The Russian construction industry and housing and utilities sector are on the brink of a radical digital transformation. By 2030, half of all business processes in these sectors will be automated using artificial intelligence. This ambitious target was announced by Deputy Minister of Construction and Housing and Utilities Konstantin Mikhaylik, who called this figure colossal.
This is not just about implementing individual "smart" solutions, but about a total restructuring of operational models. In fact, every second action in the industry—from design to utility infrastructure management—will be tied to machine learning algorithms. This is not evolution, but a true tectonic shift that will require a rethink of established approaches.
Three platforms as the foundation of digitalization
A key condition for the transition will be data unification. The authorities plan to approve three basic platforms: the first will take over construction management, the second—utility infrastructure, and the third will link them to the "Smart City" project. Such a combination will make it possible to abandon fragmented systems and bring all data to a unified format, which is critically important for training AI models.
KPIs for 2026 have already been defined for regions and federal authorities. However, serious barriers stand in the way: low data quality, an outdated technology stack whose age reaches 10–20 years, and the need for large-scale staff retraining. Mikhaylik predicts that by 2029, the process of making management decisions in the sector will change beyond recognition, since every stage of the construction cycle will be "wired" with artificial intelligence.
AI extends beyond construction
The trend toward algorithmization is also covering other industries. President Vladimir Putin has instructed the use of AI to forecast demand and optimize public transport routes, calling this a way to radically improve efficiency. Scientific data is becoming the basis for sovereign models: Prime Minister Mikhail Mishustin has approved a list of instructions that open up research datasets for training neural networks, provided that intellectual property rights are reliably protected.
Medicine demonstrates the most illustrative examples. The "MosMedAI" platform has already brought together more than two thousand clinics from 75 regions, processing over 16 million radiology studies. At the same time, security requirements are being tightened: the Big Data Association has added obligations to the industry standard for Sber, Yandex, VK, Avito, Rostelecom, and HeadHunter to regularly assess the security of AI processes and train employees.
The scale of implementation is also reflected in the market. According to the baseline forecast of the AIANA agency, the volume of the Russian AI market will grow from 316.1 billion rubles to 830 billion by 2030, and under a favorable scenario—to 1.12 trillion rubles.
Expert comment: The figure of 50% looks ambitious but achievable—especially in the housing and utilities sector, where routine processes (accounting, dispatching, accident forecasting) are easiest to algorithmize. However, the main risk lies not in technology, but in the "digital divide" between regions and the shortage of specialists capable of maintaining these systems. Without solving the staffing issue, the plan risks remaining a declaration.