The AI market in Russia: rapid growth to 830 billion rubles by 2030 and a paradigm shift
The Russian artificial intelligence market is demonstrating impressive momentum: by the end of 2025, its volume grew by 29.7% and reached 316.1 billion rubles. Over two years, the figure has doubled, indicating a qualitative shift in the industry's maturity.
Behind these figures lies not just quantitative growth, but structural transformation. Analysis shows that companies are moving from large-scale equipment purchases to renting computing capacity and implementing ready-made solutions. This is a classic sign of the market transitioning from the infrastructure investment phase to the operational efficiency phase.
Three scenarios until 2030
My baseline forecast assumes the persistence of current macroeconomic conditions—a high key rate and the existing level of geopolitical tension. In that case, the market volume will reach 830 billion rubles by 2030. However, this is only the average scenario.
The optimistic scenario raises the bar to 1.12 trillion rubles. Three key factors are needed to achieve this: easing of monetary policy, a reduction in geopolitical risks, and the development of a domestic technological base. It is especially important that domestic solutions extend beyond the internal market—export potential will become a growth catalyst.
The conservative scenario caps the volume at 582 billion rubles. Here, I factor in intensified sanctions pressure, a higher key rate, and limited access to foreign computing resources, infrastructure, and models. In such a case, costs rise, prices for end products increase, and demand for AI services slows down.
Notably, the five-year horizon looks different from the perspective of industry players. AI infrastructure will increasingly move to the cloud, the market will begin to consolidate, and truly large technology corporations will emerge. This is a natural evolutionary process for any mature tech market.
What lies behind the forecast figures
The accelerated shift toward renting capacity reflects a broader state pivot to sovereign infrastructure. Domestic models are increasingly being trained on internal data arrays rather than foreign sources. A telling example is the initiative to train sovereign AI models on Russian scientific developments. This approach reduces dependence on foreign datasets and fits within conservative assumptions about limited access to external resources.
In parallel, the issue of data security is being addressed. Large technology companies are building protection for the data arrays on which their neural networks operate. The regulatory environment is also adapting: the government has formed a dedicated working group to define rules for using copyrighted content in model training and the ownership framework for generated materials.
AI adoption is also affecting the labor market. According to Sber's estimates, generative technologies add 1.2 percentage points to productivity, primarily in office professions, while physical labor remains outside the direct influence of algorithms.
My verdict: the Russian AI market is at a bifurcation point. The baseline scenario of 830 billion rubles looks realistic, but achieving it will require coordinated efforts by the state and business to build an independent technological ecosystem. Investors should closely monitor industry consolidation—that is where new growth leaders will emerge.