Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers

BM Zeeshan Hameed, Nithesh Naik, Sufyan Ibrahim, Nisha S. Tatkar, Milap J. Shah, Dharini Prasad, Prithvi Hegde, Piotr Chlosta, Bhavan Prasad Rai, Bhaskar K. Somani

Research output: Contribution to journalArticlepeer-review


Artificial intelligence (AI) is an emerging technological system that provides a platform to manage and analyze data by emulating human cognitive functions with greater accuracy, revolutionizing patient care and introducing a paradigm shift to the healthcare industry. The purpose of this study is to identify the underlying factors that affect the adoption of artificial intelligence in healthcare (AIH) by healthcare providers and to understand “What are the factors that influence healthcare providers’ behavioral intentions to adopt AIH in their routine practice?” An integrated survey was conducted among healthcare providers, including consultants, residents/students, and nurses. The survey included items related to performance expectancy, effort expectancy, initial trust, personal innovativeness, task complexity, and technology characteristics. The collected data were analyzed using structural equation modeling. A total of 392 healthcare professionals participated in the survey, with 72.4% being male and 50.7% being 30 years old or younger. The results showed that performance expectancy, effort expectancy, and initial trust have a positive influence on the behavioral intentions of healthcare providers to use AIH. Personal innovativeness was found to have a positive influence on effort expectancy, while task complexity and technology characteristics have a positive influence on effort expectancy for AIH. The study’s empirically validated model sheds light on healthcare providers’ intention to adopt AIH, while the study’s findings can be used to develop strategies to encourage this adoption. However, further investigation is necessary to understand the individual factors affecting the adoption of AIH by healthcare providers.

Original languageEnglish
Article number105
JournalBig Data and Cognitive Computing
Issue number2
Publication statusPublished - 06-2023

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Information Systems
  • Computer Science Applications
  • Artificial Intelligence


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