UAE Bets Big on AI: Plans to Run Half of Federal Government With Agentic Systems Within Two Years

The United Arab Emirates has announced an ambitious plan to deploy agentic artificial intelligence across roughly half of its federal government operations within two years. The move is one of the fastest and most extensive government AI rollouts announced to date and shifts the role of AI from advisory to operational in public services.

What Is Agentic AI?

Agentic AI refers to systems that do more than analyze or recommend: they can interpret information, make autonomous decisions and take actions with minimal human intervention. In a government context, these systems could process applications end-to-end, dynamically adjust workflows and respond in real time to changing demand.

Rollout, Oversight and Metrics

The UAE has framed the initiative as a structured, metrics-driven program. Every ministry and federal entity will be evaluated on adoption speed, quality of implementation and how effectively processes are redesigned around AI systems. Oversight of the initiative is assigned to Mansour bin Zayed Al Nahyan, while a task force chaired by Mohammad Al Gergawi will manage day-to-day execution.

Workforce Development

A major non-technical component of the plan is staff training: every federal employee will receive AI training so they can work alongside intelligent systems. Officials say the goal is to reskill the workforce to supervise, manage and collaborate with automated systems rather than be displaced by them.

Potential Benefits

Proponents say agentic AI could speed up permit approvals, reduce bureaucratic bottlenecks, automate routine services and enable systems that adapt instantly to demand. If implemented well, the program could deliver faster outcomes for residents and businesses and position the UAE as a global leader in large-scale government AI deployment.

Risks and Open Questions

Rapid adoption raises substantial concerns. Accountability is a core issue: when autonomous systems make operational decisions, tracing responsibility for errors or harms can be complex. Privacy risks rise as AI systems may increase data collection, analysis and retention. Bias is another worry: models trained on imperfect or incomplete data can produce unfair or unequal outcomes in service delivery or enforcement. Finally, public trust matters—citizens may resist decisions made by machines, especially when transparency and appeals are limited.

Global Implications

The UAE’s timeline and scale create a possible benchmark for other countries. Success could prompt governments worldwide to accelerate AI adoption in public services; failures could serve as cautionary lessons about transparency, governance and the need for robust safeguards. Subnational governments in other countries—where experimentation is easier—may pilot similar approaches first.

Conclusion

The UAE’s plan to make AI an operational partner across half of its federal government is a high-stakes experiment. It highlights both the promise of faster, more responsive public services and the unresolved questions about oversight, data use, fairness and trust that accompany entrusting machines with consequential public decisions.