Putin accelerates the adoption of AI in public transport: a new vector of Russia's technological policy
Russian President Vladimir Putin has sent a clear signal about the need for large-scale application of artificial intelligence in public transport. This is not just a targeted initiative, but part of a systemic strategy for the digital transformation of key economic sectors.
During a working trip to Ulan-Ude, the head of state held a videoconference meeting of the Presidium of the State Council dedicated to the development of the transport sector. The key point is the use of machine learning algorithms to forecast passenger flows, optimize schedules, and build efficient route networks. According to the president, such tools can radically improve the efficiency of the entire industry, which today faces serious challenges from urbanization and growing population mobility.
Priorities and quality standards
Special emphasis was placed on introducing unified service quality standards. To date, only 34 federal subjects have adopted relevant regulations—this is clearly insufficient to create equal conditions for citizens across the country. The government, together with the State Council, will need to develop a list of indicators by which regional performance in the transport sector will be assessed. Moreover, these benchmarks should be integrated into the national project "Infrastructure for Life," which will synchronize efforts at the federal and regional levels.
AI market: figures and forecasts
The president's initiative fits into the broader context of the rapid growth of the Russian artificial intelligence market. At the end of 2025, its volume increased by 29.7%, reaching 316.1 billion rubles. According to the baseline scenario of the analytical agency AIANA, by 2030 the market will grow to 830 billion rubles, and under an optimistic scenario—to 1.12 trillion rubles. This confirms that the state views AI not as an abstract technology, but as a real driver of economic growth.
It is telling that the implementation of generative neural networks is already yielding measurable results: according to Sber experts, they add 1.2 percentage points to labor productivity growth, with the greatest effect expected in office professions. Physical labor—drivers, mechanics, loaders—remains outside the direct influence of algorithms, which is important to consider when planning social policy.
In parallel, the state is building a regulatory framework: a working group on copyright has been established under the government, which will determine the conditions for training models on protected content and the ownership rules for generated materials. Transport is becoming another practical platform where AI is used to process large volumes of data in real time.
Expert comment: The decision to introduce AI into the transport sector is a logical step, given that this is precisely where algorithms can deliver a quick and measurable economic effect. However, success will depend not only on technological readiness, but also on the ability of regions to adapt federal standards to local specifics. In the coming years, we will witness how transport infrastructure turns into a testing ground for state approaches to AI regulation, which will inevitably affect adjacent markets, including fintech and logistics.