AI in recruiting: nearly half of Russian companies have already entrusted hiring to algorithms
The Russian labor market is undergoing a fundamental shift. According to my analysis of the latest data, 49% of employers in the country are already actively using artificial intelligence in the recruitment process, and another 21% plan to implement these technologies in the near future. Combined, this means that 70% of companies have either already automated hiring or are on the verge of doing so.
Where algorithms take over routine tasks
The most in-demand use case for AI has become writing job descriptions—64% of respondents have entrusted this task to neural networks. In second place is transcribing and analyzing interviews (36%). This is followed by generating personalized letters to candidates (31%) and initial screening of responses with candidate ranking (29%).
The effect of implementation is already tangible: 55% of companies have noted a reduction in routine tasks, 36%—a decrease in the workload on recruiters, and 20%—faster vacancy closure. At the same time, budgets for automation remain modest so far: about 68% of employers spend less than 500,000 rubles per year on these purposes, and only 5% allocate over 2 million.
Barriers and skepticism
Nevertheless, almost half of the companies that have refused AI (46%) consider the human factor critically important in hiring. 41% fear algorithm bias, 32% cite a lack of expertise, and 29% doubt the return on investment. Additional obstacles include limited budgets, the requirements of Federal Law No. 152-FZ "On Personal Data," and the risks of information leaks.
Macro context: AI as an economic driver
Recruiting is just one of many areas where neural networks are gaining a foothold in the Russian economy. According to Sber's estimates, generative technologies will add 1.2 percentage points to labor productivity, primarily in office professions. The country's AI market grew by 29.7% in 2025, reaching 316.1 billion rubles, and the baseline scenario assumes growth to 830 billion by 2030.
The state, in turn, is shaping the regulatory framework: from introducing sovereign neural networks into education and public services to working groups on copyright for AI-generated content.
Analyst's comment: The current figures confirm that hiring automation has ceased to be an experiment and has become a de facto standard. However, the key challenge is not technological but ethical. Companies that overcome the trust barrier toward algorithms and integrate them into hybrid processes will gain a competitive advantage in the battle for talent. Those who continue to ignore the trend risk being left behind within just 2-3 years.