Healthcare Providers’ Perceptions of Artificial Intelligence in Prehospital Care: A Qualitative Meta-Synthesis

Background: Artificial intelligence (AI) has the potential to enhance prehospital emergency care through decision support tools and triage systems. However, healthcare providers’ perceptions significantly influence the adoption and integration of these technologies. Objective: To synthesize qualitative evidence on prehospital providers’ perceptions of AI and identify common themes that inform implementation and future research. Methods: A systematic search of major databases (PubMed, Scopus, CINAHL, PsycINFO, and Web of Science) identified qualitative studies focusing on healthcare providers’ views of AI in prehospital settings. Four studies involving 1,831 participants, including paramedics, nurses, and physicians, met the inclusion criteria. Thematic synthesis was conducted using the Braun and Clarke framework. Results: Six key themes were identified: (1) perceived clinical utility of AI, (2) concerns about data privacy and security, (3) impacts on workload and fears of job replacement, (4) engagement and adherence challenges, (5) educational needs, and (6) integration into clinical workflows. Acceptance of AI varied by professional role and training level. Trust and understanding were critical to increasing acceptance. Conclusion: Healthcare providers hold mixed attitudes toward AI in prehospital care. Addressing concerns through education, transparent system design, and regulatory guidance is essential to support adoption. Involving EMS stakeholders is vital for successful and ethical AI integration.