Artificial intelligence in financial management: strategic vectors and challenges

doi:10.26565/2311-2379-2025-109-10

I. Kovova National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” https://orcid.org/0000-0003-3545-0055

DOI: https://doi.org/10.26565/2311-2379-2025-109-10

Keywords: artificial intelligence, financial management, vectors, challenges, areas of application

Abstract

The author of the article considers the main directions of application of artificial intelligence in financial management. The article reviews the main scientific sources and positions of practitioners on the strategic prospects of applying artificial intelligence tools in financial management. The research is based on the methodology of systematic review and synthesis of scientific sources and industry reports, which is the most justified for this area of research. The article analyzes key indicators of the artificial intelligence market in the financial sector according to data from leading analytical companies, which demonstrates the impressive growth dynamics of the global artificial intelligence market by 2030-2034. The author systematizes the main challenges faced by the implementation of artificial intelligence in financial management, such as: ethical and regulatory lags, scaling problems, environmental impact and data bias. Based on the analysis of market trends, the evolutionary path of using artificial intelligence tools has been determined, which indicates the growth of market maturity, which is moving from the stage of "technology for the sake of technology" to the stage of "solutions for the sake of business tasks". The author identified strategic vectors for the implementation of artificial intelligence technology in financial management, among which three main ones were conceptually identified: increasing operational efficiency, risk management and cybersecurity, personalization and customer experience. Specific areas of application in which the implementation of artificial intelligence has the most significant results in financial management have also been systematized: fraud detection, creditworthiness assessment, forecasting needs, democratization of financial services, development of virtual assistants, etc. The article pays attention to comparing the main models of generative artificial intelligence and their possibilities of use as tools in financial management, in particular, advantages, limitations and the most optimal type of use.

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Author Biography

I. Kovova, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

PhD (Economics), Associate Professor, Associate Professor of the Department of Economic Cybernetics

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