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This paper will be reviewing how the adoption of AI in enterprises has affected financial analysis, with respect to financial reporting, forecast accuracy, and cost-effectiveness between the years 2020 and 2024. The study examines the adoption of AI and the moderating factors of the firm size, age, leverage, and financial loss using 180 observations of 10 banks and 26 insurance firms. The research methodology involves linear regression, OLS and correlation analysis to cover variance and heterogeneity. The findings demonstrate that there is a positive, strong and statistically significant correlation between AI use and performance in financial analysis. Smaller companies are less prone to the use of AI, and there is no strong impact of financial loss. The stability of the traditional and advanced regression models facilitates the validity of the results. The research gives both empirical evidence and practical information on how AI helps to increase the efficiency of financial analysis and serves as a good guide to be followed by decision-makers who want to be more efficient in their analytical performance.
Alnor et al. (2026) studied this question.