ReviewJournal of personalized medicine2026
AI and Its Shifting Roles in the Therapeutic Relationship: Implications for Precision Medicine.
Review in Journal of personalized medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
2 authors.
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Abstract
The emergence and increasing use of artificial intelligence (AI) in healthcare have paved the way for highly personalized and time-saving approaches in the field of precision medicine. It can be applied to determine a prognosis, diagnosis, and recommended treatment, and may also be used for patient monitoring. As AI applications become more widely available, reliable and easy to use, they are rapidly reshaping the traditional roles of professionals and patients in the therapeutic relationship. On the positive side, professionals may have more time to communicate with patients and provide individualized care, whereas patients may become more empowered and autonomous due to AI-facilitated personalized information and monitoring. On the negative side, AI applications threaten to reduce the role of professionals to a mediating one in clinical decision-making, provide patients with misinformation, and lead to misunderstandings that hinder patients' autonomy. In this narrative review, we examine the main ethical issues related to the AI-induced shift in roles in the therapeutic relationship, within four inter-related themes: the validity of claims that algorithms outperform humans in certain tasks; the ways in which AI saves time for health professionals but also takes time to properly explain and implement; the issues of trust and accountability, especially if AI suggestions lead to patient harm; and what AI's alleged cost-effectiveness means for professionals' employment and remuneration. Across the three roles, we find a common pattern: AI tends to absorb the technical and data-processing parts of clinical work while leaving its relational core to humans. Physicians move toward oversight and interpretation, nurses retain the attentiveness and responsiveness that define care, and patients gain tools for self-management that can widen autonomy or, left unguided, erode it. Whether the overall effect is benign depends less on the technology than on how outperformance is evidenced, how the freed time is used, how trust and accountability are anchored in people, and how cost pressures are managed. The article concludes with some suggestions for prudent use of AI in healthcare, indicating the appropriate measures that can be used to harness the power of AI without damaging the traditional cornerstones of the therapeutic relationship.
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