SYNERGY OF CORPORATE GOVERNANCE AND BUSINESS PROCESS OPTIMIZATION BASED ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES
Abstract
The article is devoted to the study of the synergy between corporate governance and business process optimization based on artificial intelligence (AI) technologies, with an emphasis on improving the effectiveness of managerial decision-making and resource efficiency. The purpose of the research is to develop and test a comprehensive system for evaluating the effectiveness of AI integration into corporate governance, which contributes to the improvement of business processes and enhances the competitiveness of companies. The research methodology is based on the combination of expert analysis, which ensures a qualitative assessment of managerial results, and AI analytical algorithms aimed at processing large datasets to generate quantitative efficiency metrics. The obtained scientific results demonstrate that the implementation of AI makes it possible to identify discrepancies between actual and normative models of business processes, particularly on the example of the “commercial proposal” process, which enabled a thorough diagnosis and the identification of critical inefficiencies. The analysis showed that the initial value of the integral quality indicator reflected low performance due to excessive resource consumption, high process interconnectivity, and elongated execution trajectories. After digital reengineering and the application of reinforcement learning technologies, the updated metrics demonstrated significant improvement, including higher process standardization, increased financial performance, and reduced time costs, which ensured the transition to a positive value of the integral indicator. The practical value of the research lies in the development of a universal methodology for assessing the synergy of corporate governance and business process optimization, which can be applied in various industries to improve the efficiency of management systems. The results of the study provide a basis for the introduction of intelligent systems into corporate governance. Prospects for further research include the enhancement of AI algorithms for automating complex managerial processes.
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