Factors Influencing Generative Artificial Intelligence Adoption in Banking: An Empirical Study

Wissem Ajili Ben Youssef, Najla Bouebdallah and Long Ha

Chapter 1 in Innovating Finance for a Sustainable Future:Integrating FinTech, Blockchain and Generative AI, 2026, pp 1-28 from World Scientific Publishing Co. Pte. Ltd.

Abstract: The study investigates the factors influencing the adoption of Generative AI (GenAI) in Vietnam’s banking sector. The theoretical framework is based on an expanded version of the Technology–Organization–Environment (TOE) model. We employed a quantitative approach, collecting data from 248 surveys conducted with banking professionals and industry practitioners. We conducted exploratory factor analysis and regression analysis. The three most significant drivers for the adoption of Gen AI are organizational readiness, competitive pressure, and compatibility. Complexity poses a significant barrier, indicating that developing simple and user-friendly GenAI applications is crucial for the technology’s adoption. This research contributes to the existing literature by expanding the Technological-Organizational-Environmental (TOE) framework to examine the adoption of GenAI within the banking sector specifically. The study offers actionable insights for banks aiming to implement AI-driven technologies effectively. Its findings have significant implications for the banking industry, as they identify the key drivers of GenAI adoption. Furthermore, the study provides strategic recommendations for Vietnamese banks to enhance operational efficiency and promote financial inclusion.

Keywords: Generative Artificial Intelligence; Technology–Organization–Environment (TOE); ESG Factors; Sustainability; Blockchain; Supply Chain Finance; Trade Finance; FinTech; Customer Loyalty; Mobile Banking; Perceived Risk; Trust; Personalization; Digital Banking Adoption; Customer Behavior; Digital Innovation; Retail Banking; CSR; Foreign Ownership; Digital Transformation; Bank Performance; Big Four; Auditing; Intention to Use; Risk Assessment; Risk Mitigation; CAMELS-Based Framework; Banking; Qualitative Approach; Quantitative Approach; Case Study; Vietnam Banking Sector (search for similar items in EconPapers)
JEL-codes: G21 G23 G28 O33 Q56 (search for similar items in EconPapers)
Date: 2026
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