Implementing Artificial Intelligence in the United Arab Emirates Healthcare Sector: An Extended Technology Acceptance Model

Shaikha FS Alhashmi, Said A. Salloum, Chaker Mhamdi

Abstract


The United Arab Emirates (UAE) has recently focused on implementing Artificial Intelligence (AI) projects in the government healthcare sector to help manage chronic diseases and early detection. However, successful AI implementation depends on adoption and acceptance by decision-makers, physicians, nurses, and patients. This paper develops and tests a modified Technology Acceptance Model (TAM) to explore critical success factors (CSFs) for the adoption of AI in the healthcare sector. The most widely used CSF variables for TAM are Perceived Usefulness (PU), Perceived Ease of Use (PEU), Attitudes toward Use (ATU) and Behavioral Intention to Use (BIU). However, a review of 23 qualitative and quantitative studies of TAM literature from 2015 to 2018 suggested that five key external factors should be included in CSF studies using TAM. An extended model was developed (ETAM) and tested using a qualitative study comprising 53 employees working in the Dubai IT and healthcare sectors. The study showed that managerial, organizational, operational and IT infrastructure factors have a positive effect on PU and PEU and, hence, should be included as CSFs in determining the implementation of AI in the healthcare sector.

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