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The integration of Artificial Intelligence (AI) in medical practice is transforming healthcare sector, yet adoption remains inconsistent. This study investigates how technological drivers specifically compatibility and observability influence AI adoption in the UAE’s healthcare sector, and explores the mediating role of trust, conceptualized through competence, integrity, and benevolence. Data were collected via a structured questionnaire distributed among healthcare professionals and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Results reveal that technological drivers positively impact trust, which in turn enhances AI adoption. Trust emerges as a critical mediator, emphasizing its role in linking technological advancements with ethical standards and professional responsibility. Although technology drivers directly influence AI adoption, trust partially mediates this relationship, highlighting the need for ethically grounded strategies in AI integration. The study provides valuable theoretical insights by combining technology attributes and psychological trust factors, and offers practical guidance for policymakers, healthcare administrators, and developers aiming to advance responsible digital transformation. Overall, it stresses the importance of fostering trust to ensure the successful adoption of AI technologies in the UAE’s healthcare sector.

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From System Features to Adoption: Examining the Role of AI Trust in Perceived Technological Drivers in The Healthcare Sector in the UAE

  • 会议论文

  • 发表日期：

    2026年

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  • Loubna  Saad Saoud,
  • Omer Aftab Qureshi

摘要

The integration of Artificial Intelligence (AI) in medical practice is transforming healthcare sector, yet adoption remains inconsistent. This study investigates how technological drivers specifically compatibility and observability influence AI adoption in the UAE’s healthcare sector, and explores the mediating role of trust, conceptualized through competence, integrity, and benevolence. Data were collected via a structured questionnaire distributed among healthcare professionals and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Results reveal that technological drivers positively impact trust, which in turn enhances AI adoption. Trust emerges as a critical mediator, emphasizing its role in linking technological advancements with ethical standards and professional responsibility. Although technology drivers directly influence AI adoption, trust partially mediates this relationship, highlighting the need for ethically grounded strategies in AI integration. The study provides valuable theoretical insights by combining technology attributes and psychological trust factors, and offers practical guidance for policymakers, healthcare administrators, and developers aiming to advance responsible digital transformation. Overall, it stresses the importance of fostering trust to ensure the successful adoption of AI technologies in the UAE’s healthcare sector.