The near-term payoff from AI in orthopedic surgery is not a robot taking the scalpel. It is a quieter shift happening before the incision and after the patient goes home: faster surgical planning, cleaner prior authorizations, less documentation burden and earlier warning when a recovery goes off track.
Surgeons and orthopedic executives describe AI as a tool moving quickly from novelty to infrastructure. The field is pulling away from experimentation and toward use cases that cut delays, reduce physician burden and extend visibility into recovery. For the leaders running orthopedic service lines and surgery centers, the clearest value is showing up across the full arc of care, not in any single moment in the OR.
The proof points are already concrete. Last year, James Germano, MD, chair of orthopedics at Northwell Health’s Long Island Jewish Valley Stream Hospital in New Hyde Park, N.Y., performed the first AI-assisted total hip replacement in the U.S. using the Ortoma platform. In that case, CT-scan data that typically could take up to two weeks to return was available in four minutes.
Before surgery: from static planning to individualized road maps
For decades, orthopedic surgery has relied on imaging, templates, surgeon experience and increasingly sophisticated implant systems. AI is now compressing parts of that process.
Planning is no longer just about choosing an implant. It is about using anatomy, imaging, outcomes data and risk signals to build an individualized plan before the patient enters the OR. Dr. Germano said AI can turn a process that once took weeks into minutes, while still leaving the surgeon responsible for the final call.
Other surgeons report similar gains. Jonathan Vigdorchik, MD, an orthopedic surgeon at Hospital for Special Surgery in New York City, told Becker’s that AI-assisted surgical planning can now be done “reliably and reproducibly in seconds.” He also pointed to ambient listening tools that generate office notes without forcing physicians to turn away from patients.
That matters in orthopedics, where the preoperative visit often carries the full weight of patient expectation: recovery time, risk, and when a patient can walk, work, drive or return to sports. AI is beginning to help surgeons answer those questions with more data and less guesswork.
Matthew Harb, MD, a hip and knee specialist at The Centers for Advanced Orthopaedics in Washington, D.C., told Becker’s that one of the most important next frontiers is perioperative optimization: identifying high-risk patients, improving clearance and reducing complications before they happen.
That is where the operational case gets sharper. Orthopedic teams still work from fragmented information, with imaging in one system, notes in another, payer requirements elsewhere and patient-reported symptoms scattered across portals and forms. The value of AI is pulling those signals together earlier, before a delay or denial forces a reschedule.
During surgery: decision support, not autonomous surgery
The operating room remains the most visible setting for AI, especially as robotics, navigation and advanced imaging spread through joint replacement and spine surgery. But surgeons draw a firm line between assistance and autonomy.
Dr. Germano said current AI tools offer suggestions that surgeons must accept, reject or adjust, and that AI must clear regulatory and clinical standards before its role expands.
Harpreet Bawa, MD, an orthopedic surgeon at Southern California Orthopedic Institute in Northridge, said personalization is already extending into planning and execution. His practice has moved entirely to robotic-assisted knee replacement, which he said lets him visualize each patient’s anatomy and make tailored adjustments. Even so, he said AI and technology “will never replace the doctor-patient relationship.”
That distinction may define the next phase. Surgeons are not looking for tools that decide for them. They want tools that surface better options faster: implant positioning, alignment, deformity correction, risk signals and recovery expectations.
Yu-Po Lee, MD, an orthopedic surgeon at UCI Health in Irvine, Calif., told Becker’s that AI is already shaping preoperative planning in spine deformity cases, where large datasets help surgeons evaluate alignment goals and support patient-specific rods manufactured before surgery. In other words, AI’s value in the OR often begins long before the first incision.
After surgery: the recovery feedback loop
The postoperative period has long been one of the least visible parts of orthopedic care. Patients go home, attend physical therapy, call if something feels wrong and return for follow-up at set intervals. Much of the recovery story happens outside the surgeon’s view.
AI, wearables and smart implants are changing that.
Michael Seem, MD, an orthopedic surgeon at Winchester (Va.) Orthopaedic Associates, said that AI, robotics and smart implants are creating a more objective view of recovery. Smart knee implants and wearable devices can capture cadence, range of motion and mobility data, letting surgeons see whether a patient is tracking within the expected curve or becoming an outlier.
The implication is earlier intervention. Instead of waiting weeks to learn a patient is struggling, a surgeon can adjust therapy, flag overactivity, call a patient who is not walking enough or spot patterns tied to better long-term outcomes.
Dr. Germano also pointed to postoperative monitoring as a major opportunity, using AI to analyze large recovery datasets and understand why some patients fall short even after technically successful hip and knee replacements. That is the larger promise: not just a faster operation, but a more predictable one for each patient.
Documentation and prior authorization: the invisible work
Some of AI’s most immediate orthopedic gains do not look surgical at all, and they land closest to the revenue cycle. AI scribes are cutting the clerical load of office visits. Prior authorization tools are flagging missing documentation before payer submission. Automated communication is giving patients faster answers before and after surgery.
Paul Bruning, division administrator of Duke University Sports Medicine, Hand and Sports Sciences Institute in Durham, N.C., told Becker’s that Duke Orthopedics has built AI into its prior authorization workflow to review clinical documentation before it goes to payers. He said the effort has improved approval rates, reduced peer-to-peer requests and cut care delays. He did not cite specific figures, and the scale of those gains is not yet quantified.
Edward DelSole, MD, an orthopedic spine surgeon at Keystone Spine & Pain Management Center in Wyomissing, Pa., said workflow automation has produced mixed results: some patients embrace instant responses and 24/7 availability, while others still prefer a person. The right approach, he said, is augmentation, not replacement.
That is the operational lesson. Tools that reduce friction are gaining traction. Tools that add confusion, false certainty or depersonalized communication meet resistance.
The caution: AI can create new problems
The optimism is real, and so are the concerns. Gregory Berlet, MD, retired orthopedic surgeon and co-founder of Orthopedic Foot & Ankle Center in Columbus, Ohio, warned that AI is being deployed widely before it is fully refined. His term for it: “AI slop.” He said patients now arrive with unrealistic expectations shaped by AI tools, forcing surgeons to spend visit time correcting misinformation.
Jeffrey Carlson, MD, an orthopedic spine surgeon at Orthopaedic & Spine Center in Newport News, Va., drew a similar line. He said AI scribes can be “a great time saver,” but that AI in the operating room is overhyped when it pushes surgeons to lean too heavily on machines.
The lesson is not to slow-walk AI. It is that implementation decides the outcome. The tools that last will solve a defined problem, fit the surgeon’s workflow and preserve accountability.
Tony Yi, chief technology and information officer of MedVanta in Bethesda, Md., said his organization evaluates AI not only on return on investment but on value of investment: physician burden, patient satisfaction, feasibility and whether the tool solves a real problem. For orthopedic leaders weighing capital against a crowded vendor market, that is the more useful test.AI is already changing orthopedic care on both sides of the incision. It is making surgical plans faster, documentation less intrusive and payer requirements easier to navigate. It is giving surgeons a more continuous view of recovery. And it is starting to turn large, scattered datasets into individualized care pathways.
The open question is no longer whether AI belongs in orthopedics. It is where. For now the clearest answer is not at the center of the OR replacing judgment. It is around the surgeon, before and after the case, across the administrative and clinical spaces where delays, uncertainty and variation still shape what a patient, and a margin, ends up looking like.
At the Becker’s 32nd Annual Meeting: The Business and Operations of ASCs, taking place October 29-31 in Chicago, ASC leaders, surgeons and healthcare executives will explore strategies to drive growth, enhance operational performance, navigate reimbursement challenges and prepare for the future of ambulatory surgery. Apply for complimentary registration now.
