Turkey Sets $10 Billion AI Plan, Targets 5 Million Trained

Turkey has laid out a national artificial intelligence strategy for 2026 to 2030 that pairs mass workforce training with an aggressive buildout of computing infrastructure, according to details of the government's action plan shared in June 2026.

The plan sets a goal of training five million people in basic AI literacy within two years, backed by a program running across all 81 provinces of the country. It also calls for preparing 100,000 professionals capable of applying AI tools in their fields and a smaller group of 10,000 advanced specialists meant to work on frontier research and development.

On infrastructure, the government wants to mobilize at least $10 billion in investment for data centers, cloud computing, and related AI infrastructure, with the private sector expected to supply most of that capital rather than the state itself. The plan pairs that funding target with a physical benchmark: raising the country's data center compute capacity to at least 1 gigawatt by 2030.

A data access component rounds out the strategy. Officials plan to open at least 2,000 government datasets through a national data library spanning sectors including health, agriculture, defense, and e-commerce, giving companies and researchers a broader base of public data to build models on.

Why the numbers matter

The gap between the workforce targets is deliberate. Training five million citizens in general AI literacy is a scale problem aimed at broad economic readiness, while the much narrower cohorts of 100,000 applied professionals and 10,000 advanced experts point to a more targeted bet on building domestic technical capacity rather than relying solely on imported talent or foreign vendors.

The 1-gigawatt compute target places Turkey among a growing list of mid-sized economies racing to secure domestic AI infrastructure rather than depending entirely on cloud capacity hosted abroad. Leaning on private capital to fund most of that buildout also shifts execution risk toward companies willing to bet on demand for local AI services and data residency requirements.

Opening thousands of government datasets could prove to be the plan's most consequential piece for developers and startups, since access to structured public data in areas like health and agriculture is often the binding constraint on building useful, locally relevant AI applications rather than compute or funding alone.

None of the reviewed material describes how the plan will be financed beyond the private-sector investment target, nor does it specify which ministries or agencies will oversee implementation of the individual training and infrastructure programs.