AI-induced Deskilling in Medicine: A Mixed-Method Review and Research Agenda for Healthcare and Beyond

Abstract The integration of Artificial Intelligence (AI) in healthcare is reshaping clinical practice, offering both opportunities for enhanced decision-making and risks of skill degradation among medical professionals. This growing impact calls for a comprehensive evaluation of its effects on medical expertise. This study presents a mixed-method literature review, combining systematic analysis with narrative synthesis to examine AI-induced deskilling and upskilling inhibition-the erosion of medical expertise and the reduction of opportunities for skill acquisition due to AI-driven decision support systems. Anchoring the discussion in the core medical competencies outlined by the Federation of Royal Colleges of Physicians of the UK-Practical Assessment of Clinical Examination Skills (PACES-MRCPUK), the systematic review identifies key vulnerabilities in physical examination, differential diagnosis, clinical judgment, and physician-patient communication. The narrative review explores broader themes related to Human–AI Interaction and the Impact of AI on Human Skills in Organizations. In response to concerns about the Second Singularity -a scenario in which decision-making autonomy is increasingly ceded to AI, weakening human oversight-this review advocates for a research agenda that prioritizes longitudinal studies, real-time monitoring of AI’s impact, and the development of frameworks to mitigate skill erosion, ensuring the preservation of professional autonomy and the safeguarding of the irreplaceable elements of human judgment in medicine and beyond.

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Publication Details

Journal
Artificial Intelligence Review
Published
2025-08-27
DOI
https://doi.org/10.1007/s10462-025-11352-1
Citations
34
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
22.25

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article

AI-induced Deskilling in Medicine: A Mixed-Method Review and Research Agenda for Healthcare and Beyond

Federico Cabitza, Chiara Natali, Luca Marconi, Leslye Denisse Dias Duran
34 citations
Artificial Intelligence Review
Artificial Intelligence in Healthcare and Education
22.25
article

AI-induced Deskilling in Medicine: A Mixed-Method Review and Research Agenda for Healthcare and Beyond

Federico Cabitza, Chiara Natali, Luca Marconi, Leslye Denisse Dias Duran
article en
34 citations

Abstract

Abstract The integration of Artificial Intelligence (AI) in healthcare is reshaping clinical practice, offering both opportunities for enhanced decision-making and risks of skill degradation among medical professionals. This growing impact calls for a comprehensive evaluation of its effects on medical expertise. This study presents a mixed-method literature review, combining systematic analysis with narrative synthesis to examine AI-induced deskilling and upskilling inhibition-the erosion of medical expertise and the reduction of opportunities for skill acquisition due to AI-driven decision support systems. Anchoring the discussion in the core medical competencies outlined by the Federation of Royal Colleges of Physicians of the UK-Practical Assessment of Clinical Examination Skills (PACES-MRCPUK), the systematic review identifies key vulnerabilities in physical examination, differential diagnosis, clinical judgment, and physician-patient communication. The narrative review explores broader themes related to Human–AI Interaction and the Impact of AI on Human Skills in Organizations. In response to concerns about the Second Singularity -a scenario in which decision-making autonomy is increasingly ceded to AI, weakening human oversight-this review advocates for a research agenda that prioritizes longitudinal studies, real-time monitoring of AI’s impact, and the development of frameworks to mitigate skill erosion, ensuring the preservation of professional autonomy and the safeguarding of the irreplaceable elements of human judgment in medicine and beyond.

Artificial Intelligence ReviewVol. 58(11)
University of Applied Sciences and Arts of Southern Switzerland (CH), Istituto Clinico Sant'Ambrogio (IT), University of Milano-Bicocca (IT), Ruhr University Bochum (DE)
European Commission
Openalex Percentile: Top 1%
Artificial Intelligence in Healthcare and Education
22.25
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