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A new BMJ series has examined how artificial intelligence is becoming a third party in clinical consultations and reshaping interactions between doctors and patients. The series describes the emergence of triadic care, a model in which clinicians, patients, and AI jointly influence clinical encounters. It explains that while this technological shift has the potential to transform healthcare, the presence of AI can alter dynamics of trust, empathy, and communication that underpin person-centered care.

The authors indicate that safe and effective adoption depends on strong governance and institutional readiness to maintain trust, ensure patient safety, and uphold clinical standards. An accompanying editorial notes that regulatory approaches are developing globally but remain inconsistent, and many healthcare institutions lack basic AI governance structures. The editorial reports that some institutions deploy AI tools without sufficient oversight, creating risks to patient safety and clinical quality.

The editorial also states that technology companies developing healthcare AI hold substantial responsibility for safe deployment, although accountability mechanisms remain limited. It outlines that coordinated governance frameworks are necessary and that healthcare institutions should implement comprehensive AI governance structures before widespread deployment. It adds that regulatory bodies need flexible guidelines that can adapt to the pace of AI advancement while maintaining rigorous safety and efficacy standards.

According to the editorial, technology companies must meet high transparency standards for post-market surveillance and adopt clear accountability processes. It further notes that professional associations and licensing bodies should require AI literacy training for healthcare professionals and adjust liability frameworks to reflect the triadic care model. The authors warn that without coordinated action, the benefits of AI could be undermined by preventable harms and a loss of public trust.

In the first article of the series, the authors examine how clinicians and patients already rely on AI during consultations, leading clinicians to focus increasingly on helping patients interpret AI-generated information in context. They explain that simple infrastructure measures such as documentation standards and transparent technology can support safe and observable integration of AI. They also emphasize the need for research to analyze how AI changes the doctor-patient relationship and to develop frameworks for this evolution.

Upcoming articles in the series will discuss the patient experience and the competencies clinicians need to use AI transparently and effectively in clinical encounters. The BMJ has stated that the series is intended to support clinicians as they navigate the integration of AI into routine care.