THE ROLE OF ARTIFICIAL INTELLIGENCE IN ENTERPRISE MANAGEMENT BASED ON QUALITY MANAGEMENT

Abstract

This article examines the role and practical significance of artificial intelligence technologies in improving quality management systems. In the context of digital transformation, quality management in enterprises extends beyond the inspection of final products and requires the near-real-time analysis of large volumes of process data, the early detection of quality deviations, the prediction of factors that cause defects, and the optimisation of managerial decisions. The study employs systems analysis, comparative analysis, content analysis, a process approach, and conceptual modelling. It proposes a conceptual mechanism for integrating artificial intelligence tools into the Plan–Do–Check–Act (PDCA) cycle of quality management. This mechanism encompasses data collection, intelligent analysis, quality risk prediction, the formulation of an optimal decision alternative, the implementation of corrective measures, and continuous performance monitoring. The findings indicate that artificial intelligence can improve the speed and accuracy of quality control, reduce human error, and strengthen enterprise competitiveness.