Uzbekistan is approaching artificial intelligence on a wave of rapid digitalization: a national AI development strategy has been adopted, the state is building digital public services and the IT Park, and a young mobile-first market gives fintech — Uzum, Click, Payme and the banks — a large volume of data for machine learning. The main question is not about ambitions but about their execution: data, talent, infrastructure and rules will determine whether AI becomes a real tool in finance and public administration or remains a set of pilots. This topic gathers news and context on how AI is entering the country's economy.
A large young audience, mobile-first habits and fast fintech growth create the data and demand where machine learning works best: payments, instalments, e-commerce and services.
Uzbekistan has adopted a national AI development strategy and is building digital public services and the IT Park, counting on AI as an accelerator of the economy and of IT-services exports.
Execution matters more than declarations: access to data and computing, training talent, localization of solutions and the rules for applying AI in finance and in dealings with citizens.
The hub links Uzbekistan's latest materials with the foundational context so that the AI topic is seen as a coherent market rather than scattered announcements.
The government is launching the “AI Partner for 10,000 Enterprises” program with a $100 million budget for its first phase.
The government will allocate additional funds to upgrade its supercomputer cluster for artificial intelligence projects.
The government has signed agreements for private investments in 800 MW of computing capacity. For the financial sector, this provides the physical foundation for local fintech solutions, from heavy credit scoring models to anti-fraud systems.
The Uzbek regulator is deploying artificial intelligence to process documents and automate interactions with financial participants.
In six months, residents paid foreign AI companies 113 billion soums.
The regulator deployed its proprietary Soliq LLM language model and machine learning to analyze business risks and speed up tax administration.
Click expands its service with a typology of financial profiles to personalize offers.
High demand for smart assistants shatters against total distrust in data security.