The object of research is Artificial Intelligence (AI) as a strategic tool for the transformation of modern business processes. The key characteristics of AI in a business context include its ability to process large datasets, automate operations, optimize resources, and create a personalized customer experience, which collectively impacts a company's performance. Problem statement. In the context of accelerated digitalization, businesses face the fundamental problem of transitioning from a general understanding of AI's potential to its practical integration to achieve measurable financial results. It is necessary to clearly identify and systematize the specific mechanisms through which AI technologies directly affect profitability. Unresolved aspects of the problem. Despite a significant number of studies on specific aspects of AI application, there is a lack of a comprehensive analysis that would systematize its impact. Additionally, insufficient attention has been paid to developing a practical roadmap for AI integration. The purpose of the article. The purpose of the article is to systematize the key mechanisms of Artificial Intelligence's influence on business performance and to develop a structured approach for its strategic implementation to maximize profitability. Presentation of the main material. The study employs a systematic analysis method to structure AI's impact on business through the "dual-engine" model. Tools such as intelligent automation, predictive maintenance, dynamic pricing, and hyper-personalization are examined. Case studies of leading Ukrainian companies have been analyzed. Conclusions. It is established that AI acts as a profitability catalyst, synergistically affecting both the reduction of operational costs and the acceleration of revenue growth. It is substantiated that successful integration requires a clear strategy, a phased approach and cultural adaptation. The absence of an AI strategy in the modern business environment is a conscious choice in favor of losing a competitive advantage.
Ниценко et al. (Tue,) studied this question.
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