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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial intelligence agents in orthopaedics: Concepts, capabilities and the road ahead

Ting Cong, Philipp Wilhelm Winkler, Bálint Zsidai, Yinan Yu et al.
2 citations
Knee Surgery Sports Traumatology Arthroscopy
Artificial Intelligence in Healthcare and Education
1.31
article

Artificial intelligence agents in orthopaedics: Concepts, capabilities and the road ahead

Ting Cong, Philipp Wilhelm Winkler, Bálint Zsidai, Yinan Yu, Kristian Samuelsson, Robert Feldt, James A. Pruneski, Michael Tobias Hirschmann, Felix Conrad Oettl
article en
2 citations

Abstract

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.

Knee Surgery Sports Traumatology ArthroscopyVol. 33(12)
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)
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
1.31
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.