Artificial intelligence as a driver of business process transformation

purpose: to identify the specific impact of artificial intelligence technologies on the transformation of business processes in organizations with different operational profiles – from production-oriented to analytical and information-based. Methods: the study employs methods of analysis and synthesis to substantiate the theoretical basis of digital transformation, comparative analysis to interpret empirical data, inductive reasoning to generalize from specific case studies, and simulation modeling to quantitatively assess the effect of artificial intelligence on labor productivity. Findings: the implementation of artificial intelligence can lead to a 20-28% increase in labor productivity depending on the type of organizational activity, as well as reduce task completion time and error rates. Artificial intelligence transforms process architecture, enhances strategic flexibility, and supports the shift from functional to platform-based management models Conclusions: artificial intelligence technologies serve not only as automation tools but also as systemic drivers of business process reorganization. Their transformational potential is reflected in accelerated decision-making, increased adaptability, and the emergence of new models of corporate governance. Achieving sustainable results requires a comprehensive approach, including technological modernization, competence development, and institutional restructuring.

artificial intelligence, business processes, digital transformation, labor productivity, machine learning, predictive analytics, automation