Graduation Year
2024
Document Type
Dissertation
Degree
D.B.A.
Degree Granting Department
Business Administration
Major Professor
Sajeev Varki, Ph.D.
Co-Major Professor
Aharon Yoki, D.B.A.
Committee Member
Jean Kabongo, Ph.D.
Committee Member
Joann Quinn, Ph.D.
Committee Member
Douglas E. Hughes, Ph.D.
Keywords
AI, Financial Institutions, Technology, UTAUT
Abstract
The importance of Artificial Intelligence (AI) is exploding in the banking sector, fueled by enhanced productivity, improved efficiencies, and personalized services to the consumers. For credit unions, the adoption of AI technologies presents opportunities and challenges. This research explores the factors influencing AI adoption in the banking sector through the lens of Unified Theory of Acceptance and Use of Technology (UTAUT) framework. This study aims to explore the influence of key aspects of UTAUT model, Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) on the intention of AI adoption among credit unions, banks, and their consumers. This research combines qualitative insights gathered from semi-structured interviews with leaders in the banking sector and quantitative data from consumer surveys.
Scholar Commons Citation
Tumma, Vijaya S., "Exploring Factors that Influence Artificial Intelligence Adoption in Banks and Credit Unions" (2024). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/10685
