Exploring Emotional Intelligence in Jordan’s Artificial Intelligence (AI) Healthcare Adoption: A UTAUT Framework


  • Amani Mohamad Alhadidi


intelligence, Health, computer, engineering, management


The integration of Artificial Intelligence (AI) has been reshaping healthcare globally. However, the AI adoption in Jordan is met with cautious progress. AI has shown substantial potential to enhance healthcare services and foster Emotional Intelligence (EI), especially in advanced economies. Despite its proven effectiveness elsewhere, the Jordanian populace is reluctant to adopt AI in the healthcare sector, with predictions for hospitalizations, medical consultations, and treatment recommendations being sluggish to gain acceptance. This study investigates the combination of Emotional Intelligence and AI adoption in the healthcare system in Jordan, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) model. In this study, a quantitative approach has been employed, whereby questionnaires were delivered through email and messaging apps to evaluate the impact of emotional intelligence on Jordanians’ willingness to adopt AI technology in the healthcare sector. The findings suggested that the UTAUT model should be further expanded to encompass emotional intelligence as its fifth construct, particularly in developing countries like Jordan, where user models for AI adoption are less explored. The implications of the study extend to healthcare planners and developers in Jordan, providing insights into factors that influence the successful adoption of AI technologies among diverse user groups. This study has provided valuable recommendations for developers of AI-based healthcare systems, enabling them to align their assistance with the perceptions and behaviors of Middle Eastern users.


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How to Cite

Amani Mohamad Alhadidi. (2024). Exploring Emotional Intelligence in Jordan’s Artificial Intelligence (AI) Healthcare Adoption: A UTAUT Framework. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 66 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6394



Research Article