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 News
MIDDLE EAST CONFLICT DRIVING A SURGE IN SCAMS, DEEPFAKES, AND GOVERNMENT IMPERSONATION

Cybercriminals don’t wait for the dust to settle. As conflict escalates across the Middle East, a parallel threat has emerged targeting ordinary people through their inboxes and social media feeds.
On 4 March, the UAE Ministry of Interior warned the public about fraudulent emails impersonating government emergency services, falsely claiming that residents must complete a mandatory registration form to receive state support or insurance coverage. The emails bore hallmarks of official government communications, making them convincingly deceptive. They are designed to exploit fear, urgency, and the instinct to comply with perceived authority. These messages are already circulating.
Alongside financial scams, verified fact-checkers have identified AI-generated and mislabelled footage circulating online as supposed evidence of attacks in the UAE. This includes video from Bahrain that was picked up by international media outlets and incorrectly broadcast as a Dubai drone strike. Fabricated videos of the Burj Khalifa collapsing, AI-generated missile strike imagery, and decade-old footage repackaged as current events have also circulated widely. In another example, a supposed “before and after” satellite image of Dubai showing smoke rising over the city was mislabelled — the image was actually from Sharjah, the neighbouring emirate. In many cases, the content spread faster than the corrections. Dubai Police have warned that sharing unverified information can carry criminal penalties under UAE law, including fines of no less than AED 200,000. Despite these warnings, the flow of misleading content has not slowed.
KnowBe4 warns patterns observed during previous conflicts and crises, including the war in Ukraine and the COVID-19 pandemic, the public should also expect charity and donation scams exploiting humanitarian concern, phishing emails disguised as embassy or government alerts, and deepfake imagery engineered to provoke fear or spread disinformation.
Dr. Martin Kraemer, CISO Advisor at KnowBe4 said, “Crises are the most reliable recruitment tool bad actors have. When people are frightened and searching for information, they are not necessarily looking for the truth. They are looking for confirmation of what they already fear. That is exactly what scammers and disinformation actors exploit. What we are seeing right now, fake government emergency emails, mislabelled footage, AI-generated imagery, is not random. It is targeted, and it is designed to exploit the gap between what people feel and what they know. The antidote is not panic. It is discipline: pause, question the source, and go directly to official channels before acting on anything. That’s precisely how governments and organizations are educating people to react in stressful situations.”
What the Public Can Do Right Now
KnowBe4 urges residents, travellers, and anyone following events in the region to apply the following principles:
- Treat urgency as a warning sign. Any message that pressures you to act quickly, register now, donate immediately, confirm your details before midnight, is likely designed to stop you thinking clearly.
- Verify before you share. Before forwarding footage or information, check whether it has been verified by a reputable news outlet or official source. Reverse image searches take seconds and can prevent significant harm.
- Go directly to official sources. If you receive communications claiming to be from a government ministry, embassy, or emergency service, navigate directly to their official website rather than clicking any link in the message.
- Question what you see. AI-generated imagery has reached a level of quality where video alone is no longer reliable evidence. Look for verification from multiple credible sources before drawing conclusions.
- Report suspicious communications. In the UAE, suspected scam emails or messages should be reported to the relevant authorities. Do not engage with the sender.
Tech Features
WHY SECURITY MUST EVOLVE FOR THE HYBRID HUMAN-AI WORKFORCE

By Javvad Malik, Lead CISO Advisor at KnowBe4
There is a specific moment in every security professional’s career when they realise the traditional rulebook hasn’t just been ignored—it’s been torn to pieces. Mine arrived last week while watching a colleague engage in a debate with an AI agent over expense policy, while simultaneously being phished by what was almost certainly another AI posing as IT support.
For decades, the cybersecurity industry has clung to a comfortable, binary premise: humans work inside the walls, threats exist outside, and our job is to keep the two apart. It was a tidy worldview that made for excellent spreadsheets, even if we knew it was fiction.
Then, AI walked into the office without knocking. It’s a reboot of the classic 2010 iPad launch, where executives demanded connection to the corporate network, heralding the age of “Bring Your Own Disaster”.
The Multi-Species Workforce
The most uncomfortable truth facing modern organizations is that they no longer employ just humans.
Your current headcount includes Peter from Accounts Payable, his three AI assistants (two sanctioned, one very much ‘shadow’), a recruitment algorithm, and whatever experimental automation Marketing has hooked up to Slack to bypass a slow internal process.
They are all making decisions. And they are all sharing data.
When Peter’s AI hallucinates a rogue clause into a vendor agreement, or a chatbot leaks PII because a prompt-engineer asked nicely, where does the buck stop? Traditional security loves clean lines—User vs. Admin, Internal vs. External. But we are now operating in a world that has gone full analogue. We have created a workforce that is part human and part silicon, yet the risk remains entirely ours to manage.
The Futility of Punitive Security
Historically, we have managed security like a digital Alcatraz. If a user clicks a phishing link, we chastise them. If they use unapproved software, we discipline them.
But punishing people for being human is like shouting at water for being wet. It provides a few seconds of emotional release for the security team, but it doesn’t change the outcome. You cannot discipline your way to a secure culture, and you certainly cannot punish an AI agent into making safer choices.
So, what happens when your workforce is 60% human, 40% AI, and rising?
Navigating the Shadow AI Explosion
Shadow AI isn’t born from malice; it’s born from friction. Employees use unsanctioned tools because the approved versions are often slow, restrictive, and designed by people who think ‘user-friendly’ as a type of malware.
If your IT ticket for an AI request won’t be resolved until Q3 2027 but the free version of ChatGPT is open in a browser tab right now, the choice for a busy employee is a foregone conclusion.
To manage this hybrid reality, we need to view the workforce as a single, unified, complex adaptive system. Here is the framework for securing the blur:
- Govern the Decision, Not the Entity: We need governance frameworks that apply to the action, regardless of whether the actor is carbon-based or cloud-hosted. If a human isn’t allowed to export customer data to a personal drive, their AI assistant shouldn’t be able to either.
- Design for Invisible Perimeters: Assume you will never have 100% visibility again. Security must shift toward real-time behavioral monitoring and anomaly detection that tracks patterns across both human and machine activity.
- Build Intuitive Culture, Not Just Compliance: You teach a child to cross the road by explaining traffic lights, not by screaming at them every time a car passes. The same applies here. You cannot train culture into an AI model, but you can design systems where humans and AI operate within a framework that makes security intuitive.
- Treat Shadow AI as a Signal: If half your workforce is using unsanctioned AI, that isn’t a compliance failure—it’s a sign your current tools are failing your people.
The question is no longer if your workforce will become a hybrid of human and machine. It already is.
The real question is whether our security models will evolve to meet this reality, or if we will keep building expensive walls around a perimeter that vanished years ago. The workplace has changed; our job is to design security that works with human nature, rather than against it.
Tech News
ALTERYX ACCELERATES ITS NEXT PHASE OF GROWTH WITH AI-READY DATA AND AUTOMATION AT ENTERPRISE SCALE

Alteryx a leading AI-ready data and analytics company, has announced its next phase of growth, surpassing $1 billion in ARR and powering more than 380 million automated workflows annually. As enterprises shift from AI experimentation to full-scale execution, demand for trusted automation and AI-ready data has never been higher. With Alteryx One, organizations are operationalizing AI responsibly and accelerating enterprise-scale decision-making.
Enterprises continue to invest heavily in AI, with 89% planning to maintain or increase spending in 2026, as generative and agentic AI technologies promise a transformative impact. Yet trust remains a critical barrier: 28% of organizations report limited or no confidence in the accuracy and quality of their data. In the UAE alone, 94% of data leaders say they lack complete visibility into AI decision-making processes. Reliable data and repeatable workflows have become the foundation for operationalizing AI successfully.
To address these challenges, Alteryx One brings together this strategy — a single platform trusted by thousands of customers that connects data, business context, and AI for insights.
Scaling AI and Automation with Alteryx One
McKinsey & Company puts AI adoption at ~84% across surveyed orgs in the Middle East region. Against this backdrop, data remains the defining factor. As per Alteryx research, nearly half (49%) of leaders cite high-quality, accessible, and well-governed data as the top requirement for AI to reach its full potential. To meet this, Alteryx One provides a trusted logic layer, a governed, repeatable workflow that captures business logic, preserves lineage, and produces AI-ready outputs.
Adoption of Alteryx One is accelerating, with thousands of customers upgrading to the new, simplified edition pricing model, making it easier to access advanced AI and automation capabilities. Built-in enterprise security and governance provide the controls organizations need to scale. By seamlessly connecting to enterprise data sources, AI models, and business applications, Alteryx One delivers trusted, governed data wherever it’s needed.
Andy MacMillan, CEO of Alteryx, said: “When automation becomes agentic, inconsistency is no longer just inefficient. It becomes an enterprise risk. AI requires a governed and repeatable logic layer. Without that foundation, organizations don’t just move faster — they scale risk faster than productivity. Alteryx is purpose-built for this next phase, giving enterprises the control, transparency, and confidence to operationalize AI, and giving lines of business the flexibility they need to adapt and change.”
In 2025, Alteryx also celebrated 10 years of its global Community, which now includes more than 750,000 members worldwide. Community members have shared thousands of peer-driven solutions, workflows, and best practices, helping organizations accelerate onboarding, scale analytics initiatives faster, and maximize the value of Alteryx One.
Automation at Enterprise Scale
The need for reliable, scalable automation has never been more evident. In 2025, Alteryx customers executed more than 380 million automated workflows, up from more than 260 million in 2023, highlighting how organizations are moving beyond experimentation to governed, enterprise-wide automation that operationalizes analytics.
Alteryx enables organizations to extend automation into new generative AI use cases while maintaining explainable, auditable outputs aligned with enterprise compliance standards. Users can interact with data using natural language, accelerate model development, and embed AI-driven insights directly into trusted workflows — helping organizations scale innovation without sacrificing control.
Business Performance
In 2025, the company surpassed $1 billion in ARR, signaling strong enterprise adoption and long-term customer commitment. Alteryx was also recognized in G2’s 2026 Best Software Awards for Best Analytics Software Products.
In parallel, Alteryx has expanded its cloud data platform ecosystem, including a deepened partnership with Google Cloud that enables customers to work directly with cloud-scale data and accelerate analytics and AI initiatives in modern cloud environments.
The company also introduced a refreshed brand identity reflecting its evolution into a unified platform for AI-powered analytics and enterprise-scale automation. With Alteryx One at the center, the company is redefining how enterprises scale AI and automation responsibly, providing the trusted foundation needed to drive intelligent outcomes.
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