Abstract
Artificial intelligence (AI)-powered voice assistants hold significant potential to transform operating room (OR) interactions by enhancing communication, maintaining sterility, and supporting surgical teams. Designed with advanced natural language processing and speech recognition, such systems—exemplified by the proposed Intelligent Operational Navigator in Operating Room—can document procedures, verify checklists, provide alerts, and reduce human error. Beyond clinical practice, they also offer innovative applications in OR technologist training through simulation, feedback, and adaptive learning. Integrating voice AI into surgery represents a step toward safer, smarter, and more human-centered healthcare, requiring interdisciplinary collaboration for effective development and implementation.
Keywords: Operating room, artificial intelligence, voice assistants, artificial intelligence powered voice assistants, medical education
Operating room (OR) technologists, as vital members of the surgical team, strive to ensure safe and effective surgeries and are responsible for maintaining sterile conditions. In a complex and sensitive environment, they must manage time in addition to preparing instruments, monitoring the sterile field, and anticipating the surgeon's needs. Due to these complex conditions and the imperative to maintain sterility, effective and safe communication in the OR remains extremely challenging. 1
The design of an artificial intelligence (AI)-powered voice assistant for the OR could enable timely communication and interaction while preserving sterile conditions. This voice assistant could be similar to common examples like Siri, Alexa, or Google Assistant, which have been previously developed for clinical settings. With the advancements in AI, particularly in the fields of natural language processing and speech recognition, AI now has the potential to support real-time communication and documentation in the OR.2,3
The application of this AI capability in the OR could potentially facilitate the following actions:
Documenting critical and high-risk procedures.
Verifying surgical checklists.
Providing reminders and alerts to the surgical team.
Facilitating communication among team members.
Supporting educational and simulation scenarios.
For example, consider an AI voice assistant, fully trained for the OR environment, named Intelligent Operational Navigator in Operating Room (IONOR). As an active system, IONOR listens to the sounds in the OR, identifies patterns, and, based on its safety checks, provides situation-based suggestions (Figure 1: Conceptual architecture of IONOR, see below).
Figure 1.
Conceptual architecture of IONOR. The diagram illustrates the workflow of the AI-powered voice assistant in the operating room. Audio signals from the OR are captured and processed via speech recognition and natural language processing. Identified intents and safety rules guide the generation of context-specific prompts and alerts, which are then documented and integrated with the EHR for auditing and quality improvement purposes. IONOR: intelligent operational navigator in operating room; AI: artificial intelligence; EHR: electronic health record; OR: operating room.
Clinical practical message
The integration of voice AI in the OR may enhance situational awareness, support adherence to protocols, and reduce the risk of procedural errors. While preliminary studies suggest improved documentation and error mitigation, further real-world validation is required to confirm these outcomes. This technology is intended to complement, not replace, human expertise, providing cognitive support to technologists and surgeons alike.
Ethical, legal, and privacy considerations
Implementation of AI assistants in the OR requires careful attention to ethical, legal, and privacy concerns. Patient data must be securely handled, and AI recommendations should not override clinical judgment. Institutions must establish accountability frameworks, ensure compliance with healthcare regulations, and provide transparency on data use and algorithmic decision-making. In addition, training personnel to appropriately interact with AI systems is essential to avoid overreliance or automation bias.
A glimpse into the future: The or transformed
Following the start of a coronary artery bypass surgery, the OR was quiet, with the entire team focused on their tasks. Dr Martin, the lead surgeon, worked with swift precision using his gloved hands. Sarah, the OR technologist, stood beside him like a seasoned orchestra conductor, ready to exchange instruments. The sounds in the room were low and precise, a cryptic language of surgical terminology.
Suddenly, a calm but firm voice was heard from the room's sound system: IONOR: “Final count protocol has not been initiated. Surgical sponge usage is higher than average.”
Sarah was taken aback. She immediately began a manual count. One sponge was missing. Tension rose, and the team paused momentarily. A controlled but hurried search began. After a few moments, the missing sponge was found under a surgical retractor. A disaster had been narrowly averted.
The surgeon nodded in approval and said, “A good catch.”
“Thank you, IONOR,” Sarah replied.
Preliminary evidence suggests that AI voice systems in the OR may reduce errors, improve documentation accuracy, and provide cognitive support for busy technologists. 4 Reports generated by AI can also support post-operative review and continuous quality improvement.
Transforming education with AI voice assistants
In addition to their clinical applications, AI assistants may transform training programs for OR technologists:
Posing scenario-based questions to encourage engagement.
Providing continuous feedback.
Simulating real-time OR procedures.
Ensuring competency-based education.
Enabling personalized learning through adaptive algorithms.
Example scenario: During a virtual training session, a student is prompted by IONOR: “Please verify instrument counts before proceeding to suture closure.” The system monitors the response, provides immediate corrective feedback if errors occur, and records performance metrics for competency assessment.
Furthermore, students’ interaction with AI in virtual environments enhances their skills in working with new technologies, preparing them for the ORs of the future. 5
Safety, robustness, and workflow integration
Key considerations for implementing voice AI in the OR include:
Recognition robustness in noisy OR environments.
Alarm fatigue and mitigation strategies.
Automation bias and human-in-the-loop controls.
Privacy and security safeguards.
Integration into existing workflow to support, not disrupt, the surgical team.
These measures ensure that AI serves as a supportive tool, enhancing safety and efficiency while maintaining human oversight.
A call for reflection and action
Given the increasing adoption of AI in healthcare, exploring its use in the OR and in personnel training is essential. Voice assistants, such as IONOR, may combine technological innovation with human expertise, enhancing precision, safety, and learning outcomes.
We recommend that development, testing, and implementation be conducted through interdisciplinary collaborations between software developers, educators, and clinical specialists. The future of surgery depends not only on skilled hands but also on intelligent, supportive technologies capable of maximizing human potential.
The OR of the future may be smarter, safer, faster, and more human-centered.
Acknowledgment
The authors would like to thank Shahid Beheshti University of Medical Sciences for their valuable guidance and support during the preparation of this study. No real patients were involved in the study.
Footnotes
ORCID iD: Ashkan Karimi https://orcid.org/0000-0002-0306-6772
Author contributions: Ashkan Karimi: Conceptualization, methodology, writing—original draft preparation. Sara Bagheri and Zohreh Khoshgoftar: Data curation, visualization, review & editing. Ashkan Karimi and Sharareh Karimi: Supervision, validation, writing – review & editing. All authors have read and approved the final manuscript.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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