AI hits the road: Putin ordered the implementation of neural networks in public transport in Russia
Vladimir Putin, during a meeting of the Presidium of the State Council held via video conference from Ulan-Ude, issued an instruction to fundamentally revise approaches to public transport management in Russia. The key emphasis is on the introduction of artificial intelligence technologies for forecasting passenger flows, optimizing schedules, and route networks. In my assessment, this is not just modernization, but an attempt to create a fundamentally new system where data and algorithms will become the basis for decision-making.
What exactly the president instructed
The head of state outlined priorities that will form the foundation of the industry's work in the coming years. This is not only about AI, but also about introducing unified service quality standards. To date, only 34 federal subjects have adopted such standards — that is less than half of the regions, which is clearly insufficient. Putin instructed the government, together with the State Council, to develop for the remaining subjects a clear list of indicators by which the effectiveness of transport operations will be assessed.
These benchmarks will make it possible to objectively compare the quality of service in different regions and will create a transparent assessment system for the authorities.
In addition, the president instructed that changes be made to the national project "Infrastructure for Life," filling it with specific, measurable goals. This effectively means that regions will now report not with abstract promises, but with concrete figures.
The AI market in Russia: figures and prospects
The president's instruction logically fits into the overall growth trend of the Russian AI market. At the end of 2025, it grew by 29.7% and reached 316.1 billion rubles. Forecasts by AIANA analysts suggest that by 2030 the market volume will grow to 830 billion rubles, and under a favorable scenario — to 1.12 trillion rubles. This is one of the fastest-growing sectors of the economy, and transport is becoming an important point of application for it.
It is telling that the introduction of generative neural networks is already producing a tangible macroeconomic effect. According to Sber's estimates, 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, but management and logistics processes will be transformed first.
In parallel, the state is also building the legal framework: a working group on copyright has already been established under the government, which will determine the conditions for training models on protected content and the rules for ownership of generated materials. This is a critically important step for legitimizing the entire industry.
My view: The initiative is timely, but success will depend on how quickly quality standards and AI tools reach the actual regions, rather than remaining on paper. Transport is a sphere where algorithms can deliver a fast and measurable effect, but this requires not only the will of the center, but also competencies on the ground.