For businesses, this changes the AI conversation. Success is no longer only about adopting AI software. It is also about modernising data pipelines, improving data quality and making information available across the organisation when it is needed. For many companies, this makes enterprise technology services more important, because AI adoption depends on strong systems, integration, cloud infrastructure and data management.
Key Challenges Still Remain
Despite the strong progress, Gulf enterprises still face significant barriers to wider AI deployment. Nearly three-quarters of IT leaders in the UAE and Saudi Arabia reported facing at least three major obstacles to AI adoption. The most common challenges include insufficient infrastructure for real-time data processing, concerns about data quality and lineage, and shortages of AI and data-related skills.
More than two-thirds of respondents also identified data infrastructure and data quality as major barriers to deploying agentic AI successfully.
These challenges are not unique to the Gulf. They reflect a global issue as companies move from AI experimentation to production. Many organisations have invested in AI tools, but fewer have built the data systems required to support continuous intelligence and autonomous decision-making.
Industry Experts See a Mature AI Ecosystem
Karim Azar, AVP and General Manager at Confluent Middle East, said the findings show that the UAE and Saudi Arabia have moved decisively from AI experimentation into deployment. He said IT leaders in both markets have a clear understanding of what is needed next, especially the importance of data streaming as a strategic priority.
According to Azar, sustaining AI performance at scale requires strong data infrastructure beneath the technology. With major government investment and long-term national vision, he said the Middle East is well positioned to lead the next phase of AI adoption.
Why Data Quality Is Central to Agentic AI
The report also found that 95% of respondents in both countries believe data streaming platforms can help overcome agentic AI deployment challenges by making information more trustworthy, contextualised and discoverable. This is especially important because agentic AI systems are expected to make decisions and take action. The same shift is also visible in consumer technology, as companies like Google move toward an AI assistant model that can complete tasks rather than simply provide answers. If the data behind those decisions is unreliable, the risks become much greater.
Shaun Clowes, Chief Product Officer at Confluent, said many organisations do not have an AI investment problem, but a data problem. He noted that AI systems depend on fresh, accurate and contextual information, while many companies still rely on fragmented data, batch processes and infrastructure not designed for continuous intelligence.
What This Means for Businesses
For businesses in the UAE and Saudi Arabia, the report points to a clear direction: AI adoption must be supported by real-time data infrastructure. Companies that want to benefit from agentic AI will need to invest not only in models and applications, but also in data quality, governance, integration, security and streaming platforms. This shift also connects with the wider use of AI tools for digital marketing, where businesses increasingly need reliable data before they can automate campaigns, customer journeys and decision-making.
This is especially relevant for sectors such as finance, logistics, retail, energy, aviation, government services and healthcare, where autonomous systems could help improve speed, efficiency and decision-making.
However, the more autonomy AI systems have, the more important it becomes to ensure that data is accurate, traceable and properly governed. Strong governance is also becoming more important as AI scams become more convincing and create new risks for UAE businesses.
Final Thoughts
The UAE and Saudi Arabia are positioning themselves at the front of the global shift toward agentic AI. With 38% of organisations in both countries already using agentic AI in production, the Gulf is moving faster than many regions in turning AI ambition into operational reality.
But the report also shows that the future of AI leadership will depend on more than adopting powerful models. It will depend on building trusted, real-time data foundations that allow autonomous systems to make better decisions. In that race, the UAE and Saudi Arabia appear to have gained an early advantage.