AI Takes to the Road: Putin Puts Neural Networks at the Service of Russia's Public Transport
Russian President Vladimir Putin has ordered the implementation of artificial intelligence technologies in the public transport system. This is not just a wish, but a strategic direction that should radically improve the efficiency of the entire industry.
During a video conference with the Presidium of the State Council, held in Ulan-Ude, the head of state outlined specific priorities. The focus is on using AI to forecast passenger flows, optimize schedules, and route networks. According to him, this will allow not just improving, but fundamentally transforming the quality of public transport operations.
Special emphasis was placed on standardization. Putin noted that only 34 federal subjects have adopted the necessary quality standards in this area. In this regard, the government, together with the State Council, will need to develop a clear list of indicators for the regions by which the quality of service will be assessed. These benchmarks will serve as the basis for comparing the performance of authorities in the transport sector across the country.
In addition, the president pointed out the need to amend the national project "Infrastructure for Life," filling it with specific measurable goals. This will allow a transition from declarations to a real assessment of the effectiveness of regional transport systems.
The AI Market in Russia: Explosive Growth and New Challenges
This instruction is a logical continuation of the state's course toward the widespread adoption of AI in the economy. The Russian artificial intelligence market is already showing impressive dynamics: in 2025, it grew by 29.7%, reaching 316.1 billion rubles. According to the baseline forecast, the market volume will reach 830 billion rubles by 2030, and under a favorable scenario, up to 1.12 trillion rubles.
The implementation of AI is also transforming the labor market. According to analysts, generative neural networks will add 1.2 percentage points to productivity growth, with the greatest effect expected in office professions. Physical labor—drivers, mechanics, loaders—will remain outside the direct influence of algorithms, which is important for social stability.
In parallel, the state is 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 owning generated materials.
Transport is becoming another platform where AI is applied in practice. Demand forecasting, schedules, and routes are precisely the tasks where algorithms process large volumes of data faster and more accurately than humans.
My view: this instruction is not just an administrative initiative, but a signal to the technology market. The implementation of AI in transport represents a vast layer of data and infrastructure solutions where both large corporations and specialized startups can profit. The only question is how quickly regions can move from pilot projects to systematic implementation, and whether the bureaucratic machine will become a brake on innovation.