Surgical Technologists
29-2055.00Median wage $64,650/yr117,460 employed (US)Rank #871 of 923 scored · top 94% by substitution
Assist in operations, under the supervision of surgeons, registered nurses, or other surgical personnel. May help set up operating room, prepare and transport patients for surgery, adjust lights and equipment, pass instruments and other supplies to surgeons and surgeons' assistants, hold retractors, cut sutures, and help count sponges, needles, supplies, and instruments.
Sub-scores
0–100 · band = confidence interval from rater disagreement
Substitution11
Exposure11
Augmentation31
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
16 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%11
panel mean rating 1.4/5 → substitution pressure 11/100
Technical feasibility todayw 20%10
panel mean rating 1.4/5 → substitution pressure 10/100
Cost vs. human wagew 15%11
panel mean rating 1.4/5 → substitution pressure 11/100
Adoption barriersw 20%inverted — strong barriers lower the score12
panel mean rating 4.5/5 (barrier strength) → substitution pressure 12/100
Sector adoption velocityw 10%7
panel mean rating 1.3/5 → substitution pressure 7/100
Task breakdown (16 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.
Maintain files and records of surgical procedures.
64CI 60–67 · exposure 70 · augmentation 75 · importance 4.0/5 · click for rater detail
Maintain files and records of surgical procedures.
64| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Healthcare is moderately digitized with uneven adoption of advanced record automation. Many hospitals and surgical centers have EHR systems but continue to rely on hybrid manual-digital workflows; pilot programs exist, but deep production automation of surgical record filing remains inconsistent across the sector. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Healthcare administrative processes are digitizing but adoption of AI-driven documentation tools in surgical settings remains uneven and often limited to larger, well-resourced hospital systems. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can substantially assist surgical technologists by auto-populating templates, organizing records, flagging missing documentation, and suggesting proper filing—allowing technicians to focus on verification and exception handling. This transforms productivity for what is otherwise a time-consuming administrative task. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-powered transcription, template-filling, and record-organization tools can meaningfully speed up documentation tasks for surgical technologists while they remain responsible for final accuracy. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | File and record maintenance for surgical procedures involves structured data entry, documentation organization, and archival—tasks that AI systems can perform end-to-end with minimal human intervention. Modern document management and RPA systems can extract procedure details, populate records, and file documents with high accuracy, easily exceeding 50% time savings. |
| Task automatability | claude-sonnet-5 | 4/5 | Documenting and filing records of surgical procedures is largely structured data entry and summarization, which current AI (e.g., speech-to-text plus EHR templating tools) can handle with substantial time savings, though final verification still requires human review. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Healthcare compliance requirements (HIPAA, state medical board regulations) and institutional credentialing policies impose moderate barriers: human oversight of sensitive medical records is often required, and certain signoff or verification steps may need technician involvement. However, these are supervisory rather than absolute barriers to automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | Medical records require accuracy and compliance with regulations (HIPAA, hospital policy), and while non-clinical staff can input records, oversight and accountability requirements create moderate friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | AI-driven document management and record-keeping cost substantially less than human surgical technician labor for routine filing tasks. The per-task cost of automated record entry and filing is typically one-fifth to one-tenth the hourly rate of skilled technician labor. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | Automated transcription and record-filing software is inexpensive per use compared to the loaded wage of a surgical technologist performing manual documentation, though integration and oversight costs remain. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 4/5 | Deployed products in healthcare organizations (EHR systems, medical record management software, document automation tools) reliably handle surgical record filing and maintenance at scale. While some manual verification may be required for complex cases, mature healthcare IT infrastructure performs this task consistently in production environments. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | EHR-integrated dictation and documentation tools exist and are used in hospitals, but full automated record maintenance still involves manual correction and varies widely in reliability across systems. |
Order surgical supplies.
49CI 25–72 · exposure 50 · augmentation 63 · importance 4.5/5 · click for rater detail
Order surgical supplies.
49| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Healthcare adoption of AI-driven procurement automation lags behind other sectors; most hospitals still rely on manual or semi-manual ordering by technologists, with limited production deployment of autonomous systems due to risk aversion and regulatory conservatism. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Healthcare supply chain digitization is progressing steadily but unevenly, with many hospitals still relying on manual or semi-manual reordering processes alongside newer automated systems. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can assist by suggesting product matches, flagging inventory shortages, and populating standard order templates, moderately improving technologist efficiency without removing them from the ordering loop or the compliance verification requirement. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-assisted inventory forecasting and automated reorder alerts can significantly reduce time technologists spend tracking stock, letting them focus on clinical prep tasks while still verifying case-specific needs. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Ordering supplies involves inventory tracking and form submission, which are partially automatable, but surgical environments require domain expertise to match procedure types to specific sterile and specialized equipment, and to verify regulatory compliance—tasks that demand human judgment today. |
| Task automatability | claude-sonnet-5 | 4/5 | Ordering supplies is largely a structured procurement task—checking inventory levels against par lists and generating purchase orders—which existing software and AI-driven inventory systems can handle with minimal human input. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Hospital procurement is heavily regulated (FDA, Joint Commission, sterility verification), often requires credentialed personnel sign-off, and integrates with complex institutional supply chains and contracts that create organizational and compliance friction against full automation. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensure is required for ordering supplies itself, though hospital procurement policies and vendor contract approvals create some organizational friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Current AI-assisted ordering systems still require significant human oversight, integration into legacy hospital systems, and validation; the all-in cost per order (including fallback handling) remains comparable to or exceeds direct staff ordering. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | Automated inventory/reorder systems are cheap to run per transaction compared to technologist time spent manually tracking and ordering supplies, though integration with hospital ERP systems adds some cost. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | While basic procurement systems exist, no deployed product reliably handles the full scope: matching dynamic surgical schedules, variant product codes, sterility requirements, and institutional protocols without frequent human intervention and error correction. |
| Technical feasibility today | claude-sonnet-5 | 4/5 | Hospital supply chain and inventory management systems already use automated reordering triggers and predictive analytics in production, though surgical-specific nuances (case-specific preference cards) still require some human review. |
Count sponges, needles, and instruments before and after operation.
19CI 18–20 · exposure 25 · augmentation 38 · importance 4.9/5 · click for rater detail
Count sponges, needles, and instruments before and after operation.
19| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Healthcare, especially perioperative settings, adopts automation slowly due to regulatory requirements, liability concerns, and strong institutional resistance to replacing safety-critical human verification. No meaningful production adoption of AI-driven surgical counts exists today. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Healthcare/OR settings are slow to adopt automation for safety-critical manual verification tasks, with adoption of tracking tech being incremental and supplementary rather than replacing human counts. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could potentially assist by flagging potential discrepancies via computer vision to prompt human review, but the core task is straightforward counting that human technologists already perform reliably, limiting meaningful augmentation gains beyond verification support. |
| Augmentation potential | claude-sonnet-5 | 3/5 | RFID/barcode tracking systems can assist by cross-verifying counts and flagging discrepancies, improving accuracy while the technologist remains responsible for the count. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Current AI vision systems can detect and count objects in images, but the task requires high-precision inventory tracking of similar-looking items in dynamic surgical environments with strict liability consequences. Full autonomous counting that eliminates human verification is not reliably deployed at production scale today. |
| Task automatability | claude-sonnet-5 | 2/5 | Some counting could theoretically be assisted by RFID-tagged sponge/instrument tracking systems, but the core manual verification task as performed by a human technologist is not replaceable end-to-end by generalist AI today. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Surgical instrument counts are legally mandated quality and safety procedures; human technologists are required by hospital policy, accreditation standards (Joint Commission), and liability frameworks to verify counts. Regulatory and liability barriers are exceptionally high—a system cannot legally replace human sign-off on this safety-critical task. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Surgical counts are a patient-safety-critical, heavily regulated procedure with legal liability for retained surgical items; protocols require credentialed OR staff to perform and document counts. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Implementing computer vision systems with sufficient accuracy, camera infrastructure, software integration, and ongoing oversight would likely cost more than the wage of a surgical technologist performing this task, especially given the liability and verification overhead required. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Specialized counting-assist hardware (RFID tags, scanners) adds cost per procedure and still requires human oversight, so it is not clearly cheaper than the marginal cost of a technologist performing the count. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | While computer vision for object counting exists in research and limited pilot deployments, no mature product reliably performs surgical instrument/sponge counting in production surgical settings with the precision demanded (zero-error tolerance). Material error rates and integration challenges with existing surgical protocols remain significant. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | RFID and barcode sponge-counting systems exist in some hospitals as adjuncts, but they are narrow specialized hardware products, not general AI systems, and manual counts remain standard practice. |
Observe patients' vital signs to assess physical condition.
18CI 11–25 · exposure 17 · augmentation 63 · importance 4.2/5 · click for rater detail
Observe patients' vital signs to assess physical condition.
18| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | While hospitals use electronic monitoring systems, actual replacement of vital-sign observation by autonomous AI is minimal. Most adoption remains supplemental—dashboards and alerts—not displacement of the technologist's role. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Healthcare, especially surgical settings, adopts AI cautiously due to regulatory, safety, and liability constraints, with monitoring tech augmenting rather than replacing staff. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI-driven dashboards and alert systems assist technologists by highlighting trends and flagging out-of-range values, improving responsiveness. However, the augmentation is partial; human judgment remains central to clinical assessment. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-enabled monitors and predictive alert systems (e.g., early warning scores) meaningfully help staff notice trends and anomalies in vitals, improving situational awareness during surgery. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can extract and flag vital sign data from monitors, the task requires contextual judgment about patient condition and readiness for surgery—something current systems do poorly without human oversight. Partial automation of data logging is possible but falls far short of the 50% time-saving bar for end-to-end task performance. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires real-time physical presence in a sterile surgical field, tactile and visual assessment integrated with immediate response capability; no off-the-shelf AI system performs this end-to-end today. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Surgical protocols, liability frameworks, and OR regulations typically require a licensed or credentialed human to validate vital signs and patient status before surgical procedures. Regulatory and professional standards create strong adoption friction against autonomous AI replacement. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Surgical technologists and OR staff are licensed/certified personnel operating under strict medical liability and regulatory frameworks; patient safety monitoring in surgery legally requires accountable human personnel. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI monitoring systems require substantial setup, integration with surgical suite infrastructure, and continuous human oversight. The all-in cost per patient assessment remains comparable to or higher than a technologist's labor. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Monitoring hardware and alert software are relatively cheap, but the human oversight, judgment, and liability required in an OR setting keep the effective cost of full substitution high. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Medical device integration and automated vital sign monitoring exist in production settings, but interpreting anomalies, making clinical assessments, and deciding intervention still require human surgical technologists. Deployed systems handle data relay, not reliable clinical judgment. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Vital sign monitors and clinical decision-support alerts exist and are widely deployed, but interpreting and acting on vitals in the OR context is still performed by trained humans, not autonomous AI products. |
Wash and sterilize equipment, using germicides and sterilizers.
15CI 5–25 · exposure 13 · augmentation 38 · importance 4.7/5 · click for rater detail
Wash and sterilize equipment, using germicides and sterilizers.
15| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Adoption of sterilization automation in surgical settings has been slow and incremental, limited to support roles; most hospital operating rooms still rely heavily on manual and semi-automated processes overseen by technologists, with cost and regulatory constraints slowing deeper automation. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Healthcare sterile processing is a physically-oriented, highly regulated environment with minimal AI/robotic adoption for this specific task; adoption in this niche remains essentially at zero. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI-assisted monitoring systems, automated sterilization timers, and tracking software can help technologists manage inventory and compliance, but augmentation is limited to supporting workflows rather than transforming productivity across the full task. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with tracking sterilization logs, compliance documentation, or scheduling equipment turnover, but offers little direct enhancement to the physical washing and sterilizing process itself. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While initial sorting and loading of equipment into sterilizers could be partially automated, the physical handling, inspection for contamination, and verification of sterilization cycles require human judgment and dexterity. Current AI/robots cannot reliably perform the full end-to-end task with 50% time savings at equal quality. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical task requiring manipulation of instruments, handling of chemical germicides, and operation of sterilizers in a sterile field; no current AI system can perform the physical washing/sterilizing process end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Healthcare regulations, surgical suite protocols, and liability requirements typically mandate that sterilization processes be verified and documented by credentialed personnel; FDA guidelines and hospital policies create strong legal and organizational barriers to full automation without human sign-off. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Sterile processing is subject to strict infection-control regulations and hospital accreditation standards requiring trained/certified personnel, creating significant liability and regulatory barriers to full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Robotic sterilization systems and specialized washers are capital-intensive and require ongoing maintenance, oversight, and human verification, making total cost-per-cycle comparable to or higher than trained surgical technologist labor in most contexts. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | No viable AI substitute exists for this physical task, so AI cost is not comparable; any automation would require robotics investment far exceeding current labor costs for this narrow task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Some robotic systems exist for laboratory automation and sterilization support, but no deployed product reliably performs the complete washing, sterilizing, and verification task in surgical settings without human oversight. Products remain narrow in scope and require significant human intervention. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | There are no deployed AI products that autonomously wash and sterilize surgical instruments; automated sterilizer machines exist but require human loading, unloading, and verification, and are not AI-driven decision systems. |
Clean and restock operating room, gathering and placing equipment and supplies and arranging instruments according to instructions, such as a preference card.
12CI 5–19 · exposure 8 · augmentation 38 · importance 4.6/5 · click for rater detail
Clean and restock operating room, gathering and placing equipment and supplies and arranging instruments according to instructions, such as a preference card.
12| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Healthcare facilities remain heavily dependent on human technologists; surgical suite automation is nascent and limited to pilot programs, not production deployment at scale. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Healthcare physical/manual tasks in operating rooms show minimal AI or robotic adoption for logistics and instrument handling, a laggard segment even within healthcare. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI-powered inventory tracking, checklist management, and preference-card visualization can assist technologists in locating supplies and verifying completeness, moderately improving workflow efficiency while humans retain control over placement and sterilization. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could help generate or optimize preference cards or inventory tracking software, but it offers little direct assistance to the physical act of cleaning and arranging instruments. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI-guided robotics could theoretically assist with material handling, current systems lack the spatial reasoning, real-world dexterity, and safety validation required to autonomously clean, arrange, and organize complex surgical instruments in a sterile environment. Setup and oversight would consume most labor savings. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical manipulation task requiring picking, sorting, and arranging real objects in a sterile field, which current AI (software/LLM-based) cannot perform; robotics for this specific unstructured task is not deployed.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Healthcare regulatory requirements (sterilization protocols, Joint Commission standards), liability exposure for instrument misplacement, and the critical safety dependency on sterile technique create substantial legal and operational barriers to full automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | While not formally licensed exclusively for this subtask, sterile technique, infection control protocols, and patient safety liability create strong organizational and regulatory friction against automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Integration costs for sterile-environment robotics, safety compliance, and per-location customization far exceed the loaded wage of a surgical technologist per task cycle. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic system performing this task, so any hypothetical solution would require expensive specialized robotics far costlier than a technologist's wage. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed commercial product reliably performs surgical room cleaning and instrument arrangement end-to-end in production healthcare settings. Robotic arms exist but require extensive task-specific programming and fail in unstructured surgical environments. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product autonomously cleans, restocks, and arranges surgical instruments per preference cards in real operating rooms today; this remains research-stage robotics at best. |
Prepare patients for surgery, including positioning patients on the operating table and covering them with sterile surgical drapes to prevent exposure.
3CI 0–5 · exposure 0 · augmentation 13 · importance 4.8/5 · click for rater detail
Prepare patients for surgery, including positioning patients on the operating table and covering them with sterile surgical drapes to prevent exposure.
3| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Surgical environments remain highly conservative and heavily regulated; adoption of automation in this direct patient-prep role is negligible. Existing surgical robotics see slow, limited adoption only for specific procedures, not routine patient positioning. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Healthcare physical care tasks show minimal AI/robotic adoption for direct patient handling; this is a low-digitization, hands-on clinical function. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI offers minimal assistance in patient positioning and draping, as the task demands real-time tactile feedback, sterility awareness, and human judgment. Existing systems do not augment a technologist's ability to prep patients more efficiently or effectively. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no meaningful assistance to the physical acts of positioning a patient and applying sterile drapes. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires physical manipulation of a conscious or anesthetized human body in a sterile environment, positioning them precisely on an operating table, and applying sterile drapes. Current AI systems lack embodied robotics with sufficient dexterity, force control, and real-time sterility assurance to perform these actions end-to-end. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a hands-on physical task requiring manual manipulation of patients' bodies, precise sterile draping, and adaptation to individual anatomy that current AI and robotics cannot perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Patient safety, sterility protocols, and liability create hard barriers. Licensing and regulatory standards require a trained, credentialed human (surgical technologist) to be responsible for patient positioning and sterile technique; automation cannot replace this legal and safety requirement. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Patient safety, sterile field integrity, and hospital liability create strong practical barriers, and licensed/certified personnel are expected to handle direct patient physical care in surgery. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Specialized surgical robots cost hundreds of thousands to millions of dollars, require dedicated infrastructure, and still need a trained human operator present. The all-in cost vastly exceeds the loaded wage of a surgical technologist performing these tasks. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic substitute performing this physical task, so any hypothetical automation would require expensive specialized robotics far costlier than a skilled technologist. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed, production-grade system reliably performs patient positioning and sterile draping in surgical settings today. Surgical robotics exist but require continuous human supervision and are task-specific; they do not autonomously prep patients for surgery. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product autonomously positions and drapes surgical patients today; robotic surgery assistance exists only for surgeon-controlled instrument tasks, not patient prep. |
Prepare dressings or bandages and apply or assist with their application following surgery.
3CI 0–5 · exposure 0 · augmentation 13 · importance 4.7/5 · click for rater detail
Prepare dressings or bandages and apply or assist with their application following surgery.
3| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Healthcare automation adoption remains slow in procedural domains; surgical dressing preparation is low-priority for automation research and has seen minimal real-world deployment due to the need for human judgment and physical dexterity. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Surgical support and physical patient-care tasks in hospital settings show minimal AI/robotic adoption for hands-on procedures like dressing application. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could potentially suggest dressing types based on wound characteristics or protocol, but the core task of physical preparation and application offers limited augmentation opportunity since the technologist must assess and handle the wound directly. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no meaningful assistance for the physical act of preparing and applying dressings during surgery. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Preparing and applying surgical dressings requires fine motor control, real-time assessment of wound condition, and direct physical manipulation that current AI systems cannot perform. While AI might assist in selecting dressing types, the actual preparation and application remain fundamentally manual tasks. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires physical manipulation of sterile materials and application to a patient's body immediately post-surgery, which no current AI system can perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Surgical wound care involves direct patient contact and carries liability for infection or poor healing; medical standards and institutional protocols require licensed personnel (surgical technologists or nurses) to perform or oversee this task, creating hard legal and regulatory barriers. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Sterile technique, infection control protocols, and clinical safety standards mean this task is tightly bound to trained, credentialed personnel in an operating room environment, creating strong practical and regulatory barriers. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The infrastructure required for robotic dressing application would vastly exceed the cost of employing a surgical technologist, and current systems are nowhere near capable of justifying such investment for this task. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute, so any hypothetical automation (specialized robotics) would be far more costly than a trained technologist performing this routine physical task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI system can reliably prepare, handle, or apply surgical dressings autonomously in clinical settings today. This task requires physical embodiment and direct patient contact that existing AI lacks. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed robotic or AI product performs post-surgical dressing/bandage application in clinical settings; this remains firmly manual work. |
Maintain a proper sterile field during surgical procedures.
0CI 0–0 · exposure 0 · augmentation 25 · importance 4.9/5 · click for rater detail
Maintain a proper sterile field during surgical procedures.
0| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Healthcare remains a cautious, regulation-heavy adopter of automation in clinical settings, and sterile field maintenance is among the most risk-sensitive tasks in surgery where institutional adoption of autonomous systems is negligible. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Operating rooms are a highly physical, low-digitization environment with minimal automation of hands-on sterile procedures; adoption of AI for this specific physical task is essentially nonexistent. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Camera-based monitoring systems could theoretically alert technologists to potential contamination, but the task is already performed by a single dedicated professional under intense focus; marginal augmentation gains are modest compared to the critical human judgment required. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI-enabled sensors or computer vision could someday flag contamination risks or track instrument counts, but current deployed assistance for real-time sterile field monitoring is minimal and unproven at scale. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Maintaining a sterile field requires continuous physical monitoring, real-time environmental assessment, and intervention in a complex spatial environment where human error carries extreme consequences. Current AI systems cannot manipulate physical operating room conditions, detect contamination across the full sterile zone, or make corrective interventions autonomously. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a hands-on physical vigilance and manual sterile-technique task performed in real time in the operating room; no current AI system can physically maintain a sterile field, arrange instruments, or catch contamination breaches by touch and observation. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Strict regulatory requirements (FDA, surgical standards, infection control protocols) mandate that a licensed surgical technologist or equivalent healthcare professional maintain and verify the sterile field; liability for surgical site infections creates hard legal responsibility tied to human credentialing. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Sterile technique is a licensed, regulated clinical function with strict infection-control standards, accreditation requirements, and direct patient-safety liability, making human performance legally and practically mandatory. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Even partial AI support (monitoring alone) would require extensive hardware, integration, and operator oversight, making it far more expensive than the labor cost of a surgical technologist who performs this task as part of their routine clinical work. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute performing this physical task, so cost comparison favors the human by default; any hypothetical robotic/monitoring system would require expensive sensors and validation exceeding human labor cost. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed product performs end-to-end sterile field maintenance; this remains entirely dependent on trained human technologists. Computer vision systems exist for some monitoring tasks but are research-stage and cannot substitute for the full responsibility of maintaining sterility throughout a procedure. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs this physical, safety-critical task; sterile field maintenance requires a physically present, trained human monitoring and acting continuously during surgery. |
Scrub arms and hands and assist the surgical team to scrub and put on gloves, masks, and surgical clothing.
0CI 0–0 · exposure 0 · augmentation 0 · importance 4.8/5 · click for rater detail
Scrub arms and hands and assist the surgical team to scrub and put on gloves, masks, and surgical clothing.
0| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Healthcare settings maintain traditional pre-operative scrubbing procedures; there is no meaningful adoption of automation for this critical sterile-field task despite decades of robotics development. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Healthcare physical/procedural tasks like this show minimal AI adoption; surgical technologist roles remain fully manual with no displacement trend evident. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | AI cannot meaningfully assist with physical scrubbing, PPE donning, or hands-on team assistance in the sterile field; the task is entirely manual and human-dependent. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers no meaningful assistance for the physical act of scrubbing hands/arms or donning sterile attire, as this is an inherently manual, tactile process. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task involves physical manipulation of arms, hands, and personal protective equipment in a sterile field, plus direct assistance to humans. Current AI systems cannot perform physical scrubbing, donning of gloves/masks/gowns, or hands-on assistance in a surgical environment. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical, hands-on hygiene and dressing task requiring manual dexterity, physical presence, and real-time coordination with the surgical team; no AI system can perform physical scrubbing or gowning. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Strict sterile field protocols, regulatory requirements for human oversight in surgical preparation, and the requirement that a licensed surgical technologist or physician verify and assist with proper donning of surgical attire create hard legal and procedural barriers. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Sterile technique and infection control in surgery are governed by strict clinical protocols and licensing/certification requirements, and this task requires direct human physical execution with no legal path to automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Robotic systems capable of this task would require custom hardware, integration, and ongoing maintenance far exceeding the cost of a surgical technologist performing these essential pre-operative duties. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI-based alternative performing this physical task, so cost comparison favors the human by default; any robotic solution would be far more expensive than current human labor. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product can physically scrub human skin, assist humans with PPE donning, or operate autonomously in a sterile surgical field. This remains purely human-performed in all surgical settings. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs physical surgical scrubbing or gowning assistance; this remains purely a human manual task with no robotic or AI substitute in production. |
Provide technical assistance to surgeons, surgical nurses, or anesthesiologists.
0CI 0–0 · exposure 0 · augmentation 25 · importance 4.8/5 · click for rater detail
Provide technical assistance to surgeons, surgical nurses, or anesthesiologists.
0| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Healthcare remains a laggard in AI automation due to regulation, high error cost, and physical task requirements. Despite decades of robotics research, no surgical AI has displaced OR technical staff in meaningful volume, and current medical AI adoption focuses on diagnostic imaging and administrative tasks. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Healthcare's physical, high-stakes operating room environment is a slow-adopting sector for AI-driven task automation, especially for direct physical assistance roles. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Limited augmentation potential exists; AI might assist with procedural scheduling or post-operative documentation, but the core technical assistance (instrument handoff, anticipation, sterile field management) remains almost entirely dependent on the human technologist's presence and judgment. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI can support pre-op planning, inventory tracking, or documentation, but offers minimal direct augmentation to the hands-on technical assistance provided during surgery itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires real-time physical presence in the operating room, adaptive responsiveness to unpredictable surgical events, and judgment about sterile field management—capabilities no current AI system possesses. AI cannot manipulate instruments, anticipate surgeon needs before they are voiced, or maintain sterile protocol. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a hands-on physical task requiring real-time instrument handling, sterile technique, and coordination inside an operating room, none of which current AI can perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Surgical technologists are licensed professionals whose presence and actions in the OR are legally mandated. Hospitals and surgical teams face strict credentialing, liability, and regulatory requirements; no unlicensed system (AI or otherwise) can legally substitute for this role during operative procedures. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Surgical settings require certified, licensed personnel physically present for sterile technique and instrument handling, with strict liability and regulatory oversight preventing any non-human substitution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | AI systems cannot yet perform this task at all, making cost comparison moot. Even research prototypes remain far from the reliability required, and the human surgical technologist salary (loaded ~$60–80k) vastly exceeds current AI inference costs that would replace zero task hours. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI system that substitutes for this labor, so any comparison favors the human; specialized robotics for this exact role don't exist commercially. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product performs surgical technical assistance in production. The task involves dynamic physical coordination, sterile environment management, and split-second decision-making in high-stakes contexts where errors carry severe consequences. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product provides physical surgical technical assistance; robotic surgery systems assist surgeons directly but do not replace the surgical technologist role. |
Hand instruments and supplies to surgeons and surgeons' assistants, hold retractors and cut sutures, and perform other tasks as directed by surgeon during operation.
0CI 0–0 · exposure 0 · augmentation 25 · importance 4.8/5 · click for rater detail
Hand instruments and supplies to surgeons and surgeons' assistants, hold retractors and cut sutures, and perform other tasks as directed by surgeon during operation.
0| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Adoption of autonomous surgical assisting remains in research and early pilot phases; the vast majority of operating rooms rely entirely on human surgical technologists. Financial and regulatory barriers prevent meaningful production deployment. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Surgical support staff roles are essentially untouched by AI adoption; healthcare's physical, high-liability operating room environment sees minimal automation of hands-on tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Current surgical robotics can augment specific subtasks (e.g., camera control, precise retraction), but general instrument anticipation and handoff during dynamic surgery remains largely human-driven. Limited productivity lift from partial automation of routine steps. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI can assist with surgical planning, instrument tracking, or inventory logistics, but offers negligible real-time augmentation of the physical hand-to-hand instrument passing task itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires real-time physical manipulation in a sterile surgical environment, precise spatial coordination, responsiveness to surgeon verbal/gestural cues, and context-dependent judgment about which instruments to provide. Current AI cannot reliably perform physical actions in such high-stakes, real-time settings. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical, real-time manual task requiring dexterous handling of sterile instruments in direct response to a surgeon's actions inside an operating field; no current AI system can perform this physically or contextually. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Surgical assistance in sterile fields involves direct patient safety liability; a licensed human (surgical technologist or surgeon) must maintain stewardship over instrument selection and sterile protocol. Regulatory bodies (FDA, state medical boards) require human accountability and hands-on oversight during surgery. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Sterile field protocols, patient safety regulations, and the need for immediate human judgment and physical dexterity under surgeon direction make this a hard-barrier task requiring trained, credentialed humans. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Surgical robots and robotic arms capable of sterile field operation are extremely expensive to purchase, maintain, and integrate into OR workflows. The total cost of ownership far exceeds the loaded wage of a surgical technologist per procedure. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI/robotic substitute performing this function, so any hypothetical automation would require expensive specialized robotics far costlier than a technologist's wage today. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed product performs intraoperative surgical assisting with independent physical instrument handling and supply management. Surgical robotics exist but require explicit surgeon control and do not autonomously anticipate and hand off instruments based on surgeon direction. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs live sterile instrument handling or intraoperative physical assistance; surgical robotics exist but require a human surgeon and separate sterile staff for this exact role. |
Prepare, care for, and dispose of tissue specimens taken for laboratory analysis.
0CI 0–0 · exposure 0 · augmentation 25 · importance 4.7/5 · click for rater detail
Prepare, care for, and dispose of tissue specimens taken for laboratory analysis.
0| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Healthcare organizations have been slow to adopt laboratory automation for specimen handling; most tissue processing remains manual or semi-automated with significant human involvement due to regulatory, safety, and quality assurance requirements. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Surgical technology is a highly physical, hands-on healthcare role with minimal AI/robotic adoption for direct specimen handling tasks in current practice. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Current AI offers minimal augmentation; computer-aided specimen tracking (LIMS integration) exists but does not fundamentally assist the core manual preparation, care, and disposal work that defines this task. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with documentation, labeling accuracy checks, or specimen tracking software, but offers minimal assistance to the physical preparation and handling itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Tissue specimen handling requires physical manipulation, sterile technique, and real-time contextual judgment about specimen integrity and preservation. Current AI systems cannot physically handle biological materials or adapt to variable specimen conditions without human oversight. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a hands-on physical task involving sterile handling of biological specimens in an operating room; current AI systems have no robotic manipulation capability to perform this end-to-end.chemical or physical task. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Stringent clinical and regulatory requirements (CLIA, CAP accreditation, state licensing) legally require trained, credentialed personnel to handle and process pathological specimens. Hospital liability and chain-of-custody protocols create hard barriers to full automation. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Chain-of-custody, sterile technique, and specimen handling are subject to strict clinical protocols, accreditation standards, and legal/regulatory requirements mandating trained, certified personnel. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Specialized tissue handling robots and integrated lab automation systems remain far more expensive than paying a surgical technologist, accounting for capital costs, maintenance, validation, and regulatory compliance. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI system substitute performing this physical handling task, so AI cost is not comparable—human labor is the only viable option today. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI system reliably performs end-to-end tissue specimen preparation, care, and disposal independently. This task requires physical robotics integrated with sterile protocols and pathological decision-making, which exists only in research. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product exists that physically prepares, labels, and disposes of surgical tissue specimens; this remains entirely a human manual and procedural task. |
Monitor and continually assess operating room conditions, including patient and surgical team needs.
0CI 0–0 · exposure 0 · augmentation 25 · importance 4.7/5 · click for rater detail
Monitor and continually assess operating room conditions, including patient and surgical team needs.
0| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Surgical settings are highly regulated, risk-averse environments with strong human-contact and licensure requirements. Adoption of AI for this task remains negligible; the sector has not moved beyond niche pilots or proof-of-concept, and organizational inertia around patient safety is substantial. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Healthcare, especially perioperative/surgical settings, is a slow-adopting, highly regulated, physically-grounded sector with minimal AI-driven displacement of hands-on roles. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Current AI tools (e.g., vital-sign dashboards, image analysis for wound monitoring) can provide marginal assistance on specific sub-tasks, but the holistic assessment of team needs, sterile conditions, and adaptive prioritization that a surgical tech performs remains largely manual and difficult to augment meaningfully with today's systems. |
| Augmentation potential | claude-sonnet-5 | 2/5 | Some AI-enabled monitoring tools (vital sign analytics, OR scheduling dashboards) can supplement situational awareness, but they play only a minor supporting role in this holistic, real-time task. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Monitoring OR conditions requires real-time perception of complex environmental and human factors (patient vitals, team communication, sterile field integrity, unexpected complications) that demand embodied presence and immediate adaptive response. Current AI systems lack the integrated sensing, contextual judgment, and accountability needed to reliably manage this continuously throughout a procedure. |
| Task automatability | claude-sonnet-5 | 1/5 | Real-time situational monitoring of a live surgical environment requires continuous physical presence, tactile awareness, and split-second judgment that no current AI system can replicate end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Surgical technologists are licensed professionals whose scope of practice and accountability for patient safety and sterile technique are legally defined and regulated. The standard of care and liability framework require a qualified human to assess OR conditions and patient needs; substitution by automation faces hard regulatory and malpractice barriers. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Surgical technologist roles require certification, physical presence in sterile fields, and direct accountability for patient safety, all legally and institutionally mandated, creating maximal barriers to automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The infrastructure cost to instrument an OR with sufficient sensors, compute, and safety-critical redundancy, plus ongoing integration and liability coverage, far exceeds the hourly wage of a surgical technologist who already provides this service as part of their role. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | No viable AI substitute exists for this role, so any cost comparison is moot; the human remains the only option, making AI's effective cost-per-task infinite relative to the human. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product performs end-to-end OR monitoring and assessment in production. While individual components (vital sign monitoring, camera feeds) exist, synthesizing these into the holistic situational awareness a surgical tech provides—including reading team cues, predicting needs, and responding to emergencies—is research-stage only. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | There are no deployed products that autonomously monitor operating room conditions and surgical team/patient needs in place of a human technologist; sensor-based OR monitoring exists only as adjunct decision support, not substitution. |
Operate, assemble, adjust, or monitor sterilizers, lights, suction machines, or diagnostic equipment to ensure proper operation.
0CI 0–0 · exposure 0 · augmentation 25 · importance 4.7/5 · click for rater detail
Operate, assemble, adjust, or monitor sterilizers, lights, suction machines, or diagnostic equipment to ensure proper operation.
0| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Surgical environments remain highly regulated and conservative; adoption of autonomous equipment operation is negligible. Hospitals rely on trained staff for this task, and the safety-critical nature of surgical equipment limits experimentation with automation. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Healthcare surgical support roles involve physical, safety-critical work with minimal AI/robotics penetration into equipment handling tasks to date. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Monitoring alerts and diagnostic dashboards could assist technologists in tracking equipment status, but the task is primarily hands-on operation and adjustment. AI assistance is limited to passive monitoring rather than transforming active operational productivity. |
| Augmentation potential | claude-sonnet-5 | 2/5 | Some diagnostic equipment includes automated alerts or self-monitoring features that aid technologists, but this offers only marginal assistance to the core physical task. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires physical manipulation of equipment in real-time surgical environments, real-time troubleshooting, and immediate response to equipment failures—capabilities far beyond current AI systems. While some monitoring could theoretically be automated, the full task of operating, assembling, and adjusting diverse surgical equipment requires embodied intelligence and direct responsibility that AI cannot reliably provide today. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires hands-on physical setup, adjustment, and real-time monitoring of medical equipment in a sterile surgical environment, none of which current AI can perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Surgical equipment operation is performed in sterile, regulated environments governed by hospital policies, FDA standards, and clinical safety protocols. A licensed surgical technologist is typically required for sterilization and equipment preparation, and liability for equipment malfunction during surgery creates strong legal and organizational barriers to full automation. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Surgical technologists are certified/credentialed and operating room equipment handling is tightly regulated for patient safety, requiring qualified human personnel by law and institutional policy. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The cost of robotics capable of assembling and adjusting surgical equipment, combined with integration, validation, and liability oversight in a surgical suite, would far exceed the wages of a trained surgical technologist. Integration and safety certification add substantial cost. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute performing this physical equipment operation, so any comparison favors the human worker entirely. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI products reliably operate, assemble, or adjust surgical sterilizers and diagnostic equipment in production clinical settings. Current systems lack the physical manipulation, real-time decision-making, and safety-critical response capabilities required in sterile surgical environments. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed AI product operates or assembles sterilizers, lights, or suction machines in an operating room; this remains a manual physical task performed by trained staff. |
Maintain supply of fluids, such as plasma, saline, blood, or glucose, for use during operations.
0CI 0–0 · exposure 0 · augmentation 25 · importance 4.4/5 · click for rater detail
Maintain supply of fluids, such as plasma, saline, blood, or glucose, for use during operations.
0| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Healthcare adoption of automation for critical intraoperative tasks remains minimal; this specific function requires human judgment, sterile technique, and immediate responsiveness in a heavily regulated environment. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Healthcare operating rooms are a low-digitization, physically-constrained environment where robotic/AI adoption for hands-on tasks like this is minimal and slow. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could potentially provide alerts or decision support (e.g., flagging unusual fluid requirements), but the core task of managing infusions demands continuous human presence and tactile control, limiting meaningful augmentation. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could help with inventory tracking or predictive supply forecasting, but offers little direct assistance to the real-time physical task of maintaining fluids during surgery. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Maintaining fluid supply during surgery requires physical handling of IV lines, monitoring actual infusion rates, and real-time adjustment based on patient condition—tasks that demand embodied presence and tactile interaction that current AI systems cannot perform. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a hands-on, physical task requiring sterile handling, monitoring, and rapid response during live surgery, which current AI systems cannot perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 5/5 | Surgical fluid management is legally and clinically required to be performed or directly supervised by licensed medical personnel; patient safety liability and regulatory requirements create hard barriers to full automation. |
| Adoption barriers | claude-sonnet-5 | 5/5 | Sterile field management and direct surgical support require certified, trained personnel physically present, with strict liability and safety regulations preventing automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The cost of any robotic system capable of managing surgical fluids would vastly exceed the loaded wage of a surgical technologist, and integration complexity in the OR environment makes this economically infeasible. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI substitute performing this physical task, so cost comparison favors the human worker by default. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product reliably manages surgical fluid administration; this task requires physical manipulation in a sterile environment and direct patient monitoring that only trained humans can execute in production settings. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product manages sterile fluid supply logistics in an active operating room; this remains entirely a human manual task. |
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.