AUTHOR=Al Qwaid Marran 

TITLE=Perceptions of health data commodification in AI-driven healthcare systems in Saudi Arabia

JOURNAL=Frontiers in Artificial Intelligence

VOLUME=Volume 8 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1559302

DOI=10.3389/frai.2025.1559302

ISSN=2624-8212

ABSTRACT=IntroductionArtificial Intelligence (AI) is transforming healthcare service delivery through predictive analytics, precision medicine, and advanced diagnostics. However, the commodification of health data introduces complex ethical and social challenges related to privacy, ownership, and consent. This study explores perceptions of health data commodification within AI-driven healthcare systems, focusing on Saudi Arabia’s rapidly evolving digital healthcare landscape.MethodsA mixed-methods approach was employed, combining quantitative surveys and in-depth qualitative interviews. The study included 42 patients, 8 healthcare professionals, 3 insurance representatives, and 4 AI experts. Data were collected across three main themes: data privacy, perceived benefits of AI, and attitudes toward data commodification. Quantitative data were analyzed descriptively, while qualitative responses were examined thematically.ResultsFindings reveal that 61.9% of patients consider health data a form of personal property, while 59.5% feel they have limited control over how their data are used. A significant trust deficit was observed, with 50% expressing low confidence in AI systems’ ability to protect privacy, particularly among older participants. Financial incentives strongly influenced willingness to share data, with 81% agreeing to share their data if compensated. Furthermore, 64.3% supported the sale of anonymized data by healthcare providers to technology companies, provided adequate safeguards are in place.DiscussionThese insights underscore the urgent need for robust regulatory frameworks emphasizing informed consent, transparency, and ethical governance in AI healthcare systems. The study highlights the importance of patient-centered policies, equitable compensation mechanisms, and enhanced training and awareness programs to build public trust and ensure responsible AI adoption. By addressing these ethical and governance challenges, policymakers can align technological innovation with equity, privacy, and the principles of ethical healthcare delivery.