Bridging trust gaps: Stakeholder perspectives on AI adoption in the United Kingdom NHS primary care.

Objectives: This study investigates the factors influencing artificial intelligence (AI) acceptance in the United Kingdom (UK) National Health Services (NHS) primary care across different stakeholder levels. It explores key barriers and enablers, focusing on workforce impact, organisational influences and ethical considerations. Methods: A mixed-methods, between-subjects approach was employed to capture stakeholder perspectives on AI trust and acceptance. Eligible participants were NHS primary care employees working at macro-, meso- and micro-levels. An online survey was distributed via Prolific and included both closed- and open-ended questions. This was followed by semi-structured interviews with a subset of volunteers. Quantitative data were analysed using descriptive statistics and qualitative responses were examined using abductive thematic analysis. Results: The study gathered 133 responses and conducted nine follow-up interviews. Three key themes were identified: (1) Workforce impact and resistance to change - concerns about job loss and skills gaps; (2) Organisational and cultural barriers - challenges around validation, leadership buy-in and integration; and (3) Trust, ethics and equity - fears about fairness, accountability and the exacerbation of healthcare disparities. Findings revealed that meso-level stakeholders (primary care managers) act as both facilitators and barriers to AI adoption, mediating between macro-level policymakers and micro-level frontline healthcare professionals while navigating organisational constraints and workforce concerns. Conclusion: The findings underscore the necessity for ethical and trustworthy AI systems, targeted stakeholder engagement, and strategies to ensure equitable and effective AI implementation in primary care. Further research should examine how trust influences AI adoption and equity in care delivery.