Work

Barriers and facilitators to healthcare artificial intelligence adoption in Wales: findings from focus groups

Year: 2026

Type: article

Abstract: Background: Building on a previous Wales-wide survey, this study aimed to provide more in-depth exploration of the barriers and facilitators to healthcare artificial intelligence adoption in Wales. Objectives: The study aimed to explore these barriers and facilitators among various social groups, to inform policy development in Wales. Methods: Four focus groups were conducted with a group of members of the public and a group of healthcare professionals (both groups recruited from a previous survey), as well as a group Sixth Form students and a group of retired adults. Inductive thematic analysis was used to generate themes and to compare the issues raised by the various groups. Contiguity-based analysis was undertaken to underscore how themes related with each other. Results: A total of 21 individuals participated in the focus groups (healthcare professionals=6, members of the public=6, sixth-form students=5, retirees=4). Seven thematic networks were identified. Across groups, seven themes were identified in the healthcare professional group, six in the general members of the public group, seven in the sixth form student group, and seven in the retiree group. All groups voiced concerns about data privacy and highlighted the importance of human oversight of AI and human contact during the clinical encounter as they expressed more trust in human practitioners. There were though differences between groups, such as greater trust in black-box systems by healthcare professionals, and between individual participants in regard to trust in private organisations developing AI for healthcare organisations. Conclusions: All groups were concerned with information security and expressed a preference for human contact during the clinical encounter and a human-in-the-loop approach. There were differences between the groups, such as in attitudes towards black-box AI technologies and trust in clinicians. No additional barriers or facilitators were identified for proxy consent.

Source: Frontiers in Digital Health

DOI: 10.3389/fdgth.2026.1927799

Authors: Michal Pruski, Jasmine Rollings, Kathleen L. Withers

Institutions: Cardiff and Vale University Health Board, University of Manchester, Cardiff University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,077