Although AI is in its infancy in healthcare, spine surgeons have found major advantages with the technology from improving imaging to administrative work.
Spine surgeons discuss what they want to do with AI in the next year.
Ask Spine Surgeons is a weekly series of questions posed to spine surgeons around the country about clinical, business and policy issues affecting spine care. Becker’s invites all spine surgeon and specialist responses.
Next question: Which factor is driving the most change in your practice today — reimbursement, regulation, technology, or patient demand?
Please send responses to Carly Behm at cbehm@beckershealthcare.com by 5 p.m. CDT Tuesday, Dec. 30.
Editor’s note: Responses were lightly edited for clarity.
Question: How do you want to leverage artificial intelligence in 2026?
Jordan Iordanou, MD, PhD. McHugh Neurosurgery (West Islip, N.Y.): In 2026, I plan to leverage AI for improved surgical planning and intraoperative navigation, enhancing precision in complex spine procedures. AI-driven predictive analytics will also help identify patients at risk of complications, optimizing outcomes. Integrating these tools into my practice will streamline workflows and elevate patient care.
Noam Stadlan, MD. Endeavor Health Neurosciences Institute (Skokie and Highland Park, Ill.): Artificial intelligence is currently very useful in the creation of office notes from a recording of the office visit. It also can be very helpful in research. However, at this point, all results must be double checked due to the small but present incidence of “hallucinations” where the AI information is not accurate or even manufactured. Like any other tool, it is useful when applied to appropriate situations with appropriate checks on accuracy. As it improves, it may be beneficial in surgical planning, especially with deformity surgery.
Alex Vaccaro, MD, PhD. Rothman Orthopaedics (Philadelphia): In 2026, we want to continue our journey in implementing artificial intelligence across our practice. Our healthcare partner, Thomas Jefferson University, is increasing its use of Ambient AI scribe that generates comprehensive clinic notes from physician-patient conversations. This will free doctors from the keyboard while capturing discrete data and quality metrics.
The consistency of this AI-captured data will help create a comprehensive internal database, accelerating clinical research and quality improvement initiatives. This structured documentation will then fuel an AI patient selection platform, which analyzes a patient’s full medical profile, from MRI imaging to potential wearable data. This information can then be used to calculate personalized risk scores.
Simultaneously, this AI-generated note will optimize revenue cycle by ensuring accurate coding, identifying all billable procedures or tasks, and performing pre-submission audits to prevent claim denials. This proactive approach to billing integrity will significantly reduce administrative waste and strengthen a health systems financial position in an increasingly complex value-based care landscape.
Our AI strategy will extend into the operating room in our physician-owned hospitals and ASCs
to maximize efficiency and output. An AI scheduler is learning each surgeon’s operative patterns and forecast case durations by analyzing patient-specific factors like BMI and surgical complexity. The system will be responsive enough to dynamically re-schedule the entire surgical day in response to emergencies or unexpected delays, minimizing downstream issues. This enables a real-time AI co-pilot to monitor multiple rooms, alerting surgeons precisely when they are needed so other tasks can be performed as one waits for their surgery to begin. This creates a shared, real-time awareness across the entire surgical team, reducing cognitive load and allowing for better anticipation of instrument and staffing needs for subsequent cases. By minimizing idle OR time and staff overtime while safely increasing case volume, this comprehensive AI integration will transform our surgical pathway into a data-driven system that enhances both clinical outcomes and financial performance.
Vijay Yanamadala, MD. Hartford (Conn.) HealthCare: AI applications in spine care range from imaging analysis to surgical planning to outcome prediction. Current promising areas include automated measurement of spinal parameters on imaging, prediction of fusion success based on multiple variables, and surgical planning assistance. However, challenges include data quality, algorithm validation, regulatory approval, and integration with existing workflows. The most realistic near-term applications may be decision support tools rather than autonomous systems.
Jacky Yeung, MD. Yale School of Medicine (New Haven, Conn.): In 2026, I see AI as an extension of the surgeon’s mind, helping us think more comprehensively, plan more precisely, and achieve better functional outcomes. Rather than relying solely on generalized alignment targets, AI can help us model ideal postoperative parameters based on patient-specific factors such as pelvic incidence, global balance, and adjacent segment motion. That kind of predictive modeling can significantly improve surgical precision, reduce revision rates, and advance truly personalized spine surgery.
Christian Zimmerman, MD. St. Alphonsus Medical Group and SAHS Neuroscience Institute (Boise, Idaho): A decade ago, the consummation of artificial intelligence was ethereal, impending and not well understood. An internet search from a borrowed server gave superficial knowledge on a point-specific question or notification that the desired information was unavailable. Fast forward to today. A simple asking delivers a biased coded algorithm which reinforces detailed responses and surveillance technologies tracking people with frightful precision. In healthcare, the app-driven, automated decision-making of surgical strategies can strip away individual training and deepen existing reliances. There is a simple and troubling fact that all must ponder and resist: the more we rely on AI, the more we must ask who controls it, how it operates, and what values are embedded within its seemingly neutral code.
