Surgical Assistants

29-9093.00
Median wage $66,800/yr22,270 employed (US)Rank #922 of 923 scored · top 100% by substitution

Assist in operations, under the supervision of surgeons. May, in accordance with state laws, help surgeons to make incisions and close surgical sites, manipulate or remove tissues, implant surgical devices or drains, suction the surgical site, place catheters, clamp or cauterize vessels or tissue, and apply dressings to surgical site.

Sub-scores

0–100 · band = confidence interval from rater disagreement

Substitution4
Exposure4
Augmentation26

Substitution — the headline: capability discounted by cost, barriers and adoption.

Exposure — technical capability alone, regardless of whether anyone deploys it.

Augmentation — how much AI assists without replacing. High here + moderate substitution = a changing job, not a disappearing one.

Tasks on the substitution scale

28 rated tasks, binned by substitution score.

Position among all scored occupations

Distribution of 923 occupation scores; the marker is this occupation.

Tasks with substitution ≥ 70

0%

Run 1.0.0-draft.1 · computed 2026-08-05 · rater panel: claude-sonnet-5, claude-haiku-4-5-20251001 · intervals span rater disagreement.

Why this score

The five weighted dimensions of the composite, averaged across this occupation's tasks (importance-weighted, panel mean). Exact weights and formulas: /api/v1/methodology.

Task automatabilityw 35%4

panel mean rating 1.2/5 → substitution pressure 4/100

Technical feasibility todayw 20%3

panel mean rating 1.1/5 → substitution pressure 3/100

Cost vs. human wagew 15%2

panel mean rating 1.1/5 → substitution pressure 2/100

Adoption barriersw 20%inverted — strong barriers lower the score5

panel mean rating 4.8/5 (barrier strength) → substitution pressure 5/100

Sector adoption velocityw 10%3

panel mean rating 1.1/5 → substitution pressure 3/100

Task breakdown (28 tasks)

Substitution pressure per task, weighted by O*NET importance in the composite. Expand a task for the full rater audit trail — every rating, every model, every rationale.

Determine availability of necessary equipment or supplies for operative procedures.

25

CI 25–25 · exposure 25 · augmentation 50 · importance 4.6/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Hospital supply chain automation is digitizing slowly; most surgical centers still rely on manual or semi-automated processes. While some health systems pilot AI supply chain tools, production adoption remains limited and confined to large academic medical centers. Physical inventory work and procedural specificity slow diffusion.
Sector adoption velocityclaude-sonnet-52/5Healthcare, especially surgical settings, is a slow-adopting sector for AI in physical/safety-critical workflows, with digitization of inventory being the main current use case rather than full task automation.
Augmentation potentialclaude-haiku-4-5-202510013/5AI can meaningfully assist by flagging low-stock items, suggesting alternatives based on procedure type, and providing predictive alerts before shortages occur. However, the human surgical assistant remains essential for validating availability, communicating with OR teams, and handling exceptions—AI augmentation is useful but not transformative.
Augmentation potentialclaude-sonnet-53/5AI-enabled inventory tracking and predictive supply systems can flag shortages or mismatches ahead of time, helping surgical assistants plan more efficiently, though the physical determination remains manual.
Task automatabilityclaude-haiku-4-5-202510012/5Current AI systems struggle with real-time inventory visibility and dynamic availability checking across distributed surgical supply chains. While automated tracking systems exist, determining *necessity* for a specific operative procedure requires contextual medical knowledge, procedure type, patient factors, and complex decision-making that AI cannot reliably automate end-to-end today.
Task automatabilityclaude-sonnet-52/5This requires physical verification of instruments/supplies in an OR and coordination with sterile processing, which current AI cannot perform end-to-end; inventory checking software can assist but not replace the physical/procedural judgment involved.'
Adoption barriersclaude-haiku-4-5-202510014/5Surgical environments are heavily regulated (FDA, hospital credentialing, Joint Commission standards) and rely on human accountability for patient safety. There is strong organizational friction: surgical teams have established protocols requiring human sign-off on equipment availability before procedures, and liability asymmetry means an AI error in supply verification could delay critical surgery.
Adoption barriersclaude-sonnet-54/5Patient safety regulations and hospital accreditation standards require human verification of surgical readiness, and liability for missing equipment during surgery creates strong barriers to full automation.
Cost vs. human wageclaude-haiku-4-5-202510012/5AI-driven inventory and supply chain optimization systems are expensive to implement and integrate into existing hospital infrastructure (EHR/operating room systems). The cost of deployment, maintenance, and the human oversight required to validate AI recommendations typically exceeds the cost of a surgical assistant manually checking supplies.
Cost vs. human wageclaude-sonnet-52/5Inventory software has upfront and integration costs comparable to or exceeding the marginal cost of a surgical assistant performing this check, since human verification is still required for safety-critical confirmation.
Technical feasibility todayclaude-haiku-4-5-202510012/5Limited deployed products perform this task reliably in production; most hospitals rely on manual inventory checks, ERP systems with poor integration to surgical workflows, or nascent RFID/IoT tracking that lacks AI-driven predictive capability. Existing systems have significant gaps in real-time visibility and fail to proactively flag shortages.
Technical feasibility todayclaude-sonnet-52/5Hospital inventory management systems exist and are deployed, but they don't autonomously determine case-specific equipment readiness or perform physical checks; this remains largely a human task with software support.

Adjust and maintain operating room temperature, humidity, or lighting, according to surgeon's specifications.

19

CI 0–39 · exposure 20 · augmentation 38 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare facilities, especially surgical settings, adopt automation conservatively and slowly; OR infrastructure is capital-intensive and highly regulated, with strong institutional preference for human oversight of environmental conditions during procedures.
Sector adoption velocityclaude-sonnet-52/5Healthcare facilities, especially operating rooms, are typically slow adopters of full automation for physical environmental controls due to safety-critical context and conservative capital cycles.
Augmentation potentialclaude-haiku-4-5-202510012/5Simple alerts or readouts showing current temperature and humidity could modestly assist a surgical assistant, but the task is fundamentally about manual adjustment and responsiveness, where AI provides minimal leverage over human judgment and control.
Augmentation potentialclaude-sonnet-53/5Smart building systems and sensor-based automation can assist staff by pre-setting or suggesting adjustments, but a human still needs to confirm and fine-tune settings per surgeon's specific real-time requests.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires real-time environmental monitoring and responsive adjustment based on surgeon directives in a dynamic operating room setting. Current AI systems lack the embodied sensors and actuators to physically control HVAC and lighting systems, and lack the in-situ contextual awareness to interpret nuanced surgeon preferences.
Task automatabilityclaude-sonnet-53/5Adjusting environmental controls via digital systems could be automated with sensors and preset protocols, but requires physical presence for verification and adaptation to surgeon's real-time preferences during a procedure.atability.
Adoption barriersclaude-haiku-4-5-202510015/5Operating rooms are heavily regulated (FDA, CMS, Joint Commission) with strict environmental standards and sterility protocols. Human surgical assistants are required by law and accreditation standards to be present; autonomous systems would require regulatory approval and cannot guarantee compliance with real-time infection-control standards.
Adoption barriersclaude-sonnet-53/5While no strict licensing is required for adjusting thermostats, hospital safety protocols, infection control standards, and surgeon preference/trust in a sterile environment create real organizational friction against removing human oversight.
Cost vs. human wageclaude-haiku-4-5-202510011/5Retrofitting an OR with autonomous environmental sensing and control would require significant hardware, integration, and maintenance costs that far exceed the wage cost of a surgical assistant performing this task manually.
Cost vs. human wageclaude-sonnet-52/5Installing and integrating smart environmental control systems requires significant capital investment and hospital-wide infrastructure changes, making near-term AI cost comparable to or higher than simply having staff adjust settings manually.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI system independently manages OR environmental controls; existing building management systems are not AI-driven and require manual human intervention or programmable presets, not real-time adaptive control responsive to surgeon feedback.
Technical feasibility todayclaude-sonnet-52/5Building automation systems (smart HVAC, lighting control) exist in modern hospitals but are not typically AI-driven agents interpreting surgeon-specific specifications in real time; this remains largely manual or rule-based, not AI-product driven.

Monitor patient intra-operative status, including patient position, vital signs, or volume and color of blood.

16

CI 7–25 · exposure 17 · augmentation 63 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5While operating room monitoring systems are widely deployed, they function as alerts and dashboards that augment rather than replace human assistants; true displacement of the monitoring role has been minimal, and most surgical teams continue to employ dedicated personnel for this task.
Sector adoption velocityclaude-sonnet-52/5Operating rooms adopt AI-assisted monitoring devices slowly due to regulatory approval, hospital procurement cycles, and safety-critical validation requirements, unlike fast-moving information-sector adoption.
Augmentation potentialclaude-haiku-4-5-202510014/5AI-powered vital sign dashboards, automated alerts, and image analysis tools substantially assist surgical assistants by highlighting changes, reducing manual charting burden, and improving data visibility, allowing the human to focus on other critical monitoring tasks and exception handling.
Augmentation potentialclaude-sonnet-53/5AI-enabled monitors (e.g., smart vital sign trackers, predictive alert systems) can help flag anomalies and support the assistant's situational awareness, but do not replace continuous physical observation and judgment.
Task automatabilityclaude-haiku-4-5-202510012/5While AI can process vital sign data and image analysis of blood volume/color in structured formats, the integrated task of continuous intra-operative monitoring—including patient positioning assessment, contextual vital sign interpretation, and rapid exception detection—requires real-time judgment and integration that current AI systems cannot perform reliably end-to-end without substantial human oversight.
Task automatabilityclaude-sonnet-51/5Real-time intra-operative monitoring requires physical presence, tactile judgment, and immediate manual intervention (repositioning, suctioning, alerting surgeons) that current AI cannot perform end-to-end.
Adoption barriersclaude-haiku-4-5-202510014/5Surgical monitoring has strong regulatory and liability barriers: a credentialed human assistant must remain legally responsible for patient safety during surgery, and hospitals face significant liability exposure if automated systems miss critical changes, creating hard barriers to full substitution.
Adoption barriersclaude-sonnet-55/5This is a licensed clinical function performed in the sterile field during surgery, with direct patient safety and liability implications, requiring a credentialed human present at all times.
Cost vs. human wageclaude-haiku-4-5-202510012/5Current AI monitoring systems require significant hardware, integration, and human oversight costs that approach or exceed the loaded wage of a surgical assistant, especially when accounting for liability and redundancy requirements in surgical settings.
Cost vs. human wageclaude-sonnet-51/5A human surgical assistant is required in the room regardless of AI monitoring tools, so AI does not reduce the need for paid human labor performing this task; cost is additive, not substitutive.
Technical feasibility todayclaude-haiku-4-5-202510012/5Deployed products exist for individual components (e.g., vital sign monitoring dashboards, automated vital sign alerts), but no end-to-end system reliably performs the full monitoring task as described, including accurate real-time assessment of patient position and blood characteristics without frequent false alarms or human verification.
Technical feasibility todayclaude-sonnet-52/5AI-based vital sign monitors and alarm systems exist and are deployed, but interpreting blood volume/color and adjusting patient position in real time remains a human physical and cognitive task with no autonomous product performing the full function.

Gather, arrange, or assemble instruments or supplies.

9

CI 5–14 · exposure 8 · augmentation 13 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare, particularly surgical services, adopts automation slowly. Even well-resourced hospitals have minimal adoption of robotic instrument management; most rely on traditional surgical technician roles with modest digitization.
Sector adoption velocityclaude-sonnet-51/5Healthcare physical task environments, especially operating rooms, show very slow AI/robotics adoption for manual instrument handling due to safety-critical constraints and low digitization of this specific task.
Augmentation potentialclaude-haiku-4-5-202510012/5Current AI offers limited assistance—simple inventory tracking or instrument counting tools provide marginal help, but AI cannot yet meaningfully augment the core task of hands-on arrangement and quality verification of sterile surgical supplies.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no current assistance for the physical gathering and arranging of surgical instruments, as this is a manual, tactile task with no digital interface for AI tools to support.
Task automatabilityclaude-haiku-4-5-202510012/5While robotic arms and computer vision can identify and locate surgical instruments, reliably assembling sterile surgical trays with precise instrument positioning and maintaining sterile protocol remains difficult. Current systems lack the dexterity, real-time adaptability, and contamination-awareness to achieve 50% time savings at equal quality in a clinical setting.
Task automatabilityclaude-sonnet-51/5This requires physical manipulation of sterile instruments in a dynamic OR environment, which current AI systems (including robotics) cannot perform reliably or safely end-to-end.
Adoption barriersclaude-haiku-4-5-202510014/5Surgical environments are heavily regulated (FDA, hospital credentialing, Joint Commission standards), and sterile field preparation has strict legal and liability requirements. Most hospitals require certified surgical technologists or assistants to perform and verify instrument sterilization and arrangement due to patient safety and regulatory mandates.
Adoption barriersclaude-sonnet-54/5Sterile technique, infection control protocols, and surgical safety regulations require trained, credentialed personnel to handle instruments, creating strong procedural and liability barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Specialized robotic systems capable of handling delicate surgical instruments aseptically would require significant capital investment, ongoing maintenance, and software licensing, making per-task costs substantially higher than employing surgical assistants.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this physical task at scale, so no meaningful cost comparison favors AI; a human is required and cheaper than any hypothetical robotic solution.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs end-to-end surgical instrument gathering, arrangement, and assembly at clinical scale. Some research prototypes exist, but no production systems routinely substitute for surgical assistants in real operating rooms.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously gathers or arranges surgical instruments in real operating rooms today; this remains beyond current robotics and AI capability in production settings.

Verify the identity of patient or operative site.

7

CI 0–14 · exposure 13 · augmentation 25 · importance 5.0/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Despite regulatory pressure for safety innovation, healthcare remains highly conservative and heavily regulated. Adoption of autonomous patient verification AI in surgical settings is minimal; adoption remains at pilot stage only, driven by compliance rather than efficiency gain.
Sector adoption velocityclaude-sonnet-51/5placeholder
Augmentation potentialclaude-haiku-4-5-202510012/5AI could assist by pre-flagging data mismatches or alerting staff to protocol deviations, but the core task—human verification of patient identity—leaves little room for meaningful augmentation without introducing error or liability.
Augmentation potentialclaude-sonnet-52/5placeholder
Task automatabilityclaude-haiku-4-5-202510011/5Patient identification is a human-facing, real-time verification task requiring direct sensory confirmation and real-world accountability. Current AI systems cannot reliably match patient identity to operative site in a surgical environment without human oversight and cannot meet the 50% time-saving bar as the task is already rapid when performed by trained staff.
Task automatabilityclaude-sonnet-52/5Identity/site verification requires physical presence, direct communication with the patient, and cross-checking wristbands, charts, and markings; AI cannot perform the physical verification act itself today."},"feasibility":{"rating":1,"rationale":"No deployed product autonomously performs patient identity or surgical site verification in the OR; this remains a manual clinical safety checklist step (e.g., Universal Protocol) executed by staff.","automatability_note":""},"cost_ratio":{"rating":1,"rationale":"There is no viable AI substitute performing this task independently, so cost comparison favors the human who must be present regardless."},"barriers":{"rating":5,"rationale":"This is a mandated patient-safety protocol (e.g., Joint Commission Universal Protocol) requiring qualified clinical personnel to verify identity and site, with high liability for errors like wrong-site surgery."},"adoption_velocity":{"rating":1,"rationale":"Surgical settings are highly regulated and physically grounded with minimal AI adoption for this specific safety-critical verification step."},"augmentation":{"rating":2,"rationale":"Digital tools like barcode scanning and EHR cross-referencing can support verification, but AI's role is marginal beyond existing checklist and ID-scanning systems already in use."}}```An error occurred—my output didn't match the exact schema. Let me redo this properly.{
Adoption barriersclaude-haiku-4-5-202510015/5This task is legally and ethically mandated to be performed by a credentialed human (Joint Commission, surgical protocols). Liability and patient safety regulations create hard barriers: a licensed provider must perform and certify patient identity as a condition of informed consent and surgical protocol compliance.
Adoption barriersclaude-sonnet-55/5placeholder
Cost vs. human wageclaude-haiku-4-5-202510011/5Implementation of AI-based identity verification systems (hardware, integration, redundancy, and oversight) would be more expensive than the minimal labor cost of a surgical assistant performing a 30-second verbal or visual check.
Cost vs. human wageclaude-sonnet-51/5placeholder
Technical feasibility todayclaude-haiku-4-5-202510012/5While biometric and imaging systems exist (facial recognition, ID scanning), they are not reliably deployed in sterile surgical environments at the moment of verification, and any errors carry catastrophic liability. No mature production system performs independent patient identity verification in OR settings without human confirmation.
Technical feasibility todayclaude-sonnet-51/5placeholder

Remove patient hair or disinfect incision sites to prepare patient for surgery.

7

CI 0–14 · exposure 8 · augmentation 0 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Despite automation enthusiasm in healthcare, surgical prep remains a low-volume, high-touch task performed by credentialed staff under strict protocols. Adoption of AI/robotic skin prep is virtually zero; institutional inertia and regulatory caution dominate.
Sector adoption velocityclaude-sonnet-51/5Healthcare physical prep tasks show minimal AI/robotic adoption; surgical support staff continue to perform this manually with no signs of automation deployment.
Augmentation potentialclaude-haiku-4-5-202510011/5AI offers no meaningful assistance to a surgical assistant performing hair removal and disinfection; the task is procedural, brief, and already highly efficient with current human workflow. Augmentation tools (e.g., computer vision for site identification) would add complexity without clear productivity gain.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no assistance for this manual physical preparation task, as it involves tactile, hands-on patient contact rather than information processing.
Task automatabilityclaude-haiku-4-5-202510012/5Hair removal and disinfection involve physical manipulation of a patient's body in a sterile field. While robotic arms can theoretically execute these motions, current AI systems lack the real-time tactile feedback, adaptability to variable anatomy, and reliable sterile-field protocol compliance needed to autonomously perform these tasks safely and at quality parity with trained surgical assistants.
Task automatabilityclaude-sonnet-51/5This is a physical, hands-on task requiring direct manipulation of a patient's body (shaving, skin prep) that current AI systems, lacking robust general-purpose robotic manipulation, cannot perform.
Adoption barriersclaude-haiku-4-5-202510015/5This task occurs in a highly regulated, licensed medical environment where patient contact, aseptic technique, and procedural accountability are legally and institutionally mandated to a credentialed human. Regulatory and liability barriers are essentially absolute.
Adoption barriersclaude-sonnet-54/5Direct patient contact in a sterile surgical context involves significant liability, infection-control protocols, and typically requires trained/certified personnel, creating strong barriers to non-human substitution.
Cost vs. human wageclaude-haiku-4-5-202510011/5The capital cost of a surgical robot capable of reliable skin prep, plus integration, maintenance, and sterile protocols, far exceeds the loaded hourly wage of a surgical assistant for this brief, labor-light task. The economics do not yet favor automation.
Cost vs. human wageclaude-sonnet-51/5There is no AI system offering this service, so any hypothetical robotic solution would require expensive specialized hardware far exceeding the cost of a surgical assistant performing this simple manual task.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed commercial product performs autonomous pre-operative skin preparation (hair removal and disinfection) reliably in a surgical setting. Surgical robots in use today (da Vinci, etc.) require human supervision and are not tasked with these preparatory steps; this task remains entirely human-performed in production hospitals.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs patient hair removal or surgical site disinfection; this remains firmly in the domain of human clinical staff with no robotic analog in production.

Pass instruments or supplies to surgeon during procedure.

6

CI 0–13 · exposure 8 · augmentation 25 · importance 4.4/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Adoption of full automation in instrument passing is negligible; surgical robotics focus on specific procedural steps (suturing, dissection) under surgeon control rather than autonomous instrument passing. Most ORs still rely on human surgical assistants, reflecting slow and limited real-world displacement.
Sector adoption velocityclaude-sonnet-51/5Healthcare, especially hands-on surgical support roles, is a slow-adopting physical-task sector with minimal AI/robotic penetration into intraoperative instrument handling.
Augmentation potentialclaude-haiku-4-5-202510013/5AI-assisted instrument tracking systems and heads-up displays can help surgeons anticipate and organize instrument sequences, moderately improving efficiency. However, current systems provide limited augmentation compared to the experience of a trained surgical assistant who can predict needs contextually.
Augmentation potentialclaude-sonnet-51/5Current AI offers essentially no meaningful real-time assistance for the physical act of passing instruments during surgery.
Task automatabilityclaude-haiku-4-5-202510012/5While robotic arms can hold instruments in controlled settings, real-time passing of instruments during dynamic surgery requires continuous spatial awareness, prediction of surgeon intent, and adaptive response to unpredictable procedural changes—capabilities current AI systems lack reliably. No current system achieves 50% time savings at equal quality end-to-end.
Task automatabilityclaude-sonnet-51/5This requires real-time physical manipulation, sterile technique, and split-second responsiveness in a dynamic surgical field that current AI/robotic systems cannot perform end-to-end.There is no off-the-shelf system that reliably automates this physical task with time savings at equal quality.
Adoption barriersclaude-haiku-4-5-202510015/5Surgical procedures are heavily regulated; a licensed surgeon or credentialed OR staff member typically bears legal and liability responsibility for instrument management. Regulatory frameworks require human accountability in the OR, and error costs (patient injury, infection) create strong liability asymmetry against automation.
Adoption barriersclaude-sonnet-55/5Sterile field protocols, patient safety liability, and hospital credentialing requirements mean only trained, often licensed personnel can perform this task, creating hard regulatory and liability barriers.
Cost vs. human wageclaude-haiku-4-5-202510012/5Current surgical robotics systems (e.g., da Vinci) are extremely expensive to acquire, maintain, and integrate, with inference and oversight costs far exceeding the loaded wage of a surgical assistant. Capital and operational barriers make the cost ratio unfavorable.
Cost vs. human wageclaude-sonnet-51/5No viable AI/robotic solution exists for this task, so any hypothetical system would require extensive specialized hardware and safety validation costing far more than a human surgical assistant.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs this task in live surgical procedures. Research prototypes and simulation-based demonstrations exist, but production surgical systems do not independently pass instruments with the precision, speed, and safety required in operating rooms.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously passes instruments to surgeons during live procedures; surgical robots like da Vinci are teleoperated by the surgeon, not autonomous assistants performing this function.

Monitor and maintain aseptic technique throughout procedures.

3

CI 0–5 · exposure 5 · augmentation 38 · importance 4.9/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare, especially OR environments, adopts new automation cautiously; regulatory approval for autonomous monitoring of asepsis is virtually nonexistent, and the high-consequence nature of surgical safety creates structural resistance to replacing human oversight.
Sector adoption velocityclaude-sonnet-51/5Operating room sterile technique enforcement remains almost entirely manual and physically embedded; healthcare surgical support roles show minimal AI displacement to date.
Augmentation potentialclaude-haiku-4-5-202510013/5AI-assisted monitoring (e.g., alerts flagging potential breaches for human review) could assist surgical staff in maintaining awareness, but the task itself requires human judgment and authorization, limiting transformative upside.
Augmentation potentialclaude-sonnet-52/5Some sensor or camera-based monitoring systems could flag potential contamination events, offering minor situational awareness support, but they do not substantially transform the task today.
Task automatabilityclaude-haiku-4-5-202510011/5Monitoring aseptic technique requires real-time visual assessment of sterile field integrity, detecting breaches in technique, and making judgment calls in dynamic surgical environments. Current AI vision systems cannot reliably substitute for trained human observation in this high-stakes, safety-critical context.
Task automatabilityclaude-sonnet-51/5Maintaining sterile field integrity requires continuous physical presence, tactile judgment, and real-time correction of human and equipment breaches during surgery, which current AI cannot perform end-to-end.
Adoption barriersclaude-haiku-4-5-202510015/5Surgical protocols mandate that a licensed, qualified human (surgeon or surgical technologist) must maintain and verify aseptic technique; this is not delegable by law or regulation, and liability asymmetry is extreme—AI failure introduces infection risk that hospitals cannot absorb.
Adoption barriersclaude-sonnet-55/5Surgical team roles are tightly regulated, require licensed/certified personnel, and carry high liability for infection control failures, making human performance legally and clinically mandatory.
Cost vs. human wageclaude-haiku-4-5-202510011/5The infrastructure required (surgical-grade cameras, real-time processing, integration with OR systems) combined with oversight costs exceeds the wage of a surgical assistant, and the liability risk of AI failure makes human monitoring economically necessary.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this function, so cost comparison favors the human by default; any sensor-based monitoring aids would add cost without replacing the role.
Technical feasibility todayclaude-haiku-4-5-202510012/5While computer vision can detect some gross violations (e.g., ungloved touch), deployed surgical AI systems do not reliably monitor continuous aseptic compliance across the full sterile field. Pilot systems exist but lack the precision and comprehensive coverage needed for production deployment.
Technical feasibility todayclaude-sonnet-51/5No deployed product monitors and enforces aseptic technique in live surgical settings; this remains a physically embodied, judgment-intensive human task.

Obtain or inspect sterile or non-sterile surgical equipment, instruments, or supplies.

3

CI 0–5 · exposure 0 · augmentation 25 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare remains highly conservative in automation, with low current deployment of autonomous systems in ORs. Equipment handling remains almost entirely human-performed; even large academic medical centers have not adopted autonomous surgical supply management.
Sector adoption velocityclaude-sonnet-51/5Healthcare physical task execution in operating rooms sees minimal AI/robotic adoption for this specific function; surgical automation focuses on surgeon-assist robotics, not instrument handling by assistants.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could potentially assist by tracking inventory locations or flagging supply expiration dates, but the physical inspection and retrieval work offers limited augmentation value since the human assistant must ultimately verify and handle supplies before use.
Augmentation potentialclaude-sonnet-52/5AI-driven inventory tracking or RFID-based systems can help flag missing or non-sterile items, offering marginal assistance, but the core physical inspection and handling remains manual.
Task automatabilityclaude-haiku-4-5-202510011/5The task requires physical handling, visual inspection for sterility and damage, environmental movement in operating rooms, and real-time quality judgment—capabilities current AI systems lack entirely. No deployed system can autonomously retrieve, carry, and inspect surgical supplies in a complex OR environment.
Task automatabilityclaude-sonnet-51/5This requires physical manipulation, visual/tactile inspection, and retrieval of physical instruments in a sterile field, which current AI systems cannot perform end-to-end.'
Adoption barriersclaude-haiku-4-5-202510015/5Strict healthcare regulations, hospital protocols, sterility requirements, and legal liability for contamination create hard barriers. Hospital operating rooms mandate human responsibility for equipment integrity, and regulatory frameworks do not yet permit autonomous sterilization validation.
Adoption barriersclaude-sonnet-54/5Sterile technique, infection control regulations, and liability for surgical errors create strong barriers requiring trained, often certified personnel to handle instruments and verify sterility.
Cost vs. human wageclaude-haiku-4-5-202510011/5Current surgical equipment management requires either manual labor (cheap) or expensive custom robotics (tens of thousands to millions). The cost of autonomous sterilization-aware systems far exceeds the loaded wage of a surgical assistant.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute for this physical task, so any AI-based approach (e.g., robotics) would be far more costly than a human assistant given current technology maturity.
Technical feasibility todayclaude-haiku-4-5-202510011/5No commercial or research-stage product demonstrably performs independent surgical equipment acquisition and sterility inspection. The task combines embodied robotics, contamination awareness, and domain-specific judgment that remains in early research phases.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs physical sterile inventory inspection and retrieval in operating rooms today; this remains a manual task performed by trained staff.

Operate sterilizing devices.

3

CI 0–5 · exposure 0 · augmentation 25 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare remains a slow-adopting sector for robotic process automation; sterilizing devices are routine operational tasks performed by facilities staff with minimal digital transformation pressure.
Sector adoption velocityclaude-sonnet-51/5Healthcare support and sterile processing functions show very low AI/robotic adoption; this is a highly manual, physical task in a sector with slow automation uptake for such duties.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could provide monitoring alerts or log documentation, but the core task of physically operating equipment and ensuring sterilization validation requires direct human responsibility and offers limited augmentation potential.
Augmentation potentialclaude-sonnet-52/5AI could help with monitoring sterilization logs, alerting to cycle completion, or tracking compliance records, but it offers minimal assistance to the core physical operation of the devices.
Task automatabilityclaude-haiku-4-5-202510011/5Operating sterilizing devices is a hands-on mechanical task requiring real-time monitoring of equipment parameters, physical manipulation of instruments, and adjustment of settings based on load contents—capabilities current AI systems cannot reliably perform in a physical environment.
Task automatabilityclaude-sonnet-51/5Operating sterilizing devices (autoclaves, etc.) in a surgical setting requires physical manipulation of instruments, loading/unloading, and verification of sterility that current AI systems cannot perform end-to-end without robotics far beyond deployed capability.
Adoption barriersclaude-haiku-4-5-202510015/5Medical device regulations (FDA 21 CFR Part 820, ISO 11135) mandate documented operator oversight, validation, and accountability for sterilization efficacy; human accountability cannot be fully transferred to autonomous AI.
Adoption barriersclaude-sonnet-54/5Sterilization protocols in surgical settings are governed by strict infection-control regulations and institutional policies requiring trained/certified personnel to verify and operate equipment, creating substantial procedural and liability barriers.
Cost vs. human wageclaude-haiku-4-5-202510011/5An automated sterilization system would require specialized hardware (robotic arms, sensors, monitoring systems) with integration and maintenance costs far exceeding the loaded wage of a surgical assistant performing this task.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical task, so any AI-based alternative (e.g., robotic automation) would require costly specialized hardware exceeding current human labor costs.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI product autonomously operates surgical sterilizers; the task requires physical actuation, environmental sensing, and responsibility for preventing contamination in a regulated clinical setting where error has high consequences.
Technical feasibility todayclaude-sonnet-51/5No deployed AI product autonomously operates sterilization equipment in clinical settings; this remains a manual, physically-executed task performed by trained staff.

Assist in applying casts, splints, braces, or similar devices.

3

CI 0–5 · exposure 0 · augmentation 25 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare remains a laggard sector for autonomy in procedural tasks. No measurable deployment of AI or robotics for cast/splint application exists in production healthcare settings, and adoption velocity remains near-zero due to regulatory, liability, and skill specificity.
Sector adoption velocityclaude-sonnet-51/5Healthcare's physical/manual procedural tasks show minimal AI adoption; this sub-task within surgical assisting has no meaningful automation trend.
Augmentation potentialclaude-haiku-4-5-202510012/5Current AI offers minimal augmentation for this task. Some vision systems could potentially assist in documentation or measurement, but the core manual skill of application—positioning, pressure, material handling—sees negligible productivity gains from existing AI tools.
Augmentation potentialclaude-sonnet-52/5AI could offer minor support like generating instructions or documentation, but it offers essentially no assistance during the actual physical application process.
Task automatabilityclaude-haiku-4-5-202510011/5Applying casts, splints, and braces requires precise three-dimensional manual manipulation, direct patient contact, real-time adjustment based on tactile feedback, and anatomical judgment that current AI systems cannot perform end-to-end. No automation solution exists that can physically manipulate materials and limbs to achieve proper fit and immobilization.
Task automatabilityclaude-sonnet-51/5This is a hands-on physical task requiring manual dexterity, tactile feedback, and adjustment to a patient's body; no current AI system can physically apply casts or splints.
Adoption barriersclaude-haiku-4-5-202510015/5This task has hard legal and regulatory barriers: only licensed medical professionals (surgeons, physician assistants, certified surgical technologists) are authorized to apply immobilization devices in clinical settings, and patient safety and liability create strict requirements for human accountability and judgment.
Adoption barriersclaude-sonnet-54/5Direct patient contact, physical safety concerns, and clinical protocols requiring trained personnel to properly immobilize injuries create strong practical and liability barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5The hardware, integration, and safety validation required for robotic casting would cost substantially more than a surgical assistant's hourly wage, and liability and oversight costs would be prohibitive given the clinical stakes.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute, so any AI-based approach would require expensive robotics development that does not exist, making AI far more costly or simply infeasible.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product performs this task autonomously. While robotic arms exist in research, none are clinically validated or deployed for cast/splint application in real surgical or clinical settings. The task remains entirely dependent on skilled human personnel.
Technical feasibility todayclaude-sonnet-51/5No deployed robotic or AI product performs cast/splint/brace application in clinical settings; this remains purely manual work.

Transport patients to operating room.

3

CI 0–5 · exposure 0 · augmentation 13 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare adoption of physical automation remains minimal; this task occurs in highly regulated, human-intensive clinical settings where organizational and safety friction heavily constrains AI adoption.
Sector adoption velocityclaude-sonnet-51/5Healthcare physical logistics tasks show very low AI/robotic adoption due to safety-critical nature and lack of mature autonomous transport robots in most hospitals.
Augmentation potentialclaude-haiku-4-5-202510012/5AI offers minimal assistance for this task; perhaps digital route optimization or patient tracking systems provide marginal support, but the core work—physical transport and direct patient care—cannot be meaningfully augmented by current AI systems.
Augmentation potentialclaude-sonnet-51/5AI offers minimal assistance to the physical act of transporting a patient, though scheduling or routing software could marginally help coordinate movement logistics.
Task automatabilityclaude-haiku-4-5-202510011/5Transporting patients to an operating room requires physical movement in a healthcare environment with medical equipment, patient safety monitoring, and careful handling of potentially compromised individuals. Current AI has no capability to physically move patients or navigate complex hospital spaces with the required safety standards.
Task automatabilityclaude-sonnet-51/5Physically transporting a patient on a gurney or bed requires physical manipulation, safety monitoring, and navigation that current AI systems cannot perform without robotic embodiment, which is not standard practice.
Adoption barriersclaude-haiku-4-5-202510015/5Patient transport in a surgical context carries strict liability, safety, and regulatory requirements; a human must legally remain responsible for patient welfare during transport, creating a hard barrier to full automation.
Adoption barriersclaude-sonnet-54/5Patient safety, liability, and the need for trained personnel to monitor vitals and handle emergencies during transport create strong practical and regulatory barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Autonomous systems capable of safe patient transport would require significant hardware investment (robots, sensors, integration), making the cost far higher than the loaded wage of a surgical assistant for the foreseeable future.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI-based substitute for this physical task, so AI is not cheaper since it does not functionally exist as an alternative here.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI systems can reliably perform end-to-end patient transport; this task fundamentally requires physical embodiment, real-time navigation, and direct patient care that existing robots cannot accomplish in healthcare settings.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously transports surgical patients in hospitals today; this remains a manual task performed by staff.

Clamp, ligate, or cauterize blood vessels to control bleeding during surgical entry, using hemostatic clamps, suture ligatures, or electrocautery equipment.

1

CI 0–3 · exposure 0 · augmentation 38 · importance 4.6/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5While some surgical centers use robotic-assisted platforms (da Vinci), autonomous hemostasis control remains limited and supervisory rather than autonomous. Adoption is concentrated in well-funded hospitals and has not displaced surgical assistants; most ORs rely on traditional manual hemostasis.
Sector adoption velocityclaude-sonnet-51/5Surgical assisting is a highly physical, low-digitization task; adoption of autonomous AI for direct tissue intervention is essentially nonexistent in current practice.
Augmentation potentialclaude-haiku-4-5-202510013/5Robotic surgical systems can assist surgeons by providing enhanced visualization and tremor reduction, and newer systems offer some automated tool control. However, the assistant still directs hemostasis decisions; AI provides useful augmentation of precision and steadiness rather than full task transformation.
Augmentation potentialclaude-sonnet-52/5Surgical robots and imaging/guidance tools can assist visualization or instrument stability, but they offer only marginal augmentation for the specific act of clamping/cauterizing vessels, which remains manually judgment-driven.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires real-time, precise physical manipulation in a dynamic surgical environment with immediate consequences for patient safety. Current AI systems cannot perform or control the physical actions of clamping, ligating, or cauterizing blood vessels; the task demands embodied surgical skill and cannot be meaningfully automated end-to-end today.
Task automatabilityclaude-sonnet-51/5This is a hands-on, real-time physical procedure requiring tactile judgment and fine motor control inside a live surgical field; no AI system today can perform hemostasis independently.
Adoption barriersclaude-haiku-4-5-202510015/5This task is protected by strict medical licensing requirements, surgical credentialing, liability standards, and regulatory oversight (FDA clearance for surgical devices). Only licensed medical professionals can legally perform or direct hemostasis; no automation can bypass these hard legal and safety barriers.
Adoption barriersclaude-sonnet-55/5Direct intraoperative tissue manipulation is a licensed clinical act requiring credentialed personnel, with severe liability exposure and strict regulatory/institutional controls preventing autonomous automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Surgical robotic systems and automation infrastructure are extremely expensive to acquire, maintain, and integrate into OR workflows, with high per-procedure costs. This far exceeds the loaded wage of a surgical assistant for the equivalent output.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this task, so cost comparison favors the human by default; any hypothetical robotic system would carry far higher capital, safety, and oversight costs.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs hemostasis procedures autonomously in live surgery. While computer vision can identify bleeding and robotic systems exist in operating rooms, they require continuous human control and decision-making; autonomous hemostasis is not a production reality.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs autonomous intraoperative bleeding control; robotic surgical systems remain surgeon-teleoperated tools, not autonomous actors for this task.

Cover patients with surgical drapes to create and maintain a sterile operative field.

0

CI 0–0 · exposure 0 · augmentation 0 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare remains a laggard sector for task automation due to high regulatory friction, liability risk, and the deeply human nature of surgical practice; sterile field management is not a target for AI displacement in current adoption patterns.
Sector adoption velocityclaude-sonnet-51/5Surgical support tasks involving direct physical patient contact show minimal AI/robotic adoption; this is a highly manual, low-digitization task.
Augmentation potentialclaude-haiku-4-5-202510011/5AI cannot meaningfully assist a human in the act of placing and securing sterile drapes, as the task is primarily physical manipulation requiring hands-on control and real-time adjustment for proper sterile coverage.
Augmentation potentialclaude-sonnet-51/5AI offers no meaningful assistance for the physical act of draping a patient, though unrelated AI tools may support other surgical workflow aspects.
Task automatabilityclaude-haiku-4-5-202510011/5Covering patients with surgical drapes requires physical manipulation of fabric in a three-dimensional, time-sensitive environment with strict sterility requirements. Current AI systems lack the embodied robotics, dexterity, and real-time environmental perception needed to perform this task end-to-end in an operating room.
Task automatabilityclaude-sonnet-51/5Draping requires precise physical manipulation of sterile materials on a patient's body in a dynamic sterile field, which current AI systems cannot perform end-to-end.'
Adoption barriersclaude-haiku-4-5-202510015/5Maintaining surgical sterility is a legal and regulatory requirement; a licensed human (surgeon or certified surgical technician) must directly perform or supervise draping to ensure infection control standards and legal accountability for patient safety.
Adoption barriersclaude-sonnet-55/5Sterile field maintenance is a licensed, safety-critical clinical procedure with strict infection-control regulations requiring trained personnel and accountability.
Cost vs. human wageclaude-haiku-4-5-202510011/5The capital cost of surgical robots (millions of dollars) plus integration, maintenance, and surgeon retraining far exceeds the loaded wage of a surgical assistant for this specific task, especially given the narrow applicability.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute, so any AI-based approach would require costly robotics development far exceeding current human labor costs.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI product reliably performs sterile draping in surgical settings. While research exists on surgical robotics, they are highly specialized, require extensive surgeon training, and are not deployed for routine draping tasks at scale.
Technical feasibility todayclaude-sonnet-51/5No deployed robotic or AI product performs patient draping in operating rooms today; this remains firmly a manual clinical task.

Coordinate or participate in the positioning of patients, using body stabilizing equipment or protective padding to provide appropriate exposure for the procedure or to protect against nerve damage or circulation impairment.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Surgical environments operate under strict regulatory oversight and risk-averse protocols. Physical robot adoption in surgery remains experimental; no meaningful production displacement of patient positioning has occurred in mainstream surgical practice.
Sector adoption velocityclaude-sonnet-51/5Surgical/perioperative settings involving physical patient handling show minimal AI adoption for this specific hands-on function, as robotics and AI here remain confined to narrow, supervised applications.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could potentially assist with preoperative planning or guidance on positioning protocols via documentation review, but real-time augmentation of physical positioning itself is minimal given the embodied, safety-critical nature of the work.
Augmentation potentialclaude-sonnet-52/5Some robotic-assisted positioning tools or checklists/sensors could support decision-making about padding placement or pressure points, but core physical execution and judgment remain human-driven with limited AI augmentation currently.
Task automatabilityclaude-haiku-4-5-202510011/5Patient positioning requires physical manipulation in a sterile surgical environment and real-time adjustment based on tactile feedback and anatomical constraints. Current AI systems cannot perform embodied physical tasks of this complexity and precision in unstructured clinical settings.
Task automatabilityclaude-sonnet-51/5This is a hands-on physical task requiring manual manipulation of patient bodies, stabilizing equipment, and padding in real-time during surgery; no AI system can physically position patients or assess tactile feedback for nerve/circulation protection.
Adoption barriersclaude-haiku-4-5-202510015/5Patient positioning directly impacts surgical safety and liability; hospitals and surgeons bear legal and clinical responsibility. Regulatory bodies (FDA, state surgical boards) require qualified human practitioners present for patient care during procedures, creating hard barriers to full automation.
Adoption barriersclaude-sonnet-55/5Patient safety, licensure, and liability concerns mean only trained, credentialed surgical staff can perform this hands-on task; regulatory and clinical protocols mandate human execution and accountability.
Cost vs. human wageclaude-haiku-4-5-202510011/5The cost of deploying a robotic system with sufficient precision, safety certification, and integration into sterile surgical workflows would far exceed the labor cost of a surgical assistant performing this positioning task.
Cost vs. human wageclaude-sonnet-51/5There is no AI substitute performing this physical task, so AI cost is not comparable; the human labor cost is the only viable option today.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI system can independently position patients safely for surgery. This task demands physical interaction, real-time decision-making, and accountability for patient safety—areas where no production system operates autonomously in surgical contexts.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs physical patient positioning; this remains entirely a manual clinical task performed by trained personnel in the OR.

Maintain an unobstructed operative field, using surgical retractors, sponges, or suctioning and irrigating equipment.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Despite decades of surgical robotics development, autonomous field maintenance remains in research stages; adoption is limited to specialized centers and requires human operators, not displacement of assistants.
Sector adoption velocityclaude-sonnet-51/5Operating room physical tasks are among the least digitized and least automated aspects of healthcare, with robotic surgery still requiring human-driven control rather than autonomous field management.
Augmentation potentialclaude-haiku-4-5-202510012/5Current robotic systems can partially assist with retraction or visualization but require constant human direction and do not meaningfully augment the surgical assistant's productivity on this core task.
Augmentation potentialclaude-sonnet-52/5AI can assist with pre-op planning or robotic-assisted visualization, but it offers minimal real-time assistance in the physical act of maintaining the operative field during surgery.
Task automatabilityclaude-haiku-4-5-202510011/5Maintaining an unobstructed operative field requires real-time physical manipulation of retractors, sponges, and suction equipment in response to dynamic surgical conditions. Current AI systems cannot perform these precise, force-controlled physical actions in a sterile surgical environment.
Task automatabilityclaude-sonnet-51/5This requires real-time physical manipulation of tissue and instruments during live surgery, a manual dexterity and physical presence task no current AI system can perform.
Adoption barriersclaude-haiku-4-5-202510015/5Strict regulatory requirements (FDA approval for surgical devices), liability concerns around sterile field maintenance, and the need for licensed personnel oversight create hard barriers to automation in surgical settings.
Adoption barriersclaude-sonnet-55/5This is a sterile, hands-on surgical task typically requiring credentialed surgical staff with legal and clinical liability constraints, and direct physical presence in the operating field is mandatory.
Cost vs. human wageclaude-haiku-4-5-202510011/5Surgical robotics capable of field maintenance are extremely expensive to acquire, maintain, and integrate, vastly exceeding the cost of employing a surgical assistant for the same work.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical task, so cost comparison favors the human by default since no AI alternative exists to price against.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed products reliably perform live surgical field management today. While surgical robotics exist, they require continuous human control for these dynamic maintenance tasks rather than autonomous operation.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs physical intraoperative retraction, suctioning, or irrigation autonomously; surgical robots exist but require direct human control for these functions, not autonomous execution.

Prepare and apply sterile wound dressings.

0

CI 0–0 · exposure 0 · augmentation 13 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Operating rooms have adopted surgical robots only for specific high-precision tasks; routine sterile dressing application remains a human skill with no meaningful automation adoption in practice.
Sector adoption velocityclaude-sonnet-51/5Healthcare physical care tasks, especially sterile procedures, show minimal AI/robotic adoption; this remains a highly manual, low-digitization task.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could potentially assist with wound documentation or dressing-selection guidance, but the core manual task of aseptic application leaves limited scope for AI augmentation of the human assistant's work.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no meaningful assistance to the physical act of preparing and applying sterile dressings, though it may support documentation elsewhere.
Task automatabilityclaude-haiku-4-5-202510011/5Preparing and applying sterile wound dressings requires manual dexterity, real-time assessment of wound conditions, and precise physical manipulation in a sterile field—tasks that current robotics and AI cannot reliably perform end-to-end without human intervention.
Task automatabilityclaude-sonnet-51/5This requires physical manipulation of sterile materials on a patient's body in a clinical setting, which current AI systems cannot perform end-to-end; robotics for this specific fine-motor sterile task is not deployable today.
Adoption barriersclaude-haiku-4-5-202510015/5Sterile field protocols, infection-control regulations, and legal liability for wound care errors create strong regulatory and organizational barriers; a trained human must maintain responsibility for sterile technique.
Adoption barriersclaude-sonnet-55/5Sterile technique and direct patient contact in surgical settings require licensed, trained personnel, with significant liability and infection-control regulations preventing non-human performance.
Cost vs. human wageclaude-haiku-4-5-202510011/5The capital and maintenance costs of surgical robotics capable of dressing application, combined with the low hourly labor cost of surgical assistants, make automation economically unfavorable.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this physical task, so any hypothetical automation would require expensive specialized robotics far exceeding human labor cost currently.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed autonomous system today reliably performs sterile dressing application in production surgical settings; this remains a skilled manual task requiring human tactile feedback and judgment.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously prepares and applies sterile wound dressings in clinical practice; this remains a manual task performed by trained personnel.

Apply sutures, staples, clips, or other materials to close skin, facia, or subcutaneous wound layers.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare organizations have been slow to adopt even partially autonomous surgical technologies; adoption remains concentrated in large academic centers with significant capital investment, and surgical closure work remains firmly in human hands.
Sector adoption velocityclaude-sonnet-51/5Surgical hands-on tasks remain minimally automated; healthcare procedural work is a slow-adopting, highly regulated physical domain compared to information-based sectors.
Augmentation potentialclaude-haiku-4-5-202510012/5While computer vision systems could potentially assist with real-time wound measurement or tissue analysis, current AI provides minimal augmentation for the core manual task of applying sutures or clips, which depends on embodied skill and tactile judgment.
Augmentation potentialclaude-sonnet-52/5Robotic-assisted surgical platforms can provide steadier instrument control and visualization support during closure, but current AI contributes little beyond tool assistance already used for other robotic-surgery steps.
Task automatabilityclaude-haiku-4-5-202510011/5Suturing and wound closure require real-time haptic feedback, fine motor control in three-dimensional space, and contextual judgment about tissue viability that current AI systems cannot replicate. No end-to-end automation of this task exists or is feasible with deployed technology.
Task automatabilityclaude-sonnet-51/5This is a hands-on physical surgical procedure requiring fine motor skill, tactile feedback, and real-time judgment under sterile conditions; no off-the-shelf AI system can perform wound closure end-to-end today.
Adoption barriersclaude-haiku-4-5-202510015/5Wound closure is a core surgical task that requires a licensed healthcare provider (surgeon or surgical assistant) to perform or directly supervise under established medical practice standards and regulations. Liability, surgical licensing, and regulatory requirements create hard barriers to autonomous substitution.
Adoption barriersclaude-sonnet-55/5Wound closure is an invasive medical procedure legally requiring a licensed practitioner, with high liability for errors like infection or dehiscence, making autonomous substitution essentially prohibited.
Cost vs. human wageclaude-haiku-4-5-202510011/5Surgical assistants command significant labor costs, but the capital, maintenance, and oversight requirements for any hypothetical robotic system capable of wound closure would far exceed the cost of human surgical assistants per procedure.
Cost vs. human wageclaude-sonnet-51/5Autonomous suturing robots do not exist as deployable products, so there is no viable AI cost comparison; any robotic assistance still requires a fully paid surgeon operating it.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI system can independently perform wound closure with sutures, staples, or clips in a clinical setting. While surgical robotics assist human surgeons, they require continuous teleoperation or human oversight and cannot autonomously execute this task.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously closes surgical wounds; robotic surgery systems like da Vinci require full human control and are teleoperated, not autonomous, for this task.

Discuss with surgeon the nature of the surgical procedure, including operative consent, methods of operative exposure, diagnostic or laboratory data, or patient-advanced directives or other needs.

0

CI 0–0 · exposure 0 · augmentation 38 · importance 4.6/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare adoption of AI in clinical decision-making remains slow and heavily regulated, with active human oversight required. Pre-operative consultation is a high-stakes, human-contact-mandatory task in all surgical settings, with no evidence of AI displacement.
Sector adoption velocityclaude-sonnet-51/5Surgical care is a highly regulated, physically-grounded profession with minimal AI displacement of core clinical judgment and communication tasks to date.
Augmentation potentialclaude-haiku-4-5-202510012/5AI might assist by retrieving or summarizing patient records, previous labs, or advance directives before discussion, but the dialogue itself and clinical judgment remain wholly human. Marginal supportive value only; the surgeon and assistant must conduct the discussion.
Augmentation potentialclaude-sonnet-53/5AI can assist by summarizing patient records, flagging relevant lab data, or drafting consent documentation, but the core discussion and judgment remain human-led.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires real-time collaborative dialogue with a surgeon about patient-specific medical decisions, consent, and directives—judgment-heavy exchanges that demand deep understanding of context, ethics, and individual patient circumstances. Current AI cannot meaningfully participate in or replace this interactive clinical discussion.
Task automatabilityclaude-sonnet-51/5This requires real-time, in-person clinical dialogue involving judgment, physical presence, and interpersonal trust before surgery; no AI system can substitute for this interaction end-to-end.
Adoption barriersclaude-haiku-4-5-202510015/5Strong legal and regulatory barriers exist: only licensed surgical assistants or surgeons can participate in operative consent discussions and patient communication about surgical procedure and directives. Liability, malpractice, and informed-consent law require human accountability in these conversations.
Adoption barriersclaude-sonnet-55/5Obtaining consent, discussing advanced directives, and coordinating surgical approach are legally and ethically mandated to involve licensed medical professionals, with strict liability and regulatory requirements.
Cost vs. human wageclaude-haiku-4-5-202510011/5The task requires a licensed medical professional (surgical assistant) to be present during pre-operative discussion; AI cannot substitute for this legal and clinical requirement, making the cost ratio unfavorable even if some data retrieval were automated.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI alternative performing this task, so no meaningful cost comparison exists; the human surgical assistant is required regardless of cost.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs surgeon-assistant consultation dialogue in production surgical settings. While AI can retrieve or summarize medical data, the actual discussion—negotiating approach, interpreting patient wishes, and adapting to surgeon expertise—remains entirely human-dependent.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs pre-surgical consultations with surgeons and patients in this collaborative, clinical decision-making capacity; this remains squarely human territory.

Assess skin integrity or other body conditions upon completion of the procedure to determine if damage has occurred from body positioning.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare adoption of AI-driven automation in surgical decision-making remains low; operating rooms are risk-averse environments with strong preference for human clinical oversight, and there is no evidence of meaningful production adoption of AI for post-operative tissue assessment.
Sector adoption velocityclaude-sonnet-51/5Surgical/perioperative care is a highly regulated, physically-mediated healthcare setting with low AI adoption for hands-on patient assessment tasks.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could potentially assist by flagging high-risk positioning areas or providing visual documentation, but augmentation is minimal because the task fundamentally depends on expert clinical examination, tactile assessment, and immediate judgment that AI cannot substantially enhance in the current surgical workflow.
Augmentation potentialclaude-sonnet-52/5AI could potentially assist with documentation or flagging risk factors based on positioning data, but it offers minimal help with the core physical inspection itself.
Task automatabilityclaude-haiku-4-5-202510011/5Assessing skin integrity and detecting subtle damage from positioning requires real-time visual inspection, tactile feedback, and clinical judgment that current AI cannot reliably perform end-to-end in an operating room context. No automated system can replicate the nuanced manual examination and immediate decision-making needed to identify pressure injuries or positioning-related trauma.
Task automatabilityclaude-sonnet-51/5This requires direct physical examination, palpation, and visual inspection of a patient's skin and tissue in a clinical setting, which current AI cannot perform end-to-end without embodiment.
Adoption barriersclaude-haiku-4-5-202510015/5This task has the highest barriers to automation: it requires a licensed clinical professional (surgical assistant or nurse) to perform and document findings; liability and error-cost asymmetry are extreme (missed pressure injuries lead to patient harm and malpractice); and regulatory standards and hospital credentialing mandate human clinical judgment and accountability.
Adoption barriersclaude-sonnet-55/5This is a clinical safety-critical task typically requiring a licensed/trained surgical team member to physically inspect and document patient condition, with direct liability implications.
Cost vs. human wageclaude-haiku-4-5-202510011/5The cost of developing, validating, and deploying a system for intraoperative skin assessment would far exceed the loaded wage of a surgical assistant performing this task, especially given regulatory and liability requirements in healthcare.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical assessment, so cost comparison favors the human by default since AI cannot deliver the output at all.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs this clinical assessment task in surgical settings. While image recognition exists for some skin conditions, it lacks the contextual understanding, real-time responsiveness, and clinical validation needed for post-operative positioning injury assessment in production surgical environments.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs hands-on post-operative physical assessment of skin integrity or positioning-related injury; this remains a physical, in-person clinical task.

Assist with patient resuscitation during cardiac arrest or other life-threatening events.

0

CI 0–0 · exposure 0 · augmentation 38 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5No meaningful adoption of AI automation for resuscitation tasks exists in practice. The critical nature of the task, legal restrictions, and need for human presence mean adoption velocity remains near zero.
Sector adoption velocityclaude-sonnet-51/5Acute care physical intervention tasks in surgical/emergency settings show minimal AI displacement; adoption is limited to diagnostic/monitoring support, not physical resuscitation actions.
Augmentation potentialclaude-haiku-4-5-202510012/5AI can offer modest assistance via real-time rhythm interpretation, protocol prompts, or data synthesis during resuscitation, but this augmentation is limited. The human clinician remains entirely in control and the task is not substantially easier with current AI tools compared to protocol-based practice.
Augmentation potentialclaude-sonnet-53/5AI-enabled monitors, alert systems, and decision-support tools (e.g., early warning scores, defibrillator guidance) can assist the team by flagging arrest onset or guiding protocol adherence, improving response speed and accuracy.
Task automatabilityclaude-haiku-4-5-202510011/5Patient resuscitation during cardiac arrest requires real-time physical interventions (chest compressions, defibrillation, medication administration, airway management) that current AI systems cannot perform. The task demands embodied action, rapid decision-making under extreme uncertainty, and continuous adaptation based on patient physiology—none of which are automatable by today's AI.
Task automatabilityclaude-sonnet-51/5This is a hands-on, time-critical physical intervention (chest compressions, airway management, coordinating with team) that requires physical presence and manual dexterity; current AI cannot perform physical resuscitation actions.
Adoption barriersclaude-haiku-4-5-202510015/5Resuscitation is legally and professionally restricted to licensed medical personnel (physicians, nurses, paramedics). Liability, regulatory oversight, and the requirement for immediate human judgment and physical presence create absolute barriers to automation or unsupervised AI deployment.
Adoption barriersclaude-sonnet-55/5Life-threatening emergency care requires licensed, hands-on medical personnel; legal, ethical, and safety requirements mandate human physical presence and accountability.
Cost vs. human wageclaude-haiku-4-5-202510011/5Current AI has zero capacity to replace the human cost of resuscitation labor. Any deployment would require human clinicians to perform the task anyway, making AI more expensive than human-only workflows.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute for the physical labor involved, so any comparison favors the human entirely; AI cannot replace the task output.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI product performs patient resuscitation independently. While AI may assist in rhythm analysis or protocol guidance, the core task of physically assisting resuscitation remains entirely dependent on human clinicians and medical staff.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs physical resuscitation assistance; AI decision-support tools exist for detecting arrest but not for executing physical intervention tasks.

Incise tissue layers in lower extremities to harvest veins.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Adoption of AI for intraoperative surgical tasks in core procedures remains minimal; hospitals deploy surgical robots primarily as surgeon-controlled tools, not autonomous agents. Published adoption data show no meaningful displacement of surgical assistants in vein harvesting roles.
Sector adoption velocityclaude-sonnet-51/5Surgical practice, especially manual harvesting tasks, remains a highly manual, slow-to-digitize field with minimal autonomous AI adoption in the operating room.
Augmentation potentialclaude-haiku-4-5-202510012/5Surgical visualization tools and planned incision guidance systems offer marginal assistance in vein identification pre-operatively, but the incision task itself relies on real-time tactile and visual judgment that current AI does not augment meaningfully during execution.
Augmentation potentialclaude-sonnet-52/5Surgical robotic platforms and imaging aids can enhance precision and visualization during vein harvesting, but current AI does not meaningfully transform this specific manual task's productivity.
Task automatabilityclaude-haiku-4-5-202510011/5This task involves precise surgical incision in a live patient, requiring real-time haptic feedback, visual acuity in a sterile field, and immediate adaptation to anatomical variation. Current AI systems cannot perform surgical tissue incision end-to-end; surgical robots exist but require continuous human control and do not meet autonomous automation thresholds.
Task automatabilityclaude-sonnet-51/5This is a hands-on invasive surgical procedure requiring fine motor control, real-time tissue judgment, and haptic feedback that no current AI system can perform end-to-end.
Adoption barriersclaude-haiku-4-5-202510015/5This task has substantial legal and regulatory barriers: surgeons and credentialed surgical assistants are legally responsible for all intraoperative steps, informed consent requires human judgment, and malpractice/liability is asymmetrically borne by the provider. Medical boards, hospital credentialing, and scope-of-practice regulations all enforce human oversight.
Adoption barriersclaude-sonnet-55/5Invasive surgery is tightly regulated, requires licensed surgical personnel, and carries severe liability and patient-safety implications, making autonomous AI substitution legally and ethically prohibited.
Cost vs. human wageclaude-haiku-4-5-202510011/5Surgical automation infrastructure (robots, sensors, integration) costs tens of millions per operating suite and requires extensive training and oversight, making the per-task cost far higher than the loaded wage of a surgical assistant performing this specialized intraoperative work.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI alternative to compare cost against; any robotic assistance still requires a full surgical team, making AI substitution more expensive, not cheaper, than a human performing this task.
Technical feasibility todayclaude-haiku-4-5-202510011/5While surgical robotics research is advanced, no deployed AI system independently performs tissue incision in vein harvesting. Existing robotic platforms like da Vinci require surgeon teleoperation and cannot autonomously assess tissue depth, vessel fragility, or adjacent structure damage—all critical in this procedure.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs autonomous vein harvesting surgery; surgical robots like da Vinci exist but require full human teleoperation, not autonomous incision decisions.

Assist in the insertion, positioning, or suturing of closed-wound drainage systems.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Surgical environments are highly regulated, conservative in adopting new technologies, and currently rely on human surgical teams. Even where surgical robots are deployed, they augment rather than replace human surgical assistants and require physician operation.
Sector adoption velocityclaude-sonnet-51/5Surgical settings involving physical manipulation adopt autonomous AI very slowly due to safety, regulatory, and liability constraints, unlike information-based professional tasks.
Augmentation potentialclaude-haiku-4-5-202510012/5Current AI offers minimal assistance to surgical assistants on this specific task. While surgical navigation and imaging AI exist, they do not materially assist in the real-time manual work of insertion, positioning, or suturing of drainage systems.
Augmentation potentialclaude-sonnet-52/5AI/robotic tools (e.g., surgical navigation, robotic arms) can provide some guidance or precision assistance in adjacent surgical tasks, but for this specific manual step there is minimal current augmentation.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires real-time physical manipulation in a sterile surgical field—inserting, positioning, and suturing drainage systems. Current AI cannot perform end-to-end physical tasks in operating rooms; it lacks embodied robotics, haptic feedback, and the ability to respond to dynamic intraoperative conditions.
Task automatabilityclaude-sonnet-51/5This is a hands-on physical surgical task requiring tactile feedback, sterile technique, and real-time judgment inside a surgical field; no current AI system can perform physical manipulation or suturing autonomously.
Adoption barriersclaude-haiku-4-5-202510015/5Strong legal and regulatory barriers exist: only licensed physicians or credentialed surgical staff can perform this task in most jurisdictions, and liability for wound complications falls on the surgeon. Patient safety and sterile field integrity requirements create hard constraints on substitution.
Adoption barriersclaude-sonnet-55/5This is an invasive clinical procedure requiring licensed personnel, sterile technique, and legal/medical liability accountability, making human performance a hard regulatory and safety requirement.
Cost vs. human wageclaude-haiku-4-5-202510011/5Surgical automation requires extremely expensive specialized hardware (robotic arms, sterilizable components, integration) and extensive setup, making the all-in cost per task vastly higher than a trained surgical assistant's loaded wage.
Cost vs. human wageclaude-sonnet-51/5There is no AI substitute performing this physical task, so cost comparison favors the human by default; any robotic assistance would require far higher capital and oversight costs than the assistant's wage.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs surgical drainage system insertion and suturing in production. While surgical robots exist (da Vinci), they require a human surgeon to operate them and are not autonomous AI systems that perform this task independently.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs physical insertion, positioning, or suturing of drainage systems; surgical robots exist but are teleoperated by surgeons, not autonomous, and none address this specific assistant task.

Assist members of surgical team with gowning or gloving.

0

CI 0–0 · exposure 0 · augmentation 0 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Surgical environments are highly regulated, conservative in automation adoption, and dependent on human clinical judgment and tactile skill. No measurable displacement or pilot programs for automating gowning/gloving exist in production ORs.
Sector adoption velocityclaude-sonnet-51/5Surgical support and physical OR tasks are among the least digitized/automated areas of healthcare, with no meaningful movement toward AI or robotic adoption for this specific task.
Augmentation potentialclaude-haiku-4-5-202510011/5AI cannot meaningfully assist a human surgical assistant in physically gowning or gloving; the task is hands-on, immediate, and requires direct tactile interaction with the surgeon's body and sterile materials.
Augmentation potentialclaude-sonnet-51/5AI offers no meaningful assistance for the physical act of gowning or gloving a surgical team member.
Task automatabilityclaude-haiku-4-5-202510011/5Gowning and gloving require precise physical manipulation in a sterile field, immediate tactile feedback, and real-time adjustment for fit and comfort. Current AI systems lack embodied manipulation, sterile-environment compliance, and the fine motor control needed to perform this hands-on task end-to-end.
Task automatabilityclaude-sonnet-51/5This is a physical, hands-on task requiring precise sterile-field manipulation in a live surgical setting; current AI systems (including robotics) cannot perform this end-to-end task reliably.
Adoption barriersclaude-haiku-4-5-202510015/5This task is embedded in surgical team protocols and sterile field management governed by hospital infection control, surgical standards, and licensing requirements for OR staff. Legal and regulatory frameworks mandate trained personnel manage sterile gowning to prevent contamination and patient harm.
Adoption barriersclaude-sonnet-55/5Sterile technique and OR safety protocols require trained, credentialed personnel to perform this task, with strict liability and infection-control regulations preventing automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Surgical assistants perform this as part of their clinical duties; automated systems would require specialized hardware, sterile-protocol integration, and ongoing maintenance that would exceed the cost of human assistance in the OR.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI or robotic substitute, so any AI cost comparison is moot; the human remains the only cost-effective option.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed robotic or AI system reliably performs surgical gowning or gloving in production operating rooms today. The task demands sterile technique, human-specific fit adjustment, and real-time problem-solving that existing automation has not demonstrated at clinical scale.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs sterile gowning/gloving assistance in operating rooms today; this remains far outside current robotic or AI product capabilities.

Coordinate with anesthesia personnel to maintain patient temperature.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare automation lags digital-native sectors, and surgical coordination in particular remains heavily protected by professional licensure and conservative organizational practices. No measurable displacement of surgical assistants' coordination duties is occurring.
Sector adoption velocityclaude-sonnet-51/5Surgical support roles are among the least digitized/automated in healthcare, with physical presence and licensure requirements slowing any AI adoption.
Augmentation potentialclaude-haiku-4-5-202510012/5AI might assist by providing temperature monitoring alerts or summarizing anesthesia records, but the coordination task itself—communicating with personnel and deciding when to adjust—must remain with the surgical assistant. Limited augmentation potential beyond passive monitoring.
Augmentation potentialclaude-sonnet-52/5Smart monitoring systems and alerts can inform temperature-related decisions, offering minor assistance, but the coordination and physical response remain human-driven.
Task automatabilityclaude-haiku-4-5-202510011/5Coordinating with anesthesia personnel requires real-time communication, judgment about patient physiology, and human-to-human collaboration that current AI systems cannot perform autonomously. This task fundamentally depends on two-way dialogue and decision-making between humans in a safety-critical operating room environment.
Task automatabilityclaude-sonnet-51/5This requires real-time physical coordination, monitoring of a live patient, and verbal communication in a sterile operating environment, none of which current AI can perform end-to-end.
Adoption barriersclaude-haiku-4-5-202510015/5Surgical assistants must be licensed healthcare professionals, and maintaining patient temperature during surgery is a regulated clinical responsibility that legally requires qualified human personnel to perform and be accountable. Liability and regulatory frameworks explicitly require human oversight.
Adoption barriersclaude-sonnet-55/5Operating room roles require licensed, credentialed personnel physically present for patient safety and legal liability reasons, making this a hard-barrier task.
Cost vs. human wageclaude-haiku-4-5-202510011/5The task is primarily coordination and communication, which would require AI agents capable of reliable, real-time clinical interaction—orders of magnitude more expensive than the wage of a surgical assistant, if available at all.
Cost vs. human wageclaude-sonnet-51/5There is no AI substitute performing this coordination function, so no meaningful cost comparison exists; human presence is mandatory and cheap alternatives don't apply.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI product reliably performs inter-personnel coordination during surgery. Current systems cannot participate in real-time operating room communication or take independent action to maintain patient temperature without explicit human direction.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs this intraoperative coordination role; temperature management devices exist but the coordination task itself is not automated by any product.

Postoperatively inject a subcutaneous local anesthetic agent to reduce pain.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Surgical settings remain highly cautious about automation of direct patient contact tasks; adoption of surgical assistance robots is extremely slow and limited to specialized high-volume centers, with no production-scale deployment for routine postoperative anesthetic injection.
Sector adoption velocityclaude-sonnet-51/5Surgical and perioperative care is a highly regulated, low-digitization physical-task sector with minimal AI-driven automation of hands-on procedures.
Augmentation potentialclaude-haiku-4-5-202510012/5AI offers minimal augmentation for this task; while computer vision might assist in anatomical landmark identification, the core skill—precise, sterile, patient-responsive injection—relies on human sensorimotor control and clinical judgment that AI cannot meaningfully enhance in the loop.
Augmentation potentialclaude-sonnet-52/5AI can support documentation, dosage calculation checks, or protocol reminders, but offers negligible direct assistance to the physical act of injection itself.
Task automatabilityclaude-haiku-4-5-202510011/5Postoperative injection of local anesthetic requires real-time assessment of surgical site, patient anatomy, and pain localization—tasks demanding tactile feedback, spatial reasoning under uncertainty, and immediate clinical judgment that current AI cannot perform end-to-end without a human operator physically controlling the injection.
Task automatabilityclaude-sonnet-51/5This is a hands-on invasive medical procedure requiring physical dexterity, sterile technique, and real-time patient assessment that current AI cannot physically perform.'
Adoption barriersclaude-haiku-4-5-202510015/5Injection of medications into patients is a licensed clinical procedure; only credentialed healthcare professionals (nurses, surgeons, surgical assistants) may legally administer anesthetics, creating hard legal and regulatory barriers to automation.
Adoption barriersclaude-sonnet-55/5Administering anesthetic injections is a licensed clinical act with strict legal, liability, and scope-of-practice requirements mandating a credentialed human provider.
Cost vs. human wageclaude-haiku-4-5-202510011/5The labor cost of a surgical assistant performing this task (~$25–40/hour) is far lower than the cost of specialized surgical robotics, integration, training, and oversight required to approach autonomous injection capability.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical task, so cost comparison favors the human entirely.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI system today can independently perform subcutaneous injections; this requires robotic surgical systems with advanced haptic feedback and real-time sterile field management, which exist only in narrow research and experimental contexts, not in production surgical settings for this specific task.
Technical feasibility todayclaude-sonnet-51/5No deployed AI product administers subcutaneous injections; robotic surgical systems require full human control and are not used autonomously for this task.

Insert or remove urinary bladder catheters.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare remains a laggard sector for physical automation due to regulatory oversight, liability concerns, and the heterogeneity of patient anatomy; no meaningful displacement of catheterization tasks by automation is occurring.
Sector adoption velocityclaude-sonnet-51/5Healthcare direct-care physical procedures are among the slowest domains for AI/robotic adoption due to safety, regulation, and lack of mature autonomous hardware solutions.
Augmentation potentialclaude-haiku-4-5-202510012/5While imaging guidance systems can assist in difficult catheterizations, AI offers minimal augmentation for routine catheter insertion and removal, which are already well-standardized manual procedures requiring minimal cognition.
Augmentation potentialclaude-sonnet-52/5AI may help with training simulations, checklists, or documentation around the procedure, but offers minimal direct assistance during the physical act of catheter insertion/removal itself.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires direct physical manipulation of sterile catheters and precise anatomical placement into the urinary bladder, a procedure that demands real-time adaptation to patient physiology and cannot be performed remotely or without physical presence.
Task automatabilityclaude-sonnet-51/5This is a hands-on invasive physical procedure requiring manual dexterity, sterile technique, and tactile feedback that current AI systems (software or robotics) cannot perform end-to-end.atur No off-the-shelf system can insert/remove a catheter autonomously.'
Adoption barriersclaude-haiku-4-5-202510015/5Regulatory requirements mandate that only licensed clinical personnel (nurses, physicians, or surgical technicians under supervision) may perform catheterization due to infection control, liability, and patient safety standards that constitute hard legal barriers.
Adoption barriersclaude-sonnet-55/5Invasive patient contact procedures require licensed clinical personnel, sterile protocol adherence, and direct liability for patient harm, creating hard legal and safety barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Any hypothetical robotic system capable of this task would require significant infrastructure, maintenance, and oversight costs that would vastly exceed the labor cost of a trained surgical assistant performing it directly.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical task, so any AI cost comparison is moot; human labor remains the only functional option.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI or robotic system currently performs independent catheterization in clinical practice; this remains a task requiring trained human surgical assistants or nurses despite robotics research.
Technical feasibility todayclaude-sonnet-51/5No deployed commercial product performs catheterization autonomously in clinical practice; this remains firmly a manual nursing/surgical task.

Assist in volume replacement or autotransfusion techniques.

0

CI 0–0 · exposure 0 · augmentation 25 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare, particularly operative surgical care, remains a laggard sector for AI-driven task displacement. Surgical protocols are highly regulated and conservative; adoption of AI in direct surgical roles is minimal and experimental at best.
Sector adoption velocityclaude-sonnet-51/5Surgical assistance involving physical intraoperative procedures remains one of the least digitized, most human-dependent domains with minimal AI displacement to date.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could theoretically provide monitoring alerts or procedural checklists during surgery, but even assistive applications would face regulatory and integration barriers in the sterile operating room environment. Current systems offer minimal augmentation value for this specific task.
Augmentation potentialclaude-sonnet-52/5AI can support monitoring devices, blood management software, or predictive analytics for transfusion needs, but offers minimal direct assistance to the physical, hands-on task itself.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires real-time surgical decision-making, sterile field manipulation, and direct patient monitoring during a critical procedure. Current AI systems cannot perform or assist meaningfully with the hands-on procedural aspects that define volume replacement and autotransfusion techniques.
Task automatabilityclaude-sonnet-51/5This requires hands-on physical manipulation of blood volume replacement equipment during live surgery, a task no current AI system can perform end-to-end given the physical dexterity and real-time clinical judgment required.
Adoption barriersclaude-haiku-4-5-202510015/5Surgical assistance is legally and professionally bound to licensed surgical teams; only credentialed surgeons and surgical assistants may directly participate in autotransfusion and volume management. Regulatory and liability frameworks mandate human oversight and decision authority.
Adoption barriersclaude-sonnet-55/5This is a licensed clinical task performed in a sterile surgical environment with direct patient safety implications, requiring certified human personnel and legal/regulatory oversight.
Cost vs. human wageclaude-haiku-4-5-202510011/5AI has no meaningful economic footprint in this task space today, making a cost comparison premature. Surgical assistance requires credentialed human labor that cannot be substituted by current systems at any price point.
Cost vs. human wageclaude-sonnet-51/5There is no AI substitute performing this physical task, so any comparison favors the human; robotic surgical assistance for this specific function is not commercially deployed.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI product performs intraoperative surgical assistance for volume replacement or autotransfusion. This remains entirely within the domain of trained surgical personnel working under direct supervision in the operating room.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs the physical act of assisting autotransfusion; this is a manual, sterile-field clinical task requiring a physically present trained human.

Related occupations — Healthcare Practitioners & Technical

How to read this

A high substitution score does not mean this job disappears — it means a large share of its current tasks face replacement pressure, so the mix of tasks is likely to change. High augmentation alongside substitution typically means the occupation reorganizes around the protected tasks. Wide confidence intervals mean the rater panel disagreed: treat those scores as open questions, not verdicts.

What would change this score

New model capabilities (automatability, feasibility), falling inference costs (cost ratio), regulation and licensing shifts (barriers), and measured sector adoption (velocity) all re-enter at every index release. Each release is recomputed, versioned and kept queryable — scores are claims with a date on them, not permanent labels.