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ASUS Techsphere Forum: Empowering Business Leaders Through Next-Gen Hardware Innovation

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ASUS Techsphere Forum - Group Photo
  • By: Subrato Basu, Managing Partner, Executive Board &
  • Srijith KN, Senior Editor, Integator Media


The line on the opening slide— “Every company will be an AI company”—wasn’t tossed out as a provocation. At the ASUS Techsphere Forum 2025 in Dubai, it landed as an operating instruction. The message across keynotes, the Intel segment, and two candid panels was strikingly consistent: AI stops being theatre the moment you standardize three things—the workspace (where people actually work), the runtime (so models are portable), and the portfolio (so you manage dozens of use cases like a product backlog, not a parade of proofs-of-concept).

A quick reality check on market size so we’re not drinking our own Kool-Aid: the global AI market in 2025 is roughly $300–$400B, depending on scope (software vs. software + services + hardware). Reasonable consensus ranges put 2030 at ~$0.8–$1.6T. In other words, still early—but already too big to treat as a side project.

A wide-angle shot of the ASUS Techsphere Forum

ASUS: PUT AI ON THE ENDPOINT—AND MAKE IT GOVERNABLE

ASUS’s enterprise stance is disarmingly practical. As Mohit Bector, Commercial Head (UAE & GCC) at ASUS Business, framed it, the fastest way to make AI useful is to put it where the work happens (the endpoint) and to make it governable. Concretely, that means:

  • NPUs for on-device inference (privacy, latency, battery life).
  • Manageability (fleet policy, remote control, security posture you can actually audit).
  • Longevity (multi-year BIOS/driver support) so IT can set an AI-ready baseline and keep it stable.

ASUS thinks about the modern workplace as an Enter → Analyse → Decide loop, this is where the workday actually speeds up—quietly, relentlessly, at the endpoint:

  • Enter: the device captures signals—voice, docs, screens, forms, sensors.
  • Analyse: retrieval-augmented reasoning + analytics produce options, risks, and rationales.
  • Decide: humans choose; agents act—raise tickets, update ERP/CRM—with audit trails.

It isn’t about one blockbuster use case. It’s about standardizing the canvas, so small wins compound every week.

ASUS Techsphere Forum 2025 - Panel 1
Panel 1 – From Data to Decisions: Leveraging AI Across Industries

INTEL: FROM SLOGAN TO STACK (AND WHY THE AI PC MATTERS)

Intel’s deck made the “every company will be an AI company” claim implementable. Four slide-level words—Open, Innovative, Efficient, Secure—double as a buyer checklist:

  • Open: less cost, no lock-in. The same models should move across CPU/GPU/NPU and PC → Edge → Datacentre/Cloud without rewrites.
  • Innovation: treat AI PCs with NPUs, edge systems, and cloud clusters as one continuum.
  • Efficient: lead on performance per dollar and per watt; energy and cost are first-class design goals.
  • Secure: your data and your models are IP; run locally when you should, govern tightly when you don’t.

A “Power of Intel Inside” platform slide stitched this together:

  • AI software & services: OpenVINO as the portability layer to convert/optimize/run models across heterogeneous silicon.
  • AI PC: always-on, private inference for day-to-day assistants.
  • Edge AI: near-machine intelligence for vision and time-series use cases.
  • Datacentre & cloud AI: scale-out training/heavy inference (fraud graphs, multimodal analytics, enterprise RAG).
  • AI networking: the fabric that keeps it all moving—securely.

Why the fuss about the AI PC? Because it’s the next enterprise inflection after Windows and Wi-Fi. Slides mapped tangible outcomes:

  • Productivity: faster info-find, auto-drafts, note-taking.
  • Communication: translation, live captioning, dictation, transcription.
  • Collaboration: smart framing, background removal, eye tracking, noise suppression—without pegging the CPU.
  • IT operations: endpoint anomaly detection, VDI super-resolution, remote screen/data removal.
  • Security: client-side deepfake detection, anti-phishing, ransomware flags.

Under the hood, Intel’s definition is a division of labour: CPU for responsiveness and orchestration, GPU for high-throughput math/creation, NPU for low-power sustained inference—the always-on stuff that makes assistants truly useful. Add vPro + Core Ultra and you get the fleet controls and long-term stability IT actually needs.

One more practical bit I liked: Intel AI Assistant Builder—a portal to stand up local assistants/agents (with RAG) that can run on the PC fleet first, shrinking time-to-value from months to days/weeks and letting you prove the full E-A-D loop before you scale heavier jobs to edge/cloud.

When the “100M AI PCs by 2026” slide hit the screen, heads tilted from curiosity to calculation. The figures—bullish vendor projections (~100M by 2026; ~80% AI-capable by 2028)—invite a haircut, but the signal is unmistakable: endpoint AI is becoming the default.

ASUS Techsphere Forum 2025 - Panel 2
Panel 2 – AI-Powered Workspaces and the Future of Work

WHAT THE PANELLISTS REALLY TAUGHT US

RAKEZ (Free Trade Zone)

Posture: Execution-first. Make AI practical on the shop floor and trustworthy in the back office—governed from day one.

What they drive:

  • Diagnostics (OEE baselines, defect maps) + data-readiness scans (MES/ERP) so pilots don’t stall.
  • Reference lines/sandboxes where vendors prove accuracy, safety, throughput before purchase.
  • Template playbooks: CV-QC, predictive maintenance, warehouse vision, invoice extraction/3-way match—each with SOPs, KPIs, integration steps.
  • Curated vendors + shared services (labelling, model hosting/monitoring, SOC for AI) to reduce MSME cost/complexity.

MSMEs: “Bookkeeping-in-a-box” to clean ledgers and free cash; pre-negotiated PoC packs (fixed price/timeline, acceptance metrics); compliance starter kit (consent, retention, safety, escalation).

Enterprises: Multi-site rollout playbooks, edge + cloud reference architectures (identity-aware RAG, policy-constrained agents), and assurance artifacts (model cards, change control, audit trails).

Outcome lens: OEE ↑, FPY ↑/DPMO ↓, MTBF ↑/MTTR ↓, faster close cycles, fewer incidents—AI that moves the P&L and passes audit.

Note – FPY — First Pass Yield; OEE — Overall Equipment Effectiveness; DPMO — Defects Per Million Opportunities; MTBF — Mean Time Between Failures (repairable systems); MTTR — Mean Time To Repair

Oracle (Consulting / Applications cloud)

Posture: AI belongs inside the workflows where finance, HR, supply chain, and service teams live. Expect talk tracks like: ground answers in your own records (RAG with policy), instrument before/after outcomes, and treat AI features as part of ERP/HCM/CX—not a sidecar chatbot. The ask from buyers: prove the Enter → Analyse → Decide gains in real workflows (FP&A forecasting lift, supplier risk scoring, HR talent match quality).

Zurich Insurance (BFSI)
Posture: AI as a force for good, scaled with governance. Think hundreds of use cases: claims triage, fraud/anomaly detection, internal knowledge bots—human-in-the-loop where stakes are high, and IoT-style prevention to reward good behaviour. The key is measurement: fewer false positives, shorter cycle times, clearer audit trails—and elevated roles, not replaced ones.

Group-IB (Cyber / Threat Intel)

Posture: AI to defend—and defend against AI. SOC copilots that summarize and enrich alerts, deepfake/phishing detection, behaviour analytics across identities and endpoints, and the emerging discipline of security of AI (prompt-injection defences, LLM gatewaying, data loss controls for AI apps). If you’re rolling out agents, involve your security team early.

Dhruva Consultants (Tax Tech Transformation)

Posture: RegTech + AI to reduce compliance cost and risk. Document AI to normalize invoices/contracts, anomaly detection for mismatches and fraud flags, and a pragmatic “bookkeeping-in-a-box” on-ramp for MSMEs. Non-negotiables: auditability, versioning, segregation of duties for anything that touches filings.

Prime Group (Labs/Certification)

Posture: Risk-scored processes—every lab step tagged with expected outputs, data access, and fallbacks. Near-term wins: smarter scheduling and test selection; long-term horizon: a Mars-ready lab by 2050 aligned with the UAE’s space ambitions. It’s operational excellence today, exploration mindset tomorrow.

Education (Heriot-Watt University, Dubai)

Posture: candid and useful: human-led pedagogy; AI-assisted admin and decision support. HWU brings talent pipelines (AI/Data Science programs), translational research, and applied robotics capacity (think Robotarium-style ecosystems). This is the repeatable talent + research engine enterprises can plug into—capstones, CPD, joint R&D—that shortens the path from idea to pilot.

WHY UAE HAS A STRUCTURAL ADVANTAGE: RAKEZ × HWU

Local context matters. RAKEZ (Ras Al Khaimah Economic Zone) is more than a location; it’s an adoption on-ramp aligned with MoIAT’s Industry 4.0 programs (ITTI/Transform 4.0). Translation: factories—especially MSMEs—get real help to deploy vision-led quality, OEE analytics, and worker-safety use cases, with policy scaffolding and incentives attached.

Pair that with Heriot-Watt University as a talent/research flywheel and you have a short, well-lit path from concept to production: execution zone + skills engine. That’s a genuine regional edge.

SUMMARY

Techsphere’s most important contribution wasn’t a prediction; it was a design pattern. ASUS gives you the enterprise substrate (AI-ready endpoints you can actually govern). Intel gives you the principles and plumbing (OpenVINO portability; CPU/GPU/NPU continuum; PC → Edge → Cloud). The panellists supplied proof patterns across industries. And the UAE context—RAKEZ for execution, HWU for talent/research—shortens the distance from idea to impact.

If “every company will be an AI company,” the winners won’t be the first to demo—they’ll be the first to standardize. Start at the endpoint, insist on portability, manage a portfolio, and make the Enter → Analyse → Decide loop measurable. That’s how the slide turns into the balance sheet.

_________________________________________________________

  • Glossary of Technical Acronyms
  • OEE — Overall Equipment Effectiveness (measures manufacturing productivity: availability × performance × quality).
  • FPY — First Pass Yield (percentage of units passing production without rework).
  • DPMO — Defects Per Million Opportunities (defect rate in Six Sigma terms).
  • MTBF — Mean Time Between Failures (average time between breakdowns of a repairable system).
  • MTTR — Mean Time To Repair (average time to repair a failed component/system).
  • AI / IT Terms
  • NPU — Neural Processing Unit (specialized chip for AI inference, optimized for low-power sustained workloads).
  • CPU — Central Processing Unit (general-purpose processor for orchestration, responsiveness).
  • GPU — Graphics Processing Unit (parallel processor for high-throughput math and AI training/inference).
  • RAG — Retrieval-Augmented Generation (technique where AI models query external knowledge bases before generating answers).
  • ERP — Enterprise Resource Planning (integrated system for core business processes like finance, supply chain, manufacturing).
  • MES — Manufacturing Execution System (software for monitoring and controlling production).
  • VDI — Virtual Desktop Infrastructure (running desktop environments on centralized servers).
  • SOC — Security Operations Center (hub for cybersecurity monitoring and response).
  • IP — Intellectual Property (protected data, models, or designs).
  • Industry & Enterprise Acronyms
  • BFSI — Banking, Financial Services, and Insurance (industry vertical).
  • FP&A — Financial Planning & Analysis (finance function for budgeting, forecasting, performance analysis).
  • HCM — Human Capital Management (HR technology and processes).
  • CX — Customer Experience (customer-facing processes and software).
  • ITTI — Industrial Technology Transformation Index (UAE Ministry of Industry and Advanced Technology initiative under Industry 4.0).

The ASUS Techsphere Forum, organized by Integrator Media, brought together C-suite leaders from diverse industry verticals to explore how evolving hardware standards are shaping the future of work. The event highlighted the growing role of AI-enabled PCs, showing how advancements in endpoint hardware can directly support business needs. By balancing industry-specific requirements with insights on hardware innovation, the forum offered executives a clear view of how these technologies can enhance productivity and deliver measurable value across the wider business community.

Tech Features

THE BEAUTIFUL GAME, FOR EVERYONE: HOW TECHNOLOGY REWROTE THE RULES OF FOOTBALL FANDOM

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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.

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Tech Features

HOW AI IS RESHAPING HIGHER EDUCATION, AND WHY UNIVERSITIES MUST REINVENT THEMSELVES

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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.

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Tech Features

How the power sector can attract the next generation of STEM talent

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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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