From de-skilling to up-skilling: How artificial intelligence will augment the modern physician
Review article, 2026

The integration of artificial intelligence (AI) into orthopaedic practice is no longer a theoretical future but an inevitable reality. As AI models increasingly demonstrate superior performance in specific diagnostic and administrative tasks, concerns have arisen regarding the potential replacement of physicians and the erosion of clinical competency. This narrative review synthesizes current evidence to reframe the debate from a fear of replacement to a strategy of augmentation. Pathways leading to 'deskilling'-the loss of existing expertise-and the emerging threat of 'never-skilling', where trainees fail to acquire foundational proficiencies due to premature reliance on automation, are analysed. Current AI applications function primarily as assistants rather than autonomous agents, offering an opportunity for 'upskilling' by liberating clinicians from repetitive administrative burdens and standardizing diagnostic accuracy. However, realizing this benefit requires deliberate educational mechanisms; one has to argue that maintaining clinical excellence requires a shift in training paradigms, emphasizing critical oversight where human reasoning validates AI outputs. AI will not replace the orthopaedic surgeon in the foreseeable future; rather, it will necessitate an evolution of the physician's role. By automating routine tasks, AI allows the modern physician to operate at a higher level, focusing on complex decision-making, procedural excellence and patient empathy. The future requires mechanisms to ensure AI remains a tool for professional elevation rather than a catalyst for skill degradation. Level of Evidence Level V.

medical education

deskilling

augmentation

artificial intelligence

upskilling

orthopaedics

Author

Felix C. Oettl

University of Zürich

James Pruneski

Tripler Army Medical Center

Balint Zsidai

University of Gothenburg

Yinan Yu

Chalmers, Computer Science and Engineering (Chalmers), Functional Programming

University of Gothenburg

David Fendrich

Tenfifty AB

Thomas Tischer

University of Rostock

Michael T. Hirschmann

Canton Hospital Basel-Land

University of Basel

Stefano Zaffagnini

University of Bologna

IRCCS Ist Ortoped Rizzoli

Kristian Samuelsson

University of Gothenburg

Journal of Experimental Orthopaedics

2197-1153 (eISSN)

Vol. 13 1 e70677

Subject Categories (SSIF 2025)

Orthopaedics

Other Social Sciences not elsewhere specified

DOI

10.1002/jeo2.70677

PubMed

41783687

More information

Latest update

3/13/2026