Artificial intelligence (AI) is rapidly entering orthopedic practice, promising to enhance diagnostics, streamline workflows, and improve patient outcomes. From automated fracture detection to predictive models for surgical risk, the potential is substantial. But as adoption grows, an important question remains: is AI truly improving care, or simply adding complexity?

Where AI Is Making an Impact

AI is already showing value in imaging, with algorithms demonstrating high accuracy in detecting fractures and identifying degenerative changes. Studies such as Lindsey et al. (2018) suggest AI-assisted interpretation can improve diagnostic sensitivity, particularly in high-volume settings.

Beyond diagnostics, AI is being used to predict outcomes such as complications and recovery timelines, helping clinicians better counsel patients and plan interventions.

The Promise and Limitations

AI also has the potential to reduce administrative burden through automated documentation and workflow optimization. However, challenges remain. Many algorithms rely on limited datasets, raising concerns about bias and generalizability. Most tools still function as adjuncts, not replacements, for clinical judgment.

What the Evidence Shows

While early results are promising, strong evidence demonstrating improved long-term patient outcomes is still limited. Much of the current literature focuses on diagnostic performance rather than clinical impact.

AI holds significant promise in orthopedics, but its role is best viewed as supportive rather than transformative, at least for now. Thoughtful, evidence-based integration will be key to ensuring these tools truly enhance patient care.