INTELLIGENT BUSINESS PROCESS MANAGEMENT BASED ON ARTIFICIAL INTELLIGENCE AS A FACTOR OF INNOVATIVE DEVELOPMENT OF THE ENTERPRISE

Abstract

The article examines the theoretical and applied aspects of integrating artificial intelligence into business process management (BPM) in the context of digital transformation. Digital transformation is substantiated as a paradigm shift in management logic that transforms value creation mechanisms, business models, and decision-making principles, while BPM serves as the infrastructural basis for these changes. It is shown that AI integration enables a transition to cognitive-adaptive management, in which business processes acquire the capacity for self-learning, forecasting, and dynamic adjustment. Key trends in digitalization are identified, including data-driven management, ecosystem business models, and continuous innovation. In this context, enterprises are increasingly viewed as open adaptive systems operating within digital ecosystems, where value creation is based on data exchange, network interaction, and continuous analytical support. The main barriers to AI integration into BPM are systematized, including infrastructural fragmentation, low data quality, organizational inertia, and lack of competencies. Their systemic interdependence is substantiated, demonstrating that implementation effectiveness depends on the coherence of management system components. It is emphasized that the imbalance between technological capabilities, process architecture, and managerial practices significantly reduces the effectiveness of intelligentization and transformation processes. A conceptual model of AI integration is developed, reflecting the transition from automation to intelligent management, together with a mechanism for its implementation based on systemic integrity, phased development, and adaptability. The model highlights the importance of synchronizing digital infrastructure, data management systems, and business processes as a prerequisite for effective AI deployment. It is substantiated that the model ensures intelligent-adaptive efficiency, improves decision-making quality, enables proactive management, and strengthens enterprise innovative capacity, shaping a new quality of modern management.