THE PROBLEMATICS OF ECONOMIC JUSTIFICATION FOR THE IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE IN BUSINESS PROCESS AUTOMATION

Анотація

This scientific article explores the complex and timely issue of providing a sound economic justification for the implementation of artificial intelligence (AI) in the automation of business processes. In the current stage of digital transformation, AI is increasingly perceived not merely as a high-tech tool, but as a strategic asset capable of driving efficiency, flexibility, and long-term competitiveness for businesses. Despite the global expansion of AI-driven technologies, there remains a substantial gap in economic methodologies that can accurately evaluate the financial feasibility and strategic value of AI adoption. This issue is especially relevant for transitional economies, including Ukraine, where businesses face limited investment resources, high levels of uncertainty, and an urgent need for modernization in order to adapt to global market demands. The primary focus is placed on identifying the economic prerequisites and constraints of AI integration into business processes, followed by the development of an analytical framework for their assessment. The research addresses two primary objectives: to define and examine the core economic barriers, risks, and systemic challenges associated with the use of AI in diverse business environments; and to develop an analytical model for evaluating the economic viability, return on investment, and strategic effectiveness of AI-enabled automation solutions. The proposed model combines quantitative and qualitative criteria such as cost-efficiency, productivity growth, technological adaptability, operational risk mitigation, and scalability under dynamic conditions. The practical value of the study lies in the applicability of its findings for improving managerial decision-making, optimizing investment planning, and enhancing the digital readiness of enterprises, particularly in Ukraine, where AI integration may serve as a catalyst for sustainable economic recovery and competitive growth. If this problem remains unresolved, businesses risk inefficient allocation of resources, suboptimal investment decisions, and falling behind in the global race for technological competitiveness.

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