Purpose Artificial intelligence (AI) is increasingly embedded in our daily lives, forming the basis for innovative value creation and unique transformative experiences. Accordingly, the purpose of this study is to explore the key factors and barriers influencing employees’ intention to adopt AI in the banking sector using the technology–organisation–environment (T-O-E) framework. Design/methodology/approach This study gathered data from 389 banking employees in the Indian National Capital Region using self-administered questionnaires. The researchers applied “variance-based structural equation modelling” to analyse the collected data and draw insights from the results. Findings The results demonstrate that perceived usefulness and perceived ease of use substantially influence employees’ attitudes towards AI adoption. The result also demonstrated that perceived usefulness, perceived ease of use, top management support and competitive pressure are significantly associated with employees’ behavioural intentions towards AI adoption. However, technological competency and government support insignificantly influence employees’ behavioural intention towards artificial intelligence adoption. Practical implications The findings will empower managers and practitioners to effectively address the opportunities and challenges of AI, fostering its successful integration, enhancing employee experiences and ultimately driving organisational success in a competitive landscape. This study will offer recommendations to AI developers, guiding them to prioritise significant factors, ultimately fostering the smooth adoption of innovative techniques among users. Originality/value This paper is a preliminary attempt to identify the drivers and barriers to and the general perception and accessibility of banking employees towards AI adoption in India. Unlike prior studies, it highlights the unique challenges and opportunities faced by the banking industry using the T-O-E framework. This study also has the potential to assist banks in fine-tuning their AI adoption strategies and offers insights for further studies in the respective domain.
Kumar et al. (Thu,) studied this question.