Maturity model and success factors for the implementation of AI agents in Russian companies

Abstract

By early 2026, AI agents ceased to be experimental tools and began to be considered as a form of business process automation. Based on the analysis of in-depth interviews, an expert session, a quantitative survey of Russian companies, and sources reflecting Russian and foreign experience in the deployment of AI agents, a five level maturity model was developed. This model includes the following levels: initial, repeatable, defined, managed, and optimizing. The model allows diagnosing an organization’s readiness for industrial use of agent systems. It was revealed that full autonomy of AI agents is virtually non existent in Russian practice; hybrid operating models with clearly defined human in the loop thresholds dominate. The shortage of qualified specialists is the main constraint. The greatest potential of AI agents is observed in repetitive operational tasks where non standard situations are rare. The effect of implementing AI agents should most often be assessed not as direct cost reduction, but as an increase in team efficiency. The main success factors are data quality and depth of integration with the corporate IT landscape.