RISKS OF ARTIFICIAL INTELLIGENCE FOR MANAGEMENT: CLASSIFICATION, MANAGEMENT, KPI

The rapid introduction of artificial intelligence (AI) technologies into business processes qualitatively transforms the nature of management risks, generating new strategic, operational, ethical and reputational threats. The autonomy and transparency of AI systems require the development of specialized approaches to their management, integrated into the corporate strategy. The purpose of the study — systematization of AI risks for management and development of a risk management system, including the selection of optimal key performance indicators (KPIs). The work is based on the secondary analysis of data from reports, surveys and research publications. The methods of statistical, quantitative and systematic analysis, as well as a normative approach for the formation of management recommendations are used. The study identified and structured seven key categories of AI risks: strategic, operational, ethical, organizational, financial and investment, risks for managerial roles, and reputational. Specific management practices and a KPI system are proposed for each category, linking technical risks with business consequences. The scientific value of the work lies in the comprehensive systematization of AI risks for management. The practical value is to provide managers with structured tools for integrating AI risk management into corporate strategy and operational activities, which is a critical factor for sustainable development in the context of digital transformation.