Intraoperative efficiency has always mattered for ASCs, but achieving it has become increasingly difficult as day-to-day operations evolve. Case volumes are growing, staffing remains tight, and cost pressures continue to mount. All the while, patients still expect the same safe and timely procedures.
Artificial intelligence offers a practical way to meet these challenges, particularly for ASCs evaluating how to improve surgical efficiency with AI without undermining clinical expertise. For example, computer vision systems recognize surgical phases and anticipate instrument needs in real time, while predictive analytics help teams better forecast case duration. A 2024 review of research on AI use in operating room management found that AI can both predict surgical case durations and detect potential surgical case cancellations.
Before diving deeper into how AI fits into intraoperative workflows, it’s important to clarify what we mean by surgical efficiency in the ASC operating room.
Surgical efficiency refers to the ability to move cases through the OR smoothly and predictably. It’s a broad concept covering accurate case timing, instrument readiness, clear communication, and minimal disruptions during surgery.
Even well-run ASCs face barriers to surgical efficiency, such as:
Delayed case starts or overruns
Missing or late instruments
Workflow interruptions
Communication gaps among OR team members
Bottlenecks that affect downstream cases
These challenges make it difficult for teams to maintain consistent intraoperative efficiency using traditional tools alone, creating an opportunity for more data-driven, real-time support.
ASC surgical teams can use AI to improve intraoperative efficiency by enhancing coordination and predictability during surgery. With better visibility into case progression, teams can stay aligned, reduce interruptions, and maintain smoother workflows. These advances illustrate how AI in surgical procedures is increasingly being used to support real-time decision-making inside the operating room.
Computer vision and machine learning systems analyze intraoperative video and real-time signals, such as instrument use and procedural milestones, to track surgical progress as it unfolds. This enables timely, role-specific support that helps surgical teams work together more effectively and respond faster to changing conditions.
In practice, this support often takes the form of cues or alerts delivered during the procedure. AI systems can prompt teams when a surgical phase is nearing completion, highlight deviations from expected workflows, or surface timing and instrument-related insights that help teams make adjustments without interrupting the flow of the case.
Two reviews from 2024, one in the Journal of Medical Systems and the other in Surgical Research, describe how machine learning models combine historical surgical data with real-time signals to generate more accurate estimates of procedure duration and resource needs.
Together, these capabilities support real-time intraoperative workflows in several key ways:
Workflow recognition and prediction: By recognizing surgical phases as they occur, AI helps teams anticipate upcoming steps, reduce unnecessary verbal check-ins, and maintain a steadier case flow.
Role-specific support: AI tools provide surgeons, anesthesia providers, and other OR staff with timely, relevant information that improves coordination during surgery.
Instrument and activity awareness: AI helps teams understand which instruments are in use and what’s coming next, reducing delays, unnecessary handoffs, and the risk of missing or retained instruments.
AI-powered patient monitoring and safety support: Continuous analysis of physiologic and procedural data allows AI to flag abnormal readings, detect deviations from expected surgical workflows, or highlight potential safety risks, supporting timely intervention without increasing cognitive burden.
Importantly, these tools are designed to support, not replace, the surgical team. For ASCs professionals wondering - “Will surgical techs be replaced by AI?”, current implementations reinforce human expertise by reducing manual tracking and cognitive burden rather than completely automating clinical decision-making.
While AI can provide meaningful support during surgery, its effectiveness depends on the quality and availability of the data it receives. That makes interoperability between operating room systems a critical requirement.
Interoperability is fundamental to AI, especially in the operating room. AI systems need structured data that can move freely between technologies to support real-time decisions. Without it, AI tools operate in silos rather than functioning across the operating room.
What does this look like in practice? Interoperable AI systems can:
Access real-time data from anesthesia systems, OR schedules, and device feeds
Align surgical phase recognition with case timing and instrument readiness
Reduce manual handoffs and verbal interruptions during procedures
Provide insights to individual team members instead of isolated alerts
A 2024 review of AI in operating room management describes how machine learning models integrate scheduling data, device feeds, and workflow signals to improve case timing and coordination. AI tools must be integrated into existing clinical workflows rather than operate in isolation.
By translating and contextualizing data between connected systems, AI helps different applications communicate with each other.
For ASCs, immediate benefits include greater procedural predictability, reduced disruption, and improved team coordination .
AI-enabled workflows deliver measurable benefits, including:
More predictable procedure times
Reduced delays and turnover friction
Improved patient safety and satisfaction
Lower stress and cognitive load for staff
Together, these benefits highlight practical ways to optimize surgical procedures with AI while maintaining safety, efficiency, and clinician control. AI is already improving key operational areas, including surgical case duration prediction, PACU resource allocation, and early identification of likely cancellations.
AI adoption in the operating room is still in the early stages, but implementations have already demonstrated its potential to improve ASC surgical efficiency. As the use of AI in surgical procedures continues to advance, ASCs will have even more AI options for enhancing surgical workflow than ever before, including:
Greater use of AI to interpret surgical workflows in real time: Expect continued reductions in non-actionable alerts and advances in role- and phase-aware insights that provide the right information at the right time during surgery.
More modular adoption models: It will become even easier for ASCs to address specific workflow challenges without disrupting existing systems or clinical routines.
Advancements in AI-enabled surgical robotics: Rather than fully autonomous surgery, expect AI to augment robotic systems to improve instrument handling, intraoperative navigation, and ergonomics.
Increased emphasis on clinician-led implementation and governance: There’s a growing movement to involve surgeons and nurses early on to ensure AI tools align with surgical practice.
Implementing new technologies in the OR may feel daunting, but for ASCs considering how to improve surgical efficiency with AI, it doesn’t have to cause upheaval. Surgery centers can introduce AI gradually, starting with targeted applications that address specific workflow challenges such as instrument readiness, turnover coordination, or real-time decision support.
Successful implementations integrate with existing systems, thereby augmenting rather than disrupting clinical workflows. They should be designed in consultation with the surgical teams who will use them. The surgical centers that will benefit most will be those that approach AI deliberately and focus on practical applications that support their teams and strengthen existing operations.
During surgery, AI improves efficiency by recognizing workflow patterns, anticipating next steps, and reducing interruptions through real-time insights and alerts. For ASCs evaluating how to improve surgical efficiency with AI, these tools provide practical, in-the-moment support that strengthens coordination without disrupting care.
Will surgical techs be replaced by AI?No. AI will not replace surgical technologists. While there are many ways to optimize surgical procedures with AI, the technology is designed to enhance the surgical workflow by reducing manual tracking and improving coordination — allowing technologists, physicians, and nurses to focus on patient care.
What AI options for enhancing surgical workflow are most relevant for ASCs today?ASCs can start with AI tools that solve specific pain points. That often means predictive analytics to improve case timing, computer vision to support real-time workflow awareness, and instrument tracking to reduce delays. Which tools matter will vary by the center’s workflows and case mix.
Does AI require major changes to existing OR workflows?No. ASCs can introduce AI gradually to support specific needs. It doesn’t have to disturb established clinical routines. When integrated into existing systems and implemented with clinical input, AI improves efficiency without major disruptions.