THE USE OF ARTIFICIAL INTELLIGENCE IN ADAPTIVE ENTERPRISE MANAGEMENT

Abstract

This article explores the role of artificial intelligence (AI) in adaptive enterprise management in the context of digital transformation. In today's environment of instability and rapid market changes, businesses face the need to enhance flexibility and efficiency in management processes. AI has emerged as a key tool in addressing these challenges by enabling business process automation, improving decision-making accuracy, and optimizing resource allocation. The study examines the main AI technologies used in management, including machine learning, neural networks, natural language processing, and robotic process automation.

Based on a review of scientific research, the article identifies key areas of AI implementation in strategic enterprise management, such as market trend forecasting, competitive environment analysis, and personalized customer interaction. The major challenges associated with AI adoption are highlighted, including high financial costs, a shortage of qualified personnel, ethical concerns, and cybersecurity issues. Specifically, the study addresses problems related to algorithmic bias and the lack of transparency in AI-driven decision-making.

Additionally, the article proposes a conceptual model for integrating AI into adaptive enterprise management. This model incorporates a hybrid approach that combines AI-driven analytics with human managerial competencies. The research emphasizes the importance of developing a digital culture within organizations, adapting workflows for AI collaboration, and ensuring algorithmic transparency.

The findings confirm that AI adoption enhances businesses' responsiveness to market changes, improves decision-making efficiency, and reduces operational costs. However, the study also underscores the need for further research on AI implementation strategies, regulatory frameworks, and risk mitigation related to AI applications in enterprise management.