Why the GCC might have an edge on implementing Agentic AI

Not long ago, a loan officer at a Middle Eastern bank spent two days processing a single mortgage application. Know Your Customer (KYC) verification meant hours of manual document checks, cross-referencing databases and waiting for approvals. Today, that officer completes the process in under four hours, not because she works faster, but because an AI agent handles the verification and flags only exceptional cases for human review.

So, what happens to the hours she wins back? She might analyze fraud patterns AI agents cannot interpret, mentor junior colleagues or spend more time with clients. The work hasn’t disappeared; it has shifted toward judgment, empathy, cultural intelligence and trust.

While the world experimented with AI assistants and chatbots in 2023 and 2024, 2025 marked a clear inflection point in the Gulf Cooperation Council (GCC), comprised of the UAE, Saudi Arabia, Qatar, Kuwait, Bahrain and Oman. New national AI frameworks, sovereign cloud rollouts and the first wave of enterprise deployments pushed Agentic AI from concept to practice.

AI agents not only respond to prompts but perceive their environment, make decisions and take coordinated action with humans “on the loop,” are now a reality.

A 2025 study by e& and AWS, which surveyed 226 GCC organizations with more than 100 employees across five industries, examined how enterprises are approaching this transition.

Adoption is accelerating quickly. Globally, one-third of organizations have begun scaling traditional AI programmes. In the Gulf, recent findings show that 19% of organizations have already moved from pilots to full-scale implementation of Agentic AI, with 74% planning adoption. At these organizations, human responsibilities now centre on setting strategic priorities, interpreting AI-generated insights, upholding ethical standards and stepping in when exceptional situations require intervention.

Across the region, organizations are moving from exploration to meaningful scale, supported by GCC-wide structural strengths. The research shows that 83% of Gulf organizations are already investing in AI, underpinned by unified national strategies and a decision-making culture where CEOs and C-suite leaders drive adoption. This alignment among government, regulators and enterprises removes friction and is helping the region turn early momentum into a credible pathway to global leadership.

The GCC also has substantial infrastructure advantages. Sovereign-by-design cloud zones across the UAE, Saudi Arabia and Bahrain keep sensitive data within national borders. They are encrypted by default and auditable in real time. This reduces the jurisdictional complexity that hampers cross-border data flows and gives regulators and enterprises a standardized framework when AI agents handle information.

Another advantage lies in the region’s coordinated approach to national visions, industrial strategies and regulatory development. Governments, regulators and enterprises often move in the same direction at the same time, shortening decision cycles, accelerating standards and simplifying compliance. This creates an environment where Agentic AI can scale with fewer structural obstacles. Still, common principles do not eliminate ambiguity, and adoption can be chaotic. It falls to organizations to navigate the transition with clarity and intent.

Regulatory agility is emerging as another first-mover strength. Gulf regulators are demonstrating a willingness to introduce AI guidance quickly, iterate with industry and adjust rules as system behavior evolves. This creates predictability for enterprises that want to deploy Agentic AI at scale. Faster regulatory response makes early adoption less risky and more strategic.

The region is also building Agentic AI frameworks from first principles, supported by institutions that can set direction, unify incentives and act quickly. When a federal government entity in the UAE deployed AI agents to let citizens retrieve information in natural language, responses became faster and more consistent, backlogs declined and staff shifted from routine requests to complex policy development and citizen engagement.

According to the same study, accuracy rose by 70% when an oil and gas company used AI agents to analyze seismic data. Geologists gained the space to interpret patterns and steer exploration strategy using experience that only years in the field can provide.

This shows that organizations succeeding with Agentic AI are not necessarily the ones with the most advanced technology. They are the ones investing in three critical, interconnected areas: trust, training and transformation.

They are building trust by treating AI agents as accountable digital workers with defined roles and decision rights. They are investing in training that goes beyond technical skills to develop judgment, contextual understanding and adaptive leadership. And they are pursuing genuine transformation, redesigning work rather than simply automating existing processes.

Across the Gulf, AI agents are detecting network anomalies and executing remediation protocols in IT operations centres. Customer service teams rely on multilingual agents that handle routine inquiries in Arabic, English and Urdu while escalating culturally sensitive issues to humans. Compliance divisions use agents to monitor regulatory changes and generate documentation while specialists focus on strategic risk interpretation.

These systems are delivering measurable outcomes, including higher productivity and processing times reduced from days to hours. Early adopters recognize that Agentic AI is a workforce transformation that demands organizational courage.

But success requires more than awareness; it requires targeted action. Trust, training and transformation must guide deployment. Emerging Gulf approaches to human-in-the-loop oversight suggest a model of autonomy that can strengthen institutional roles while expanding how people contribute to decision cycles. Clear escalation paths must address system failures. Accountability should be shared across engineers, enterprises and overseers, and sovereign data layers should continue supporting traceability and compliance. Workforces need investment in judgment, context and trust. AI agents should operate within defined identities, access rules and decision boundaries.

If the region commits to this model, it can set a global benchmark for Agentic AI that protects sovereignty and enhances human capability, ensuring that the hours reclaimed across industries, like the loan officer who moved from two days of paperwork to four hours of oversight, are consistently redirected toward higher-value contributions.