Artificial Intelligence and the Future of Finance: An Empirical Study of Adoption, Benefits and Challenges

Abstract

Abstract The rapid integration of artificial intelligence (AI) into the financial sector has fundamentally transformed the way financial institutions operate, manage risk, and deliver services to customers. Despite the growing adoption of AI technologies across banking, insurance, and investment management, there remains a limited understanding of how the perceived benefits and perceived challenges of AI collectively shape the adoption behavior of finance professionals and organizations. This study addresses this gap by developing and empirically testing a conceptual model that examines the influence of perceived benefits (PB) and perceived challenges (PC) on AI adoption (AD) in the financial services industry. Drawing on the Technology Acceptance Model (TAM), the Diffusion of Innovations (DOI) theory, and the Unified Theory of Acceptance and Use of Technology (UTAUT), this research employs a quantitative survey methodology. A structured questionnaire was administered to 100 respondents working in or associated with the financial sector. The instrument comprised 24 items distributed across three constructs: Perceived Benefits of AI (8 items, α = 0.922), Perceived Challenges of AI (8 items, α = 0.931), and AI Adoption in Finance (8 items, α = 0.911). Data were analyzed using descriptive statistics, Pearson correlation analysis, and multiple linear regression. The results of the multiple linear regression analysis revealed that the model explained 38.9% of the variance in AI adoption (R² = 0.389, F(2,97) = 30.87, p < .001). Perceived benefits emerged as a strong and statistically significant positive predictor of AI adoption (β = 0.580, p < .001), while perceived challenges had a statistically significant but weaker negative effect (β = -0.162, p < .05). The regression equation was: AI Adoption = 0.884 + 0.617(PB) - 0.162(PC). These findings underscore that while perceived benefits are the primary driver of AI adoption, perceived challenges exert a modest inhibiting effect, suggesting that organizations can accelerate AI adoption by strategically emphasizing tangible benefits while proactively addressing recognized challenges. Keywords: artificial intelligence, AI adoption, financial services, perceived benefits, perceived challenges, Technology Acceptance Model, multiple linear regression