The AI market in Russia: a leap to 830 billion rubles by 2030 — my scenario analysis
The Russian artificial intelligence market ended 2025 with an impressive result: volume grew by 29.7%, reaching 316.1 billion rubles. Over two years, the figure has doubled, indicating a structural rather than a cyclical acceleration. However, behind these numbers lies a deeper transformation: companies are shifting from purchasing expensive equipment to renting computing power and implementing ready-made solutions. This is changing the very economics of the industry.
Three scenarios until 2030
My baseline forecast assumes the current macroeconomic situation persists: a high key rate and the existing level of geopolitical risks. In this case, the market will grow to 830 billion rubles by 2030. However, this is not the limit.
The optimistic scenario raises the bar to 1.12 trillion rubles. This will require monetary policy easing, reduced external pressure, and, critically, the formation of a domestic technological base. The key condition here, I believe, is the entry of domestic solutions into external markets—without this, the growth potential will remain unrealized.
The conservative estimate limits the volume to 582 billion rubles. This option materializes under tightened sanctions, a higher rate, and limited access to foreign computing resources and models. In this case, costs rise, prices for end products increase, demand for AI services falls, and the technological gap becomes entrenched.
Structural changes: clouds and sovereignty
Over a five-year horizon, AI infrastructure will finally move to the cloud, the market will begin to consolidate, and truly major technology players will emerge in the industry. The accelerated shift to renting capacity reflects a broader state pivot toward sovereign infrastructure. Domestic models are increasingly trained on internal data sets 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 preservation is being addressed: major technology companies are building protection for the data arrays on which their neural networks operate.
Market growth is also changing the regulatory framework. The government has already formed a working group to define rules for using copyrighted content when training models and the order of ownership of generated materials. AI adoption also affects the labor market: in my 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 conclusion: the Russian AI market is entering a phase of maturity, where the key factor will not be access to hardware, but the ability to monetize data and create competitive products. Investors should closely watch companies that can enter international markets—they will be the main beneficiaries of this transformation.