Gulf AI uptake outpaces measurable returns

AI uptake in Gulf businesses has surged, with 84 per cent of organisations across the Gulf Cooperation Council now using the technology in at least one business function, up from 62 per cent in 2023. However, the benefits of this adoption are not translating into measurable financial gains. Only 11 per cent of surveyed organisations are considered "value realisers," meaning they have scaled AI deployment and can attribute at least 5 per cent of earnings to the technology.

The majority of companies are still in the early stages of AI deployment, with only 31 per cent reaching a stage where AI is fully scaled or deployed across the enterprise. This discrepancy highlights a gap between experimental AI use and actual value creation. The root cause may lie in fragmented technology estates, where data remains trapped in legacy systems and governed inconsistently.

Companies often struggle to integrate disparate datasets, reconcile duplicate information, and repair poor-quality records before AI tools can work reliably at scale. This "silent AI tax" adds to the operational burden, creating extra costs and complexity. Google Cloud research indicates that 55 per cent of global executives face operational limits due to fragmented information, and only 45 per cent of enterprise data can be accessed by AI systems on average.

Trusted business context is becoming a key bottleneck for companies attempting to move AI from pilots into production. While many Gulf companies expect AI budgets to increase, the challenge now shifts from securing executive support to proving that the investment can generate dependable commercial outcomes at scale. Effective AI adoption requires clear business objectives, stronger technology architecture, data management, talent, and change-management practices.

Data quality is particularly crucial, especially with the rise of generative and agentic AI systems. Weak controls can lead to errors spreading more quickly, as automated systems may draw from inconsistent records or act on unclassified, unvalidated, or outdated information. Addressing these weaknesses in data infrastructure and governance is essential before expanding AI deployments.

However, a 2025 GCC Board Directors Institute review reveals that only 5 per cent of respondents have a fully implemented AI adoption plan, despite growing board-level attention to the technology. The institute attributes this to limited expertise and skills gaps, underscoring the need for stronger governance standards and improved data quality to support effective AI oversight.