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UAE Leads in AI Agent Deployment as Enterprises Face Control Challenge

The UAE leads surveyed markets in large-scale agentic AI deployment, with enterprises running hundreds of agents while governance, visibility and rapid containment remain key challenges as adoption accelerates across sectors.

Written By : Poulami Saha
Reviewed By : Pranchal Srivastava

The UAE is emerging as a leading market for large-scale agentic AI deployment, with enterprises running significantly more AI agents in production than organisations in other markets surveyed by Dataiku. The findings come from a new Dataiku study conducted by Harris Poll among 685 CIOs across eight countries.

UAE Enterprises Scale Up AI Agent Deployment

The research shows that 62% of UAE CIOs estimate their organisations have more than 50 AI agents operating in production. Around 15% report running more than 500 agents, the highest share among the markets surveyed and above the 9% global average.

The expansion is also driving demand for specialised talent. Among UAE organisations creating or planning embedded AI expert and forward-engineering roles, 22% expect to hire more than 10 people over the next year. This represents the highest proportion recorded in the study.

The rapid expansion of agentic AI did not translate into a similar level of reported business damage. However, 62% said, “ Such behaviour was detected before it caused customer, financial, compliance or operational damage.” Only 18% reported actual impact, compared with 31% globally. 

Containment Remains a Major Challenge

Detection does not necessarily mean organisations can quickly stop problematic AI agents. Only 5% of UAE CIOs said they could reliably identify and contain a problematic agent across environments within one to two hours.

About 27% could intervene later the same day, while 45% said containment could take between 24 and 48 hours. Another 23% estimated that they would need two days or more.

The study also found that only 18% of UAE CIOs have a fully unified view of agents across platforms, data environments and business applications. The findings underline a broader shift from AI experimentation to enterprise-scale deployment. 

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