By Wei Huang, Chief Technology Officer, Anomali

In cybersecurity, each era is defined by a shift in architecture. Firewalls dominated the 2000s. Endpoint protection and identity controls shaped the 2010s. Today, we are entering a new phase — one where cloud-native platforms, real-time data correlation, and AI-powered analytics are no longer optional but essential.

Nowhere is this transition more timely than in the Gulf Cooperation Council (GCC) region. As cloud adoption accelerates across the United Arab Emirates (UAE), Saudi Arabia, and neighboring states, national cybersecurity resilience has become a critical pillar of digital transformation. GCC organizations have a unique opportunity to leap ahead — bypassing legacy limitations and adopting next-generation security architectures purpose-built for today’s advanced threats.

The Core Shift: Security Is Now a Data Problem

For decades, cybersecurity focused on control: firewalls, proxies, endpoint agents, and network gateways. While these tools remain foundational, today’s adversaries have evolved. Attackers exploit gaps between systems, bypass controls through misconfigurations, and evade siloed defenses with increasing sophistication.

The result is a fundamental architectural shift: modern security is no longer solely about enforcing control — it’s about processing data. Effective defense requires ingesting, normalizing, and correlating telemetry across every layer of the enterprise: endpoints, cloud workloads, SaaS platforms, identity systems, and external intelligence feeds. When combined with AI-powered analytics, this data-driven approach transforms raw telemetry into actionable insights, allowing defenders to outpace attackers, rather than merely react, once an attack has been detected.

Cloud-Native Design: The Architecture That Scales

Traditional security information and event management (SIEM) systems and on-premises platforms struggle to meet the scale, flexibility, and speed required in modern hybrid environments. Cloud-native architectures, by contrast, offer elastic scalability that aligns directly with national digital transformation priorities across the GCC.

However, the scale of telemetry introduces new challenges. Global cloud storage volumes are projected to reach 100 zettabytes by the end of 2025. Storing and processing such massive datasets can quickly become prohibitively expensive — unless managed with modern design principles.

The solution lies in the security data lake: a unified, long-term, cloud-native repository capable of retaining years of structured and unstructured security data. Unlike legacy systems limited to weeks or months of visibility, a security data lake enables continuous historical analysis for threat hunting, compliance, and investigations.

Crucially, modern architectures decouple storage and compute. Instead of permanently allocating compute resources (as most legacy platforms do), serverless designs apply compute power only when needed, dramatically reducing cost while enabling faster analysis.

For example, by leveraging serverless infrastructure on Amazon Web Services (AWS), Anomali enables compute bursts across thousands of nodes, delivering correlations and searches up to 1,000 times faster, at a fraction of the cost of traditional solutions. This approach is particularly aligned to national resilience goals, where speed and efficiency are essential.

Real-Time Correlation at Petabyte Scale

Today’s attackers automate their reconnaissance, probing continuously for vulnerabilities across every layer of the enterprise. To keep pace, organizations must reduce detection time and response costs, which demands real-time correlation across petabytes of data.

By integrating telemetry from multiple domains — including firewalls, endpoints, SaaS platforms, identity providers, and threat intelligence — organizations gain visibility into attacks that no single control would detect alone. For GCC enterprises expanding hybrid and multi-cloud infrastructures, the ability to correlate across these diverse sources in real time is mission-critical.

AI Delivers Context, Not Just Alerts

Artificial intelligence is now widely marketed in cybersecurity, but much of it offers opaque conclusions without transparency — effectively adding noise rather than clarity.

True AI-powered defense must provide explainability. Anomali applies chain-of-thought (CoT) AI reasoning, ensuring every detection includes the rationale, evidence, and audit trail behind each decision. This transparency builds analyst confidence and accelerates skill development, particularly valuable as GCC nations continue building local cybersecurity talent and operational maturity.

Intelligence Closes the Gaps Left by Controls

Even with modern defenses in place, critical gaps remain. Studies show that many endpoint detection and response (EDR) solutions still miss up to 30% of advanced threats, thanks to sophisticated evasion techniques, configuration gaps, or partial visibility. Firewalls suffer similar challenges: misconfigurations and limited context allow adversaries to slip past perimeter defenses.

This is where intelligence plays a decisive role. By unifying diverse telemetry and correlating billions of daily security events, modern security analytics platforms fill these blind spots, delivering full-spectrum detection across hybrid environments. For critical infrastructure, financial institutions, and government entities in the GCC, closing these gaps is no longer optional — it is a resilience imperative.

Agentless, Serverless, Effortless

Managing thousands of endpoint agents introduces complexity, operational risk, and resource overhead. Cloud-native platforms eliminate much of this friction by integrating directly with cloud platforms, SaaS services, and enterprise infrastructure via secure APIs, allowing telemetry ingestion without deploying additional agents.

For organizations balancing hybrid complexity with cloud-first strategies, agentless deployment models dramatically simplify operations — enabling faster rollout, lower risk, and greater agility.

Why the GCC Is Uniquely Positioned to Lead

The UAE, Saudi Arabia, and neighboring GCC nations are investing heavily in smart cities, digital economies, and next-generation public services. These national ambitions require security platforms that are scalable, adaptive, intelligent, and capable of evolving alongside rapid technological change.

Cloud-native, AI-powered, intelligence-driven security operations are no longer a distant vision but an operational necessity. By embracing these architectures, GCC enterprises and governments are positioned not only to meet today’s security demands, but to set a global standard for the future of cyber defense.

The time to shift from fragmented controls to unified intelligence is now. The future of security isn’t about deploying more tools — it’s about building smarter platforms.

And the GCC is ready.

Wei Huang is the Chief Technology Officer at Anomali, a global leader in intelligence-driven cybersecurity solutions.

As the region accelerates its digital and cultural transformation, professional audio will only grow in importance.

By Yassine Mannai, Associate Director Sales, Shure MEA

The Middle East and Africa (MEA) region is witnessing an extraordinary moment of profound transformation as nations continue to reimagine their respective economies. Cities across this vibrant region are increasingly positioning themselves as global hubs, anchored on rapid technological shifts. From national diversification agendas such as Saudi Arabia’s Vision 2030 to the UAE’s expanding cultural economy and Africa’s urbanization, the region is rethinking how it communicates, collaborates, and entertains. Against this backdrop, professional audio integration has emerged as the key enabler. Pro audio is no longer viewed as luxury; it has become a strategic pillar of productivity, culture, and trust.

For Shure, this represents fertile ground for growth. The company’s trajectory in the region is anchored on a clear multi-prong approach: sustainable value creation through localization, strong partnerships, and continuous education. Rather than chasing short-term wins, the focus is on building strong ecosystems where audio technology empowers organizations to achieve their ambitions.

A Partner in Regional Growth

Demand for professional audio is being fueled by three key drivers. First, the large-scale investments in infrastructure and cultural projects trend in the region is creating an appetite for reliable, scalable audio solutions. Second, with hybrid work and learning still active, audio systems now serve as must-have tools for collaboration, ensuring clarity and engagement. Third, the entertainment and events industry continues to flourish, with audiences expecting immersive sound experiences with emotional connection.

Shure’s presence in conferences, cultural centers, and classrooms underscores its adaptability. By aligning closely with each sector’s needs, the company is not just supplying equipment – it is shaping how people experience communication and culture. Providing the ultimate IT and meeting room solutions is one thing, ensuring that end-user requirements in meeting spaces are consistently met is where the rubber meets the road, which makes factors such as quality, form factor, and smart solutions that leverage technology for seamless integration crucial.

A Strategy Anchored on Three Pillars

Shure’s growth blueprint rests on localization, partnerships, and education.

• Localization ensures that global standards are adapted to regional requirements. A broadcaster in Abu Dhabi may demand wireless mobility, while a university in Riyadh seeks scalable, user-friendly systems. Meeting these nuanced needs requires agility and customization.
• Partnerships with distributors, integrators, and resellers expand reach and sustain service excellence. These trusted relationships are critical to delivering value on the ground.
• Education equips professionals with the right skills to maximize technology investments. Through training initiatives, Shure empowers AV specialists to deploy and maintain systems effectively, ensuring customers achieve long-term returns.

Technology and Innovation at the Forefront

We strongly believe that the future of audio in the region will be shaped by three defining trends.

• Immersive experiences are becoming a cultural norm, and audio must now create impact as much as it delivers clarity.
• AI and intelligent systems are moving from concept to reality making adaptive audio that responds to its environment the way to go.
• Hybrid environments will remain central to work and education even as physical and virtual interactions merge with audio determining whether collaboration succeeds or fails.

A century of sound, a future of possibility

This year, Shure marks its 100-year anniversary. Few technology brands reach such a milestone, and fewer still do so with their reputation for quality and trust intact. For customers and partners in MEA and beyond, the centennial is not merely a celebration of heritage. It is a reassurance that Shure’s next century will be guided by the same principles that made it a global leader – with innovation, reliability, and customer focus at the core.

As the region accelerates its digital and cultural transformation, professional audio will only grow in importance. For IT leaders, this means viewing sound not as an afterthought, but as a strategic layer of infrastructure – one that underscores effective communication, collaboration, and connection.

Shure’s growth story is far from complete. The company’s next chapter is being written in partnership with the region’s institutions and enterprises. And in an age where voices need to be heard clearly across physical and digital spaces, Shure’s mission remains simple: to deliver sound that empowers progress.

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.

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.

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.

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.

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• 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.