THE IMPACT OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES ON MODERN MANAGEMENT PROCESSES AND DEVELOPMENT PROSPECTS: PROBLEMS AND SOLUTIONS

Abstract

Artificial intelligence (AI) has moved from a peripheral experimental capability to a core operational layer in modern management. Yet the diffusion of AI across organizations is highly uneven, and the gap between adoption and value creation is widening. This article examines the impact of AI technologies on contemporary management processes—strategy, decision-making, operations, human resource management, marketing, and customer experience—and identifies the principal problems that constrain value capture, including the scaling gap, the talent and culture deficit, governance and ethics fragility, the productivity paradox, and measurement immaturity. Drawing on recent international evidence (McKinsey, IBM, OECD, Gartner, SHRM) and conceptual contributions from the management literature, the paper proposes the SCALE framework—Strategy alignment, Capability development, Architecture and workflow redesign, Leadership and governance, and Ethics and trust—as a structured response to the documented bottlenecks. The analysis shows that approximately 78–88 percent of organizations now use AI in at least one business function, but only around 5–6 percent qualify as AI high performers with measurable EBIT impact, and roughly two thirds of organizations remain in pilot purgatory. The paper argues that the principal binding constraint is not technology but managerial design: organizations that redesign workflows, allocate clear ownership, invest in capability building, and embed ethics in operating routines convert AI investments into measurable performance gains, while those that bolt AI onto unchanged processes do not. Implications are formulated for managers, boards, public policy, and management education in both advanced and transition economies.