Healthcare Workers’ Perspectives on Artificial Intelligence in Primary Care

Background and Objectives: The integration of artificial intelligence (AI) in healthcare has gained increasing attention to enhance clinical decision-making, service efficiency, and accessibility. While global research highlights both the potential and the challenges of AI implementation, little is known about how primary healthcare professionals perceive and experience this technological shift. This study aimed to examine the attitudes, experiences, and perceived barriers among primary healthcare workers regarding the application of AI in their professional practice. Materials and Methods: A cross-sectional survey was conducted among 678 employees from 43 primary healthcare institutions in Lithuania. Data were collected using a structured questionnaire developed based on existing literature and validated through exploratory factor analysis. Six key factors were identified: perceived AI benefits, threat to professional autonomy, personal readiness and motivation, organizational support and training, ethical concerns, and practical experience. Statistical analysis included ANOVA, t-tests, and Spearman correlation to assess differences across demographic and professional groups. Results: Respondents generally expressed a favorable attitude toward AI, especially recognizing its potential to improve care quality and efficiency. The highest scores were observed in perceived AI benefits and individual readiness. However, practical experience with AI was limited. Significant differences emerged across age, professional role, and years of experience: younger and less experienced staff showed greater enthusiasm and openness to AI, while older and more experienced professionals voiced concerns about autonomy and ethical implications. Organizational support and access to training were positively associated with AI acceptance. Conclusions: Primary healthcare workers are positively inclined toward the adoption of AI but face a gap between perceived potential and actual implementation. Successful integration requires tailored training, strong leadership support, and clear ethical frameworks. Addressing individual, organizational, and ethical factors is critical to fostering trust and enabling sustainable AI use in healthcare settings.