Technology
FROM PILOTS TO POWER INFRASTRUCTURE: HOW THE GCC IS ENGINEERING THE NEXT PHASE OF AI
By Farid Yousefi, Founder & CEO, Finder Group Ai
Artificial intelligence in the Gulf Cooperation Council (GCC) is entering a decisive new chapter. What began as experimentation, ie, isolated pilots, proof-of-concept chatbots, and innovation lab demos, is rapidly evolving into something far more consequential. In 2026, AI will no longer sit at the periphery of digital transformation strategies. Instead, it will operate as a foundational layer of economic, industrial, and civic infrastructure, embedded into how energy systems run, how governments serve citizens, and how capital flows through the region.
This shift reflects a broader reality: the GCC is no longer merely adopting global AI trends, but actively shaping its own AI paradigm, one that is grounded in sovereign control of data and compute, tuned to Arabic language and local context, and aligned with national visions that prioritize scale, speed, and long-term resilience. The region’s ambition is not incremental improvement, it is to redefine how intelligence itself is designed, governed, and deployed at national scale.
The Maturation of Generative and Agentic AI
By 2026, the most significant leap in AI capability across the GCC will come from the maturation of generative AI and “agentic” AI systems. These technologies move beyond passive analytics or conversational interfaces. Agentic AI can reason, plan, and take actions across complex workflows, effectively acting as a digital operator rather than a static tool.
Crucially for the region, large language models fine-tuned for Arabic dialects and Gulf-specific context are rapidly improving. This has profound implications. Customer-facing AI systems are becoming genuinely fluent, capable of understanding nuance across Modern Standard Arabic, Gulf dialects, and bilingual Arabic-English interactions. Banks can now deploy AI-driven fraud detection and customer support in Arabic without sacrificing accuracy or trust. Governments can offer multilingual virtual assistants that guide citizens through services with clarity and cultural sensitivity.
Beyond language, real-time predictive analytics is reaching operational maturity. In energy and utilities, AI models are being trained to detect early warning signs of equipment failure on oil rigs, pipelines, and power grids. The economic impact is significant: preventing a single unplanned outage can save millions of dollars while improving safety and environmental outcomes.
In logistics and smart cities, multimodal AI, systems that simultaneously process images, sensor data, and text, is transforming operations. Ports are using AI to automate customs paperwork and optimize cargo routing. Cities like Dubai and Riyadh are deploying AI to dynamically manage traffic congestion, monitor infrastructure health, and improve public safety. These capabilities signal a clear transition: AI is no longer an experimental back-office function, but front-line infrastructure, intelligence delivered as a utility.
Redesigning Government and National Infrastructure Around AI
This technological maturation is reshaping how GCC governments think about digital services and national-scale infrastructure. Traditional e-government portals, static, form-based, and siloed, are giving way to AI-powered concierge models. Instead of navigating multiple platforms, citizens increasingly interact with a single intelligent agent.
Imagine a system that can visually review submitted documents, understand a request in natural language, and execute transactions across multiple departments in one seamless interaction. This is not a distant vision. Across the GCC, ministries are already using generative AI to automate administrative tasks, summarize regulations, and simulate policy outcomes. These early deployments foreshadow a future where agent-based systems anticipate needs and act proactively.
Mega-projects and smart city initiatives are embedding AI from inception rather than retrofitting it later. With dense networks of IoT sensors feeding real-time data, cities such as NEOM, Riyadh, and Dubai are building AI “control layers” that continuously monitor traffic, energy consumption, water usage, and security. Agent-based systems can then coordinate responses, rerouting vehicles, balancing power loads, or flagging anomalies, without waiting for human intervention.
The result is self-optimizing infrastructure. Humans remain responsible for strategy, ethics, and oversight, while AI executes decisions at machine speed. This represents a fundamental shift in governance and urban management: designing for intelligence at scale rather than manual supervision.
Sovereign Compute: The Backbone of GCC AI Ambitions
None of this transformation is possible without a parallel revolution in AI infrastructure. The GCC’s aspiration to become a global AI hub hinges on sovereign compute capacity – control over the data centers, chips, and energy that power advanced AI models.
Over the past two years alone, sovereign wealth funds across the region have mobilized more than $100 billion toward AI infrastructure. This scale of investment is unprecedented, outpacing even Europe. Landmark initiatives such as Abu Dhabi’s Stargate project, a multi-gigawatt data center campus designed to host and train large AI models on local data, and Saudi Arabia’s plans for up to 6 gigawatts of AI data centers under its HUMAIN initiative exemplify this ambition.
The region enjoys a structural advantage in this race: energy. Power costs in the Gulf are less than half those in many European markets, providing a natural edge in the energy-intensive process of training large models. At the same time, operators are innovating to address environmental and climatic challenges. Advanced cooling technologies, including liquid immersion cooling, are being deployed to operate efficiently in summer temperatures exceeding 45°C. Renewable energy integration is also increasing, aligning AI growth with sustainability goals.
Equally important is sovereign control over hardware. GCC nations are investing in local chip design programs and forging strategic partnerships to secure access to cutting-edge AI processors. In an era of global supply-chain uncertainty, this control over compute is becoming as strategically important as control over oil reserves once was. The region is effectively converting its natural advantages of capital and energy into a durable compute advantage for the AI age.
Where ROI Is Materializing First
From an investment standpoint, the strongest returns in the GCC are emerging where AI delivers direct, measurable impact. Predictive maintenance in energy and utilities is a prime example. AI systems that prevent equipment failures or optimize drilling operations offer immediate cost savings and operational resilience. Unsurprisingly, pilots in oil and gas—such as AI models analyzing drilling plans—are rapidly scaling into production environments.
In financial services, AI-driven fraud detection, risk scoring, and KYC automation are moving from experimentation to enterprise-wide deployment. Banks across the region have demonstrated that these systems reduce losses, improve compliance, and significantly speed up customer onboarding. Customer service automation is also reaching maturity. Telecom operators, airlines, and government agencies that once piloted Arabic-language chatbots are now preparing to replace tier-one support entirely with AI agents, improving availability while lowering costs.
Logistics represents another high-ROI frontier. Gulf ports and free zones are scaling AI solutions that automate documentation, optimize cargo flows, and reduce bottlenecks. Successful trials have shown faster throughput and improved competitiveness—critical advantages for economies positioning themselves as global trade hubs.
The common thread is pragmatism. Investors and enterprises are increasingly prioritizing AI that solves real problems and delivers returns per dollar invested. The era of AI experimentation without clear outcomes is giving way to disciplined scaling of proven use cases.
Regulation as an Accelerator, Not a Constraint
As AI adoption accelerates, governance has become a central pillar of the GCC’s strategy. National AI frameworks in the UAE, Saudi Arabia, and Qatar are establishing trust-first guardrails focused on transparency, accountability, and human oversight. These policies are not designed to slow innovation, but to ensure it scales safely.
Saudi Arabia’s guidelines, for example, mandate human oversight for public-sector AI and require transparency measures such as watermarking AI-generated content. Qatar’s central bank has introduced governance rules requiring audits and human review for high-stakes algorithms. These frameworks inevitably influence data flows, encouraging sensitive information to remain within national borders.
While this localization may initially limit free cross-border data movement, it is simultaneously fueling massive investment in regional cloud and data center infrastructure. Over time, regulatory alignment across the GCC, particularly around shared principles of fairness, accountability, and transparency, will enable AI solutions certified in one country to scale regionally. Clear rules reduce uncertainty, giving enterprises and investors confidence to deploy AI at scale.
The Hidden Risks of Autonomous AI
Despite the momentum, risks remain, and some are underestimated. One of the most significant is overconfidence in AI accuracy. Even advanced models can hallucinate or fail, particularly when dealing with local dialects or sparse data. In high-stakes sectors such as security, healthcare, or law enforcement, such errors can have serious consequences. Human oversight is therefore not optional, regardless of how autonomous a system becomes.
Operational fragility is another concern. Many organizations overlook infrastructure dependencies, such as reliance on imported GPUs or insufficient cooling and backup power for data centers. In the Gulf’s climate, these vulnerabilities can quickly become systemic risks. Cybersecurity also takes on new dimensions as AI systems gain autonomy, expanding the attack surface for malicious actors. A compromised AI traffic system or a convincing deepfake could undermine public trust overnight.
Finally, reputational and regulatory backlash remains a risk if AI is misused or deployed without adequate safeguards. A single incident involving biased decision-making or a privacy breach could slow adoption across entire sectors. Rigorous testing, transparency, and fail-safes, the unglamorous aspects of AI, are essential for sustainable progress.
Who Will Lead the GCC AI Race?
By 2026, leadership in the GCC AI landscape will be shaped by a combination of talent, data, sovereign strategy, and investment appetite. The UAE and Saudi Arabia are poised to lead, each leveraging distinct strengths. The UAE’s early-mover advantage, world-class institutions such as MBZUAI, and deep integration of AI into daily life have positioned it as a global reference point for adoption. Saudi Arabia, meanwhile, brings unmatched scale, capital, and data assets particularly in energy, making it the region’s AI infrastructure powerhouse.
Other GCC nations will lead in targeted ways. Qatar is emerging as a center for ethical AI and safe deployment, Bahrain as a pioneer in cloud-first government integration, and Oman as a steady builder of digital infrastructure and local talent pipelines. Across industries, government services will continue to drive adoption, while energy and finance lead commercially.
From Oil Wells to “Intel Wells”
Ultimately, the GCC’s AI journey is about more than technology, it’s about redefining economic value creation. The region is moving from oil wells to “intel wells,” treating data and insight as the new strategic resource. At Finder Group AI, our mission is to connect the region’s abundant capital with its brightest innovators responsibly, transparently, and at scale.
By 2026, the global conversation will shift from AI hype to AI habitat. The Gulf will not just be adopting AI, but exporting a new standard, one that balances cutting-edge innovation with trust, governance, and purpose. The rise of the GCC as an AI hub will create opportunities far beyond its borders, shaping the next phase of the global AI economy on the region’s own terms.
-Ends-
About the Author:
Farid Yousefi is a serial entrepreneur and innovator leading the development of Finder Group Ai, an AI-powered venture builder ecosystem based in Dubai. With a strong background in strategy, business development, and technology adoption, his focus is on helping ideas transform into scalable businesses through AI-driven solutions.
His work spans across building and mentoring startups, forging partnerships, and guiding ventures from ideation to growth. He is passionate about creating impact through technology, developing sustainable ecosystems, and supporting founders on their journey through in-depth technical and industry knowledge and expertise and access to a global network of venture capitalists and angel investors to attract investment, and through partnerships at the highest level within government to aid integration and scale rapidly within local territories.
Tech Features
FROM AI EXPERIMENTS TO EVERYDAY IMPACT: FIXING THE LAST-MILE PROBLEM
By Aashay Tattu, Senior AI Automation Engineer, IT Max Global
Over the last quarter, we’ve heard a version of the same question in nearly every client check-in: “Which AI use cases have actually made it into day-to-day operations?”
We’ve built strong pilots, including copilots in CRM and automations in the contact centre, but the hard part is making them survive change control, monitoring, access rules, and Monday morning volume.
The ‘last mile’ problem: why POCs don’t become products
The pattern is familiar: we pilot something promising, a few teams try it, and then everyone quietly slides back to the old workflow because the pilot never becomes the default.
Example 1:
We recently rolled out a pilot of an AI knowledge bot in Teams for a global client’s support organisation. During the demo, it answered policy questions and ‘how-to’ queries in seconds, pulling from SharePoint and internal wikis. In the first few months of limited production use, some teams adopted it enthusiastically and saw fewer repetitive tickets, but we quickly hit the realities of scale: no clear ownership for keeping content current, inconsistent access permissions across sites, and a compliance team that wanted tighter control over which sources the bot could search. The bot is now a trusted helper for a subset of curated content, yet the dream of a single, always-up-to-date ‘brain’ for the whole organisation remains just out of reach.
Example 2:
For a consumer brand, we built a web-based customer avatar that could greet visitors, answer FAQs, and guide them through product selection. Marketing loved the early prototypes because the avatar matched the brand perfectly and was demonstrated beautifully at the launch event. It now runs live on selected campaign pages and handles simple pre-purchase questions. However, moving it beyond a campaign means connecting to live stock and product data, keeping product answers in sync with the latest fact sheets, and baking consent into the journey (not bolting it on after). For now, the avatar is a real, working touchpoint, but still more of a branded experience than the always-on front line for customer service that the original deck imagined.
This is the ‘last mile’ problem of AI: the hard part isn’t intelligence – it’s operations. Identity and permissions, integration, content ownership, and the discipline to run the thing under a service-level agreement (SLA) are what decide whether a pilot becomes normal work. Real impact only happens when we deliberately weave AI into how we already deliver infrastructure, platforms and business apps.
That means:
- Embed AI where work happens, such as in ticketing, CRM, or Teams, and not in experimental side portals. This includes inside the tools that engineers, agents and salespeople use every day.
- Govern the sources of truth. Decide which data counts as the source of truth, who maintains it, and how we manage permissions across wikis, CRM and telemetry.
- Operate it like a core platform. It should be subject to the same expectations, such as security review, monitoring, resilience, and SLA, as core platforms.
- Close the loop by defining what engineers, service desk agents or salespeople do with AI outputs, how they override them, and how to capture feedback into our processes.
This less glamorous work is where the real value lies: turning a great demo into a dependable part of a project. It becomes a cross-functional effort, not an isolated AI project. That’s the shift we need to make; from “let’s try something cool with AI” to “let’s design and run a better end-to-end service, with AI as one of the components.”
From demos to dependable services
A simple sanity check for any AI idea is: would it survive a Monday morning? This means a full queue, escalations flying, permissions not lining up, and the business demanding an answer now. That’s the gap the stories above keep pointing to. AI usually doesn’t fall over because the model is ‘bad’. It falls over because it never becomes normal work, or in other words, something we can run at 2am, support under an SLA, and stand behind in an audit.
If we want AI work to become dependable (and billable), we should treat it like any other production service from day one: name an owner, lock the sources, define the fallback, and agree how we’ll measure success.
- Start with a real service problem, not a cool feature. Tie it to an SLA, a workflow step, or a customer journey moment.
- Design the last mile early. Where will it live? Is it in ticketing, CRM, Teams, or a portal? What data is it allowed to touch? What’s the fallback when it’s wrong?
- Make ownership explicit. Who owns the content, the integrations, and the change control after the pilot glow wears off?
- Build it with the people who’ll run it. Managed services, infra/PaaS, CRM/Power Platform, and security in the same conversation early – because production is where all the hidden requirements show up.
When we do these consistently, AI ideas stop living as side demos and start showing up as quiet improvements inside the services people already rely on – reliable, supportable, and actually used.
Tech News
HASHGRAPH VENTURES COMPLETES FIRST CLOSE, CEMENTING ABU DHABI’S POSITION AS A GLOBAL HUB FOR WEB3 AND AI INNOVATION
Hashgraph Ventures, an Abu Dhabi–based venture capital fund regulated by the Financial Services Regulatory Authority (FSRA) within Abu Dhabi Global Market (ADGM), today announced the successful first close of its Web3 and AI early-stage venture capital fund. This marks Hashgraph Ventures’ capacity to start capital deployment towards founders and entrepreneurs who are redefining the Web3 economy.
The announcement was made during Abu Dhabi Finance Week (ADFW), where Hashgraph Ventures also hosted its official launch event with over 150 guests. The gathering brought together senior government officials, tier-one venture capitalists, global law firms, digital asset leaders, and many of the region’s most influential investors and founders. The strong turnout underscores Abu Dhabi’s accelerating emergence as a world-class destination for digital asset innovation and institutional-grade venture formation.
In 2024, Hashgraph Ventures received its fund management license by the ADGM Financial Services Regulatory Authority (FSRA) and launched its USD100 million global venture capital fund (Hashgraph Venture Fund-I) out of ADGM. As part of its investment framework, Hashgraph Ventures aims to fund blockchain and deep technologies, focusing on Seed, Series A, and Series B stages and backing founders and entrepreneurs who are driving the next era of digital transformation.
As part of its active deployment strategy, Hashgraph Ventures also confirmed its participation in the seed round of Bloxtel, a next-generation telecom infrastructure company leveraging tokenized eSIM (“dSIM”) and blockchain-enabled 5G access points to radically simplify and decentralize private network deployment. Bloxtel is led by the founders of Simless — creators of the original eSIM technology now used in modern smartphones.
Kamal Youssefi, Co-Founder and Executive Chairman of Hashgraph Ventures, said: “This marks a defining moment for Hashgraph Ventures and for the region’s investment and innovation landscape. The first close of our regulated fund and strategic investment in Bloxtel reflects our commitment to backing frontier technologies that will shape the next era of digital infrastructure. Abu Dhabi has become a global hub for visionary founders, investors, and policymakers — and we are proud to contribute to its rise as the world’s leading hub for Web3, AI, and decentralized networks.”
Dara Campbell, Senior Executive Officer of Hashgraph Ventures, added: “This has been a monumental week for our firm. To complete our first close and announce a sector-defining investment during Abu Dhabi Finance Week — one of the most influential global finance gatherings — sends a clear message about our intent and ambition. Hashgraph Ventures is building a world-class investment platform from Abu Dhabi, for the world. Our momentum reflects both the strength of this ecosystem and our long-term commitment to shaping the future of digital infrastructure from here in the UAE.”
Tech Features
WHY LEADERSHIP MUST EVOLVE TO THRIVE IN AN AI DRIVEN WORLD
By Sanjay Raghunath, Chairman and Managing Director of Centena Group
Leadership today is being reshaped not by technology alone, but by the pace at which the world around us is changing. Conventional leadership models built on rigid hierarchies, authority, and control are no longer sufficient in an era defined by artificial intelligence, automation, and constant disruption. What organisations need now is a more human-centric model, adaptive, and grounded form of leadership.
As digital transformation accelerates, the role of a leader has fundamentally shifted from imposing authority. Leadership is no longer about issuing directions from the top; it is about guiding organisations and people through uncertainty with clarity and confidence. In an AI-driven world, effectiveness does not come from being the most technical person in the room, but from understanding how technology reshapes industries and how to integrate it responsibly to create long-term value.
The economic impact of AI is already undeniable. Reports suggest that AI could contribute up to USD 320 billion to the Middle East’s GDP by 2030, with the UAE alone expected to see an impact of nearly 14 per cent of GDPby that time. Globally,PwC estimates that AI adoption could increase global GDP by up to 15 per cent by 2035. These numbers signal more than opportunity, they signal inevitability. Leaders who cling to static models and resist change risk being overtaken as industries evolve around them.
One of the most persistent challenges in leadership today is resistance to change. When leaders rely on outdated hierarchies and familiar ways of working, organisations struggle to respond to volatility. What worked yesterday may no longer work tomorrow. Flexibility, once considered a desirable trait, has become a necessity for survival. Ignoring change is no longer an option.
At the same time, expectations of our colleagues have shifted significantly. People today seek more than compensation or career progression. They are looking for purpose, belonging, and leaders who communicate with transparency rather than authority. This shift is reinforced by the 2025 Employee Experience Trends Report, which draws on feedback from 169,000 employees. The findings show that belonging and purpose are now among the strongest drivers of engagement, while AI-related anxiety and change fatigue are growing concerns within the workforce.
These factors highlight the role of authentic human connection in leadership. One of the critical elements in this regard is emotional intelligence (EQ), which enables leaders to build trust, inspire confidence and form meaningful relationships with their teams. While data, analytics, and AI can inform better decisions, it is empathy that sustains relationships and credibility. Leaders who lack emotional awareness often appear distant, making trust difficult to establish and sustain.
In an era of advanced technologies such as AI, automation and chatbots, there is a prevailing fear about technology overtaking the human role. It is the leadership’s responsibility to instil confidence in people that technologies are designed to enhance human capability, not to diminish it. Technology must be positioned as an enabler. Even though the pace of this transformation can be exhausting, leaders must navigate this challenge with renewed energy and a clear strategy to guide their organisations.
Today, leadership that is adaptable, collaborative, and emotionally aware is proving far more effective than traditional command-and-control models. The transition is from exercising authority to creating genuine connections. Strong leaders integrate change into their strategies while keeping people at the centre of their organisations, while viewing technological innovations as a partner rather than a threat.
Investing in people is not optional, as roles continue to evolve and skill requirements change. Our colleagues must feel valued and supported, as recognition and empathy contribute to boosting engagement and innovation. Empathic leadership helps bridge the gap between market demands and individual needs. Listening with intent, understanding context and responding with genuine concern are no longer additional qualities, they are essential leadership competencies.
The future belongs to leaders who blend clear thinking with empathy, who remain grounded in the present while envisioning bold possibilities and driving innovation forward without eroding trust. In this AI-driven age, success depends on how leaders balance innovation with trust. Leadership is neither about resisting change nor surrendering to it entirely. It is the ability to guide people through uncertainty with emotional depth and stability, recognising that true authority is not earned through control, but through the strength of human connection.
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