This article examines the transformation of corporate governance under the influence of artificial intelligence (AI) technologies. The relevance of the topic is driven by the rapid growth in the adoption of AI-based solutions. At the same time, more than a third of enterprises report significant economic benefits from their use. However, the issue of systematizing the technologies employed in organizational activities, particularly in the management function, remains pressing. The authors propose assessing the maturity of AI technology application in organizational management, thereby enabling the avoidance of typical errors and the development of a coherent AI transformation strategy. Consequently, the aim of the study is defined as follows: to develop a methodological framework for assessing the maturity of AI application in organizational management, including the refinement of key concepts, systematization of approaches to analyzing the impact of AI technologies on the management function, and the creation of practical assessment tools for diagnosing and interpreting maturity levels. To analyze the theoretical and methodological aspects of strategic management in the context of digital transformation, methods of data analysis from open sources, scientific research methods including analysis and synthesis, as well as deduction and generalization were employed. The empirical basis of the study comprises case studies of Russian companies from various industries (manufacturing, logistics, retail) at different stages of AI integration into management processes. The authors have developed approaches to assessing the impact of AI on organizational management, clarified the concept of “maturity” in the application of AI technologies in management, constructed a maturity assessment matrix for the use of AI in organizational management activities, created a checklist for diagnosing the current maturity level, and proposed an interpretation of diagnostic results for the current level of AI maturity in management activities. The matrix includes nine sequential levels: from the local use of open models by employees (“Level 0: Interest”) to the creation of a fully autonomous “captive company” capable of operating and generating revenue without human intervention (“Level 8”). Each level is characterized in terms of the AI technologies and tools employed, architectural approaches (robot-centric, AI-centric, multi-agent architecture), key artifacts, the sequence of tool application, and the transformation of management functions (planning, organization, motivation, control, coordination). Based on an analysis of Russian companies’ case studies, the expected effects of progressing through AI maturity levels are examined, the costs required to achieve each level are estimated, and practical examples are provided. The maturity assessment matrix serves as a tool for diagnosing a company’s current state and formulating its AI transformation strategy, enabling an objective assessment of the company’s status and identification of directions for its AI transformation. Promising research directions include the development of detailed metrics for assessing each maturity level, as well as the study of industry-specific features of applying this matrix. Another important area is the analysis of risks and ethical aspects associated with the operation of high-level autonomous systems.