Educational equity and generative AI adoption in banking: bridging the digital divide among employees

Adopting Generative AI (GenAI) in the banking sector is essential for enhancing operational efficiency and innovation. This study employs a three-phase mixed-method approach to examine the factors influencing employees’ intention to adopt GenAI in the banking sector of Pakistan. In the first phase, 16 semi-structured interviews identified key themes, including managerial support, access to training resources, digital infrastructure, perceived self-efficacy, and technological readiness. The second phase involved a quantitative survey of 386 banking employees analyzed using partial least squares structural equation modeling (PLS-SEM), while the third phase applied artificial neural network (ANN) analysis to determine variable importance. Findings reveal that managerial support, training access, and digital infrastructure significantly enhance adoption intention, both directly and indirectly through self-efficacy, while technological readiness strengthens these relationships, indicating that employees with higher readiness levels are more likely to translate organizational support and resources into GenAI adoption intentions. The study offers valuable theoretical and practical insights for fostering GenAI adoption in the banking industry, particularly within developing economies.

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