Artificial intelligence agents in orthopaedics: Concepts, capabilities and the road ahead
Artificial intelligence (AI) is increasingly used in orthopaedics, yet current models are often limited to narrow, isolated tasks like analysing an X-ray or predicting a single outcome. This paper introduces AI agents-a new class of AI systems designed to overcome these limitations. Unlike traditional AI, agents can autonomously manage complex, multistep processes that mirror the complete patient journey. They can coordinate tasks from initial diagnosis and surgical scheduling to postoperative monitoring and rehabilitation, acting as intelligent assistants for clinical teams. This review explains what distinguishes AI agents from conventional AI, explores their potential applications in orthopaedic practice-including perioperative workflow optimisation, research acceleration and intelligent physician support-and discusses the significant implementation and ethical challenges that must be addressed. For the orthopaedic surgeon, understanding AI agents is becoming essential, as these systems offer a transformative potential to enhance efficiency, improve patient outcomes and shape the future of clinical leadership in a technologically advancing field. LEVEL OF EVIDENCE: Level V.
Authors
- Ting Cong (ORCID: https://orcid.org/0000-0003-4262-4674)
- Philipp Wilhelm Winkler (ORCID: https://orcid.org/0000-0002-3997-1010)
- Bálint Zsidai (ORCID: https://orcid.org/0000-0002-5697-6577)
- Yinan Yu
- Kristian Samuelsson (ORCID: https://orcid.org/0000-0001-5383-3370)
- Robert Feldt (ORCID: https://orcid.org/0000-0002-5179-4205)
- James A. Pruneski (ORCID: https://orcid.org/0000-0002-8645-9386)
- Michael Tobias Hirschmann (ORCID: https://orcid.org/0000-0002-4014-424X)
- Felix Conrad Oettl (ORCID: https://orcid.org/0000-0001-9721-685X)
Institutions
- University of Pittsburgh (US)
- University of Basel (CH)
- University of Zurich (CH)
- Tripler Army Medical Center (US)
- Sahlgrenska University Hospital (SE)
- Kepler Universitätsklinikum (AT)
- Universitätsklinik Balgrist (CH)
- Skåne University Hospital (SE)
- Kantonsspital Baselland Standort Bruderholz (CH)
- Chalmers University of Technology (SE)
- University of Gothenburg (SE)
Publication Details
- Journal
- Knee Surgery Sports Traumatology Arthroscopy
- Published
- 2025-10-17
- DOI
- https://doi.org/10.1002/ksa.70109
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.31