Customer Trust in Era of AI: Examining the Adoption of Artificial Intelligence in Public and Private Sector Banking

Mahima Sharma; Maneesha Kaushik

doi:10.69968/ijisem.2025v4i3492-512

Authors

Mahima Sharma Research Scholar Rajasthan Technical University
Maneesha Kaushik Associated Professor Swami Keshvanand Institute of Technology, Management & Gramothan (SKIT)

DOI:

https://doi.org/10.69968/ijisem.2025v4i3492-512

Keywords:

Artificial Intelligence, Customer Trust, Banking Services, Technology Acceptance Model, PLS-SEM, India, Digital Banking, AI Adoption.

Abstract

Purpose – This research throws light on the factors creating customer trust in AI in Indian banking sphere of public and private banks. It examines the ways in which usefulness, ease of use, security, and awareness of AI shape customer attitudes and intentions toward AI adoption, which contribute to their trust in AI. The mediating effects of attitude and behavioural intention between these perceptions and trust formation are also contemplated in investigation.

Design/methodology/approach – In an attempt to confirm the model, data were gathered from 453 Indian bank customers via a structured questionnaire. PLS-SEM was administered for the evaluation of the proposed conceptual model, while MGA was conducted for comparing the responses of public sector versus private sector bank users.

Findings – Perceived security turns out to be the strongest factor influencing attitude toward AI and intention to use AI, followed by ease of use and usefulness. Attitude and intention are significant mediators between technological perceptions and customer trust. Contrary to expectations, AI knowledge had no influence on trust, neither directly nor indirectly. Another set of results relates to the sectorial differences of those customers: customers in public sector emphasized security all the more.

Research Limitations/Implications – The cross-sectional nature of this study constrains analysis over time, and the results may not be generalized to the population beyond digitally literate respondents in India. Future works can follow the longitudinal and qualitative approach, including more constructs like algorithmic transparency, and extending the model to other service industries.

Originality/Value – The research investigates an extension of the Technology Acceptance Model through more trust-related variables concerning AI in banking. It provides practical as well as theoretical contributions by unravelling psychological and perceptual factors underlying AI trust, particularly in an emerging economy. The insights give bank managers and policymakers a conscious starting point for promoting responsible and inclusive AI adoption.

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