Putin mandated the integration of AI into public transport: a new vector for Russia's technological sovereignty.
Russian President Vladimir Putin has issued an order for the systematic implementation of artificial intelligence technologies in the public transport sector. This decision, announced during a meeting of the State Council Presidium, marks another step in the strategy of digitalizing key economic sectors and sets fundamentally new tasks for the regions.
The focus is not merely on automation, but on a radical improvement in the efficiency of the entire transport industry. This involves using machine learning algorithms to forecast passenger flows, optimize schedules, and build route networks. In essence, this is a transition from intuitive management to analytical management, based on processing big data in real time.
Key aspects of the order
Separately, the head of state emphasized the issue of standardizing service quality. To date, only 34 federal subjects have adopted the necessary standards, which is clearly insufficient for the uniformity of the country's transport system. The government, together with the State Council, will need to develop a clear list of indicators by which the performance of regions in this area will be assessed. This will not only allow for comparisons between subjects, but will also create a basis for making changes to the national project "Infrastructure for Life," filling it with specific, measurable targets.
The order fits organically into the overall trend of accelerated AI development in Russia. The Russian artificial intelligence market is showing impressive growth: by the end of 2025, it grew by 29.7%, reaching 316.1 billion rubles. According to the baseline forecast of the AIANA agency, the market volume could grow to 830 billion rubles by 2030, and under a favorable scenario, exceed the 1.12 trillion rubles mark.
Impact on the labor market and regulation
Interestingly, the implementation of AI in the transport sector, contrary to widespread concerns, is unlikely to lead to job cuts for drivers and technical staff. Sber analysts note that generative neural networks will add 1.2 percentage points to productivity growth, with the main effect falling on office professions. Physical labor remains outside the direct influence of algorithms, making the transport sector a kind of testing ground for hypotheses about "soft" automation.
In parallel, the state continues to build the regulatory framework for AI. A working group on copyright is already operating under the government, which should determine the conditions for training models on protected content and the rules for owning generated materials. This is a critically important issue, without solving which further scaling of AI in the commercial and public sectors is impossible.
Cryptalist expert opinion: The initiative to implement AI in public transport is not just modernization, but an attempt to create a precedent for the effective use of algorithms in the infrastructure sector. In my view, the success of this program will depend not on technology, but on the quality of data that regions can provide for training models. Without unified standards and open data, any algorithms will remain merely a beautiful decoration. That is why the order to develop quality indicators seems even more significant than the very idea of implementing AI.