Behavioural Intentions to Adopt Artificial Intelligence in Healthcare: Exploring the Perception of Healthcare Professionals

K. S. Swathi, S. Aswathy, T. C. Kavitha*, Krishnaraja Chadaga, Niranjana Sampathila*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Artificial intelligence (AI) technologies are used in healthcare to detect diseases faster, provide personalized treatment, automate some processes, and enhance hospital safety. Yet, one of the critical challenges is users’ hesitation and unwillingness to adopt technological applications in medical practice. Hence, this research aims to identify the important factors affecting professionals’ behavioural intentions to use AI in healthcare. This cross-sectional survey was conducted in Kerala, India. We proposed a framework grounded on the literature on technology acceptance theories, and the conceptual model was tested using a 20-item questionnaire with a 5-point Likert scale. The structured questionnaire was converted into a Google Form and shared with the respondents. A total of 347 respondents, including doctors, nurses, and allied healthcare professionals from 5 different private hospitals in India, participated in this study. The partial least square structural equation modelling approach was used to evaluate the proposed framework upon confirming the reliability and validity of the measurement items. The study findings reveal that perceived ease of use (PEU), perceived usefulness (PU), and facilitating conditions (FC) are the critical factors that influence the behavioural intentions (BI) of healthcare professionals to use AI. Though healthcare professionals perceived the risk of using AI, it did not affect their choice to use AI. This study gives an understanding of healthcare professionals’ behavioural intentions to use AI so that the administrators can plan and improve their strategies to implement AI in hospitals.

Original languageEnglish
JournalJournal of Technology in Behavioral Science
DOIs
Publication statusAccepted/In press - 2025

All Science Journal Classification (ASJC) codes

  • Health(social science)
  • Applied Psychology
  • Human-Computer Interaction
  • Computer Science Applications

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