Determinants of AI Adoption in Banking Services in India: An Empirical Investigation

Abstract

Purpose: This study intends to explore the elements that have an impact in determining the intent of customers to use artificial intelligence (AI) in banking services in India's banking sector.

Design/methodology/approach: In order to understand the significance and constraints of implementing AI in the banking sector, a thorough literature review on the baking sector was conducted. 286 completed questionnaires from Indian banking customers were gathered for the quantitative investigation. Using the SmartPLS 3.0 software, the data were evaluated to determine the key factors influencing their intention to use AI.

Findings: The findings align with the theoretical underpinnings of the Technology Acceptance Model (TAM) and underscore the multifaceted nature of customer decision-making in the context of AI adoption in banking. The loadings and reliability analysis further solidify the robustness of the measurement model, ensuring that the constructs employed are reliable indicators of their respective latent variables. The high loadings and acceptable reliability metrics affirm the internal consistency and reliability of the measurement items, enhancing the credibility of the study's findings.

Practical implications: Practical implications suggest fostering positive attitudes towards AI, addressing data privacy concerns, and enhancing awareness to boost AI adoption in banking. Emphasizing perceived usefulness, mitigating perceived risk, and leveraging subjective norms can inform strategic interventions, guiding banks to tailor initiatives that align with customers' perceptions and preferences.

Originality/value: This study is one of the first to examine the significance and possible difficulties of integrating AI technology into banking services and to highlight the main factors affecting the decision to do so in India's banking sector.