaching, assessment, and research. AI literacy is rapidly becoming as fundamental as digital literacy was twenty years ago.
Preparing Graduates for an AI-First Workforce
Perhaps the biggest transformation is happening outside the classroom. Virtually every profession; from healthcare and finance to engineering, education, law, and government; is being reshaped by AI.
Graduates entering the workforce will collaborate with intelligent systems every day. This requires a new combination of technical and human capabilities. Understanding AI, data, automation, and digital technologies will become essential across disciplines. Equally important will be creativity, emotional intelligence, leadership, adaptability, ethical decision-making, and lifelong learning. The most successful professionals will not compete against AI. They will learn how to work alongside it.
Looking Ahead
The future university may look very different from today’s institution. Degrees are likely to become more modular and flexible, complemented by stackable micro-credentials that allow professionals to continuously update their skills throughout their careers.
Immersive technologies such as virtual and augmented reality will create richer learning experiences, while learning analytics will enable institutions to identify struggling students earlier and provide personalized support. Education will become increasingly global, connected, and lifelong.
The Human Advantage
Despite all these technological advances, one thing remains unchanged. Education has never been solely about transferring knowledge. It is about inspiring curiosity, building confidence, developing character, nurturing empathy, and preparing individuals to make meaningful contributions to society.
No algorithm can replace the inspiration of a great teacher or the mentorship that shapes a student’s future.
AI should not diminish the human element of education. It should amplify it.
The universities that thrive over the next decade will not be those that simply adopt AI tools. They will be those that successfully combine technological innovation with the uniquely human qualities that no machine can replicate. Because ultimately, the future of higher education is not about artificial intelligence. It is about human intelligence; enhanced by AI, guided by educators, and applied to solve the world’s most complex challenges.
By Amjad Alqaqaa – Vice President – MEAI
Power sectors around the world are undergoing rapid transformation. Digital technologies, advanced materials, and the shift towards lower-carbon energy are reshaping how power plants and critical infrastructure are designed, operated, and maintained. Yet one persistent challenge continues to hold the sector back: a shortage of people with the right engineering and technical skills.
As the UAE continues to advance its ambitions as a leading hub for innovation and technology, there is an increasing need to strengthen and future-proof STEM capabilities to keep pace with evolving industry demands. According to a report by STEM workforce consultancy SThree, 40% of STEM professionals in the UAE believe that upskilling and reskilling are the most effective ways to boost productivity and competitiveness. While more than a third (32%) point to skills shortages as a barrier to productivity, highlighting a clear gap between workforce capabilities and industry needs.
Additionally, data from the Hays 2026 US Salary & Hiring Trends Guide indicates that companies in the UAE are starting to slow down recruitment and instead are investing in the skills of their existing workforce, with around 42% of employers prioritising upskilling over hiring.
Research from LinkedIn also suggests demand for green skills is rising much faster than supply, highlighting a widening gap between the skills needed for the energy transition and the talent currently available in the workforce.
For power generation companies, this is more than a recruitment issue. Skills shortages can impact equipment reliability, delay maintenance programmes, and slow the deployment of new technologies. In a sector where uptime, safety, and efficiency are critical, having the right expertise in place is essential.
At the same time, interest in STEM subjects among young people has fallen in recent years. This weakens the future talent pipeline. This means companies must do more to attract and develop STEM talent.
Showing young people what engineering looks like today
One of the challenges is perception. Many young people still associate engineering with traditional industrial roles, rather than the highly advanced, technology-driven careers available today.
Today’s engineers work with advanced digital tools, automation systems, and real-time monitoring technologies. In the power sector, they help keep turbines, pumps, and other critical systems running efficiently. They also work on challenges linked to sustainability, energy efficiency, and emissions reduction.
To address this gap, employers must play a more active role in educating emerging talent about the career opportunities in the sector. That means working more closely with schools, colleges, and universities to showcase the wide range of careers available across engineering and energy.
Partnerships between industry and academia play an important role here. For example, John Crane works closely with the University of Sheffield to support research and PhD programmes in areas such as materials science and engineering. Collaborations like this help connect academic research with real industrial challenges and encourage more students to consider careers in engineering.
These partnerships also help ensure that new research translates into practical solutions that can support industries such as power generation.
Why apprenticeships matter
Alongside academic pathways, apprenticeships are another key way to attract new talent into engineering.
They offer a practical, accessible route into engineering, allowing individuals to gain hands-on experience while working towards recognised qualifications. For employers, apprenticeships provide an opportunity to develop skills aligned to real operational needs, from maintenance and reliability engineering to digital and software capabilities.
But apprenticeships are not only for new recruits. They can also help people who are already in work develop new skills. Programmes linked to areas such as leadership, project management, and digital technologies allow employees to adapt as roles change and technology evolves.
This matters because the skills challenge is not only about bringing new people into the sector. It is also about helping the existing workforce build the capabilities needed for the future.
Building the right skills through training partnerships
Developing a skilled workforce requires more than internal programmes alone. Strong partnerships with external training providers are essential to ensure employees gain the specialist knowledge needed in highly technical environments.
Working with a network of training providers enables organisations to deliver structured learning alongside on-the-job experience. This approach ensures that training remains aligned with real operational challenges, including maintaining equipment reliability, improving efficiency, and meeting evolving safety standards.
Reaching a broader talent pool
Engineering companies need to widen their outreach and look beyond traditional recruitment channels. This includes engaging with students earlier and encouraging people from different backgrounds to consider technical careers.
In addition, requalification programmes are increasingly important in some regions. For example, in the Czech Republic, targeted requalification initiatives are helping individuals transition from other industries into engineering roles, providing a practical route to address skills shortages while bringing valuable experience into the sector.
Ensuring training programmes cater to a wide range of people with varying levels of experience can upskill new and existing workers and build a healthier talent pipeline. Providing that support is an investment that helps create a stronger, more resilient workforce in the long term.
Building the workforce of the future
The power sector plays a central role in driving the global energy transition. In the Middle East, this transition is expected to drive demand for a wide range of engineering roles, particularly in renewable energy, grid infrastructure, and related technologies, highlighting the need for targeted training and workforce development programmes to equip both new entrants and existing workers with relevant technical skills.
Engineers and technicians will be needed to maintain power plants, improve equipment performance, and develop new energy technologies. But these goals will only be possible if the industry has access to the right skills.
To achieve this, companies must think differently about talent. Strengthening collaboration with educators, improving outreach to diverse talent, and offering practical training routes such as apprenticeships all play an important role in addressing the STEM skills gap.
Apprenticeships alone will not solve the skills gap. But when combined with research partnerships and targeted workforce development, they can play a major role in rebuilding the STEM talent pipeline. By investing in people and skills today, the power sector can build the workforce it needs to support a more reliable and sustainable energy system for the future.
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