The UAE’s National Experts Programme AI track shortlisted 135 finalists from more than 1,000 applicants in April 2026. The programme is designed to build a national base of artificial intelligence expertise across government, industry and specialised technical fields.
The finalists represented all seven emirates. The selection included professionals from the public and private sectors, with the public sector accounting for the larger share. The programme described the cohort as experienced and academically strong, with participants expected to develop sector-specific, implementation-oriented ideas.
A final group of 25 participants was expected to join the inaugural cohort. The design is significant because the UAE is attempting to build AI capability inside institutions that will have to procure, govern and operate systems. AI adoption depends on engineers, but it also needs leaders who understand sector priorities, data constraints, procurement, workforce effects and risk.
The programme is different from a general training course. Its emphasis is on national experts who can translate AI into projects in priority sectors and connect technical work to public and economic outcomes. That implementation layer is important as the UAE moves from strategy announcements toward wider use of AI in government and industry.
The shortlist does not establish that the participants have delivered production systems or that the programme has generated measurable economic impact. Those outcomes will depend on the capstone projects, institutional sponsorship and whether participants remain involved in AI implementation after the cohort ends.
Future reporting should examine the final cohort, the projects selected, the sectors involved and the measurable results. The programme is still a meaningful signal that the UAE views expert human capital as a core part of its AI strategy.
The programme’s design also recognises that national AI capability is distributed across professions. Policy leaders, domain specialists, engineers, data practitioners and executives each affect whether an AI project is safe and useful. A cohort model can help connect those perspectives around defined sector problems.
The strongest evidence of success will be visible in the projects that receive sponsorship, the institutions that adopt them and the outcomes that can be measured after implementation. Until then, the shortlist is a credible signal of intent and talent selection, not proof of delivered impact.
