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Evaluating AI adoption in healthcare: Insights from the information governance professionals in the United Kingdom

Olawade, David B, Weerasinghe, Kusal, Teke, Jennifer, Msiska, Maines, Boussios, Stergios, Hatzidimitriadou, Eleni (2025) Evaluating AI adoption in healthcare: Insights from the information governance professionals in the United Kingdom. International Journal of Medical Informatics, 199 . Article Number 105909. ISSN 1872-8243. (doi:10.1016/j.ijmedinf.2025.105909) (KAR id:109718)

Abstract

Artificial Intelligence (AI) is increasingly being integrated into healthcare to improve diagnostics, treatment planning, and operational efficiency. However, its adoption raises significant concerns related to data privacy, ethical integrity, and regulatory compliance. While much of the existing literature focuses on the clinical applications of AI, limited attention has been given to the perspectives of Information Governance (IG) professionals, who play a critical role in ensuring responsible and compliant AI implementation within healthcare systems. This study aims to explore the perceptions of IG professionals in Kent, United Kingdom, on the use of AI in healthcare delivery and research, with a focus on data governance, ethical considerations, and regulatory implications. A qualitative exploratory design was employed. Six IG professionals from NHS trusts in Kent were purposively selected based on their roles in compliance, data governance, and policy enforcement. Semi-structured interviews were conducted and thematically analysed using NVivo software, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT). Thematic analysis revealed varying levels of AI knowledge among IG professionals. While participants acknowledged AI's potential to improve efficiency, they raised concerns about data accuracy, algorithmic bias, cybersecurity risks, and unclear regulatory frameworks. Participants also highlighted the importance of ethical implementation and the need for national oversight. AI offers promising opportunities in healthcare, but its adoption must be underpinned by robust governance structures. Enhancing AI literacy among IG teams and establishing clearer regulatory frameworks will be key to safe and ethical implementation.

Item Type: Article
DOI/Identification number: 10.1016/j.ijmedinf.2025.105909
Uncontrolled keywords: NHS policy, AI ethics, Artificial intelligence, Data security, Healthcare governance
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
R Medicine
Institutional Unit: Schools > Kent and Medway Medical School
Former Institutional Unit:
There are no former institutional units.
Funders: University of Kent (https://ror.org/00xkeyj56)
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 22 Aug 2025 08:58 UTC
Last Modified: 30 Aug 2025 02:56 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/109718 (The current URI for this page, for reference purposes)

University of Kent Author Information

Boussios, Stergios.

Creator's ORCID: https://orcid.org/0000-0002-2512-6131
CReDIT Contributor Roles: Methodology, Supervision, Writing - original draft, Writing - review and editing
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