As artificial intelligence (AI) becomes increasingly visible in healthcare, the central challenge is no longer simply whether these tools have clinical potential, but how healthcare organizations can implement them responsibly. This study examines how clinicians and healthcare administrators perceive diagnostic AI in particular and what factors shape their trust, collaboration, and adoption decisions within U.S. healthcare organizations. Using a qualitative research design, I conducted 20 semi-structured interviews with 10 clinicians and 10 healthcare administrators. The findings show that clinicians and administrators evaluated diagnostic AI through different lenses, with clinicians emphasizing patient care, professional responsibility, and workflow, while administrators focused more on scalability, infrastructure, and organizational feasibility. Participants across both groups also raised concerns about reliability, bias, accountability, and implementation barriers. Together, these findings suggest that successful adoption depends not only on technical performance but also on trust, workflow integration, and governance strategies that account for competing stakeholder priorities.
Isabelle Claire Alexandra Murphy (2026) studied this question.