Date of Conferral

10-21-2025

Degree

Doctor of Business Administration (D.B.A.)

School

Business Administration

Advisor

Cynthia Phillips

Abstract

The rapid integration of artificial intelligence (AI) into the financial services industry has created a need for financial services managers to understand which factors drive AI adoption among non-technical staff, because shortfalls in AI adoption can erode efficiency gains and competitive advantage. Grounded in the Technology Acceptance Model (TAM), the purpose of this quantitative correlational study was to examine the relationship between perceived usefulness (PU) of AI, perceived ease of use (PEOU) of AI, and AI adoption among non-technical employees in the financial services industry. The research questions focused on whether PU and PEOU were significantly related to AI adoption and whether one was a stronger predictor than the other. A convenience sample of 81 non-technical financial services professionals from LinkedIn met the inclusion criteria and completed a SurveyMonkey questionnaire. Data were analyzed using the Statistical Package for the Social Sciences (SPSS). Results of the multiple linear regression were significant, with F(2, 78) = 46.469, p < .001 and R² = .544. Notably, both PU (B = 0.723, p < .001) and PEOU (B = 0.355, p = .008) significantly predicted adoption, with PU being the stronger predictor. The model explained 54.4% of the variance in adoption, indicating a large effect size. Findings suggest that organizations can increase AI adoption by emphasizing productivity benefits while reducing complexity barriers. The implications for positive social change include the potential for employees to experience increased efficiency and reduced work complexity, enabling financial institutions to operate more effectively and contributing to the economic resilience of local communities.

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