Orderlies

31-1132.00
Median wage $38,290/yr52,440 employed (US)Rank #782 of 923 scored · top 85% by substitution

Transport patients to areas such as operating rooms or x-ray rooms using wheelchairs, stretchers, or moveable beds. May maintain stocks of supplies or clean and transport equipment. Psychiatric orderlies are included in Psychiatric Aides.

Sub-scores

0–100 · band = confidence interval from rater disagreement

Substitution15
Exposure12
Augmentation23

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

22 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%13

panel mean rating 1.5/5 → substitution pressure 13/100

Technical feasibility todayw 20%10

panel mean rating 1.4/5 → substitution pressure 10/100

Cost vs. human wagew 15%9

panel mean rating 1.4/5 → substitution pressure 9/100

Adoption barriersw 20%inverted — strong barriers lower the score32

panel mean rating 3.7/5 (barrier strength) → substitution pressure 32/100

Sector adoption velocityw 10%10

panel mean rating 1.4/5 → substitution pressure 10/100

Task breakdown (22 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.

Transport portable medical equipment or medical supplies between rooms or departments.

47

CI 16–79 · exposure 45 · augmentation 25 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510014/5Major health systems and hospital networks are actively deploying supply robots; significant pilots are underway across tier-1 and tier-2 medical centers in the US and internationally. Adoption is accelerating in digitized, capital-rich healthcare settings.
Sector adoption velocityclaude-sonnet-52/5Healthcare facility operations are a low-digitization, physical-labor-heavy sector where robotic adoption for logistics is happening but remains niche and slow compared to information-sector AI adoption.
Augmentation potentialclaude-haiku-4-5-202510012/5Once a robot is handling transport, there is minimal assistance role for the human orderly in the core task. Augmentation potential is low because the task is primarily logistical movement rather than one requiring human judgment or decision-making in parallel with automation.
Augmentation potentialclaude-sonnet-52/5AI-assisted routing or robotic carts can somewhat support logistics planning, but for the core physical transport task itself, current AI offers limited direct assistance to the human orderly.
Task automatabilityclaude-haiku-4-5-202510015/5Transporting portable medical equipment and supplies between fixed, known locations is a well-structured physical task. Autonomous mobile robots (AMRs) and robotic delivery systems deployed in hospitals today can navigate corridors, use elevators, and deliver items to specific departments with minimal human oversight, achieving substantial time and labor savings.
Task automatabilityclaude-sonnet-51/5This is a physical manual transport task requiring navigating hospital environments, handling equipment, and interacting with staff/patients; no off-the-shelf AI system performs this end-to-end today.
Adoption barriersclaude-haiku-4-5-202510013/5Hospitals face moderate barriers: infection control protocols, liability for equipment damage or misplacement, and staff resistance; however, no strict licensing requirement exists for the task itself, and delivery robots do not require legal sign-off. Organizational adoption requires some workflow redesign and safety integration.
Adoption barriersclaude-sonnet-53/5No licensing requirement for this specific task, but hospital safety protocols, infection control, liability for equipment damage, and need for judgment in emergency situations create real friction against full automation.
Cost vs. human wageclaude-haiku-4-5-202510014/5A hospital-deployed AMR costs roughly $50–150k upfront with operational costs of $3–8/hour, compared to an orderly wage (~$35–50k/year or ~$20/hour loaded). At high utilization (16+ hours/day), the per-task cost becomes significantly cheaper than human labor within 2–3 years.
Cost vs. human wageclaude-sonnet-52/5Autonomous delivery robots require significant capital investment, facility modification, and maintenance, making them costly relative to an orderly's wage except at very large scale facilities with high volume.
Technical feasibility todayclaude-haiku-4-5-202510014/5Multiple hospital systems have deployed autonomous delivery robots (e.g., Tugs, Gita, Moxi) in production for supply and equipment transport. These systems perform reliably on standard hospital routes, though they require some environmental adaptation (elevator integration, floor mapping) and human handoff for final placement in crowded or non-standard spaces.
Technical feasibility todayclaude-sonnet-51/5While hospital delivery robots exist in pilot or limited deployments for specific supply routes, general transport of arbitrary portable medical equipment between rooms is not a mature, widely deployed product capability.

Collect soiled linen or trash.

46

CI 15–77 · exposure 45 · augmentation 13 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510013/5Healthcare and hospitality sectors show growing but uneven pilot adoption of robotic collection; production deployment is rising but still not dominant, making adoption middling rather than fast and deep.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/janitorial functions are a laggard sector for AI and robotics adoption, with physical automation of this nature essentially absent in production.
Augmentation potentialclaude-haiku-4-5-202510012/5AI/robotic assistance offers minimal augmentation to a human orderly's core task—the work is already manual and repetitive, and robots are designed for replacement rather than in-loop support.
Augmentation potentialclaude-sonnet-51/5AI offers no meaningful assistance for this manual collection task since it is purely physical labor with no cognitive or planning component to augment.
Task automatabilityclaude-haiku-4-5-202510015/5Robotic systems (vacuum, autonomous collection, bin-lifting robots) can collect linen and trash end-to-end with significant time savings today; this is a highly structured, repetitive physical task with clear endpoints that current automation technology handles efficiently.
Task automatabilityclaude-sonnet-51/5This is a physical manipulation task requiring mobility, dexterity, and navigation through hospital environments; no current AI/robotic system can perform this end-to-end at equal quality with time savings.
Adoption barriersclaude-haiku-4-5-202510012/5Few legal or licensing barriers exist; main friction is organizational inertia, existing workforce considerations, and customer comfort—but nothing legally prevents full automation of linen and trash collection.
Adoption barriersclaude-sonnet-52/5No licensing or legal requirement mandates a human perform this specific task, though infection control protocols and hospital logistics create some procedural friction.
Cost vs. human wageclaude-haiku-4-5-202510013/5Robotic collection systems have substantial upfront capital costs and maintenance overhead that can rival or exceed the loaded wage of an orderly in lower-cost labor markets, making the economics sector-dependent.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic solution for this physical task, so any hypothetical automation would require expensive specialized robotics far exceeding orderly wages.
Technical feasibility todayclaude-haiku-4-5-202510014/5Deployed robotic solutions (e.g., autonomous floor-cleaning robots, robotic waste bins, collection drones in some facilities) perform this task reliably in production environments, though deployment is not yet universal across all facility types.
Technical feasibility todayclaude-sonnet-51/5No deployed products in healthcare settings autonomously collect soiled linen or trash; this remains far beyond current robotics deployment in clinical environments.

Clean equipment, such as wheelchairs, hospital beds, or portable medical equipment, documenting needed repairs or maintenance.

34

CI 10–57 · exposure 33 · augmentation 38 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Healthcare adoption of robotic cleaning and monitoring tools remains concentrated in large hospital systems and is still in pilot or early deployment phases. Widespread production-scale adoption across clinics, small hospitals, and ambulatory centers is limited by cost, integration friction, and organizational inertia.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/janitorial functions are a low-digitization, physically intensive segment with minimal AI/robotic adoption for equipment cleaning tasks.
Augmentation potentialclaude-haiku-4-5-202510013/5Mobile monitoring apps and automated logging tools assist orderlies in documenting equipment status and maintenance schedules, and robotic or UV systems can handle initial disinfection, freeing orderlies for inspection and triage. The human remains essential for complex judgment and verification, making this meaningfully assistive.
Augmentation potentialclaude-sonnet-52/5AI could help with the documentation portion (logging needed repairs via voice-to-text or simple apps), but offers no assistance with the physical cleaning itself.
Task automatabilityclaude-haiku-4-5-202510014/5Robotic systems can physically clean equipment (wheelchairs, beds, medical devices) with documented efficacy in clinical settings, and automated monitoring systems can track and log maintenance needs. The task involves straightforward mechanical cleaning and data entry, both of which are within reach of current autonomous systems to achieve >50% time savings at equal quality.
Task automatabilityclaude-sonnet-51/5Physical cleaning of wheelchairs, beds, and medical equipment requires manual dexterity, mobility, and physical manipulation that current AI systems cannot perform; this is a robotics/physical task, not a cognitive one.
Adoption barriersclaude-haiku-4-5-202510013/5Healthcare environments impose moderate barriers: regulatory expectations around documentation quality, infection control compliance, and hospital procurement standards require human oversight. However, no explicit legal mandate requires a licensed human to perform cleaning or inspection, only to verify and sign off on critical repairs.
Adoption barriersclaude-sonnet-52/5No licensing requirement specifically for cleaning equipment, though infection-control protocols and hospital policy create some procedural friction; the main barrier is technical infeasibility rather than regulation.
Cost vs. human wageclaude-haiku-4-5-202510012/5While specialized medical cleaning robots and IoT monitoring systems have dropped in price, the integration cost, maintenance, and oversight infrastructure still approach or exceed the loaded wage of an orderly, particularly for the full end-to-end workflow. Full cost parity has not yet been achieved at scale.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI system performing this physical task, so any hypothetical robotic solution would be far more expensive than an orderly's wage given current robotics costs.
Technical feasibility todayclaude-haiku-4-5-202510013/5Robotic cleaning systems exist in healthcare settings (UV-C disinfection robots, automated washers) and condition-monitoring tools are deployed, but end-to-end automation combining physical cleaning, inspection, and reliable defect documentation remains limited in production. Most deployed solutions handle partial workflows rather than the full task consistently.
Technical feasibility todayclaude-sonnet-51/5No deployed products autonomously clean and inspect hospital equipment at scale; general-purpose robotic manipulation for varied cleaning tasks remains research-stage.

Stock or issue medical supplies, such as dressing packs or treatment trays.

30

CI 25–35 · exposure 25 · augmentation 38 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Healthcare is digitizing slowly in supply-chain areas; large hospital systems pilot automated solutions, but adoption remains limited. Small and rural clinics—where most orderlies work—have minimal automation of supply stocking, reflecting laggard sectoral adoption patterns.
Sector adoption velocityclaude-sonnet-52/5Healthcare facility logistics and physical supply chain functions are historically slow to adopt automation compared to information-processing sectors, though automated dispensing cabinets have seen moderate uptake over the past decade.
Augmentation potentialclaude-haiku-4-5-202510013/5Digital inventory dashboards and mobile apps can assist orderlies by showing real-time supply levels and prioritizing restocking locations, improving efficiency and reducing search time without removing the human from the loop.
Augmentation potentialclaude-sonnet-52/5AI-driven inventory management and reordering software can help predict and flag supply needs, offering some assistance, but does not meaningfully change the physical labor of stocking/issuing trays.
Task automatabilityclaude-haiku-4-5-202510012/5While inventory tracking systems can automate counting and ordering, the physical stocking and issuing of medical supplies—requiring location knowledge, handling of varied items, and in-person distribution to care units—remains largely manual. Current AI cannot fully replace human judgment on inventory placement and immediate supply access needs.
Task automatabilityclaude-sonnet-52/5This task requires physical manipulation, movement through a hospital, and locating/placing physical supplies, which current AI systems (software/LLMs) cannot perform without embodiment; only inventory-tracking software portions are automatable, not the physical stocking/issuing itself.
Adoption barriersclaude-haiku-4-5-202510014/5Healthcare facilities face regulatory compliance requirements for medical supply handling and chain-of-custody documentation. Additionally, clinical staff often prefer human orderlies for real-time responsiveness and the ability to communicate urgent supply needs, creating organizational and safety barriers to full automation.
Adoption barriersclaude-sonnet-52/5No licensing requirement for stocking supplies, but hospital logistics, infection control protocols, and physical facility integration create some friction against wholesale automation of the physical movement of supplies.
Cost vs. human wageclaude-haiku-4-5-202510012/5Deploying automated inventory systems, robotic picking, and delivery mechanisms would require substantial capital and integration costs that currently exceed the labor cost of a single orderly position, particularly in smaller or mid-sized healthcare facilities.
Cost vs. human wageclaude-sonnet-52/5Physical automation (robots, automated dispensing cabinets) requires significant capital investment in hardware and integration, which is often more expensive than low-wage orderly labor for this specific narrow task, though inventory software alone is cheap.
Technical feasibility todayclaude-haiku-4-5-202510012/5Basic inventory management software exists, but end-to-end automation of physical stocking and real-time issuance of medical supplies to clinical units lacks reliable deployed solutions. Robotics for warehouse stocking are nascent in healthcare settings; most medical supply chains still rely on human orderlies for last-mile distribution.
Technical feasibility todayclaude-sonnet-52/5Automated inventory systems and RFID-based supply cabinets exist in some hospitals for tracking, but robotic stocking/issuing of medical supplies to point-of-care remains rare and largely pilot-stage rather than mainstream production.

Transport specimens, laboratory items, or pharmacy items, ensuring proper documentation and delivery to authorized personnel.

28

CI 25–30 · exposure 25 · augmentation 38 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Healthcare is relatively slow to adopt autonomous delivery despite pilots. Physical infrastructure (elevators, narrow corridors, equipment compatibility), accreditation concerns, staff resistance, and regulatory uncertainty limit rollout to a handful of major academic medical centers. Most hospitals continue relying on orderlies, indicating low real-world adoption velocity.
Sector adoption velocityclaude-sonnet-52/5Healthcare facilities, especially hospitals, are historically slow adopters of physical automation due to capital constraints, safety validation, and infrastructure retrofitting needs.
Augmentation potentialclaude-haiku-4-5-202510013/5Tracking systems, route-planning software, and automated documentation systems can assist orderlies by reducing manual paperwork and optimizing routes. However, AI assistance here is modest and incremental—documentation systems already exist, and route optimization provides modest productivity gains. The human must remain engaged for delivery verification and handling.
Augmentation potentialclaude-sonnet-52/5AI can assist with tracking/documentation via barcode/RFID systems and scheduling optimization, but offers limited assistance to the core physical transport and handoff task.
Task automatabilityclaude-haiku-4-5-202510012/5This task has significant physical and logistical barriers. While documentation and tracking could be partially automated, the core requirement—transporting items to specific authorized locations in a hospital or laboratory—requires physical presence, real-time navigation of complex indoor spaces, and handling of potentially fragile or hazardous materials. No current system can reliably handle the end-to-end task at 50% time saving.
Task automatabilityclaude-sonnet-52/5Physical transport of specimens/items through a hospital environment requires navigation, handling, and identity verification that current general-purpose AI cannot perform end-to-end; only narrow robotic delivery systems address parts of this in limited settings.
Adoption barriersclaude-haiku-4-5-202510014/5Healthcare delivery faces substantial regulatory and liability barriers. Chain-of-custody documentation for laboratory specimens, compliance with hazardous material transport rules, and verification that authorized personnel receive items create legal accountability that currently requires human sign-off. Some jurisdictions explicitly require a human orderly or technician to handle controlled substances or biohazards.
Adoption barriersclaude-sonnet-53/5Chain-of-custody, documentation accuracy, and patient safety concerns create moderate regulatory and liability friction, though this isn't a licensed task requiring credentialed sign-off.
Cost vs. human wageclaude-haiku-4-5-202510012/5Current autonomous delivery systems (robots, integration, maintenance, remote operations) cost tens of thousands to hundreds of thousands per unit with ongoing operational costs. Orderly wages are typically $25k–$35k annually. The all-in cost per delivery task still exceeds human labor when accounting for deployment scope, error recovery, and oversight requirements.
Cost vs. human wageclaude-sonnet-52/5Autonomous delivery robots have high upfront capital and integration costs (facility mapping, elevator integration, maintenance) that often exceed the wage cost of an orderly performing the same task, especially at smaller scale.
Technical feasibility todayclaude-haiku-4-5-202510012/5Autonomous delivery robots exist in research and early pilots (e.g., hospital delivery robots) but operate only in narrow, pre-mapped environments with significant human oversight and frequent handoffs. They cannot reliably navigate unpredictable hospital/lab spaces, handle diverse specimen types, or verify 'authorized personnel' at the point of delivery. Production deployments remain rare and limited.
Technical feasibility todayclaude-sonnet-52/5Hospital delivery robots exist and are deployed in some large facilities for point-to-point transport, but they require fixed infrastructure, cannot handle all exceptions, and are far from ubiquitous.

Stock utility rooms, nonmedical storage rooms, or cleaning carts with supplies.

26

CI 19–34 · exposure 20 · augmentation 25 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare logistics automation remains nascent despite years of pilot interest; most hospitals still use manual orderly labor for stocking due to cost-benefit mismatch and the need for multipurpose staff. Actual production deployment of stocking robots in hospitals remains minimal.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/janitorial functions are a low-digitization, physical-labor sector with minimal AI or robotics adoption for routine restocking tasks.
Augmentation potentialclaude-haiku-4-5-202510012/5Inventory management software and mobile carts with automated picking lists could assist orderlies in organizing and locating supplies, but AI assistance on the core stocking task itself (grasping, placing, organizing physical items) remains limited compared to what a human already does intuitively.
Augmentation potentialclaude-sonnet-52/5Basic inventory tracking software or apps could help orderlies know what to restock and when, but this offers only modest assistance to the core physical task.
Task automatabilityclaude-haiku-4-5-202510012/5While robots could theoretically move and place items in storage areas, the task requires spatial reasoning, inventory tracking, and handling of varied item types and sizes that current AI-controlled systems rarely do reliably end-to-end. Existing automation is limited to controlled environments with structured layouts, not the varied real-world utility and storage rooms typical in hospitals.
Task automatabilityclaude-sonnet-52/5This requires physical manipulation of objects across a facility—identifying stock levels, retrieving supplies, and physically restocking carts and rooms—which current AI systems cannot perform without robotic embodiment.4
Adoption barriersclaude-haiku-4-5-202510013/5Healthcare facilities have modest adoption friction: orderlies perform multiple related tasks, restocking is mixed with other duties, and there is organizational preference for human flexibility and responsiveness. However, no legal licensing or formal regulatory barrier prevents automation of this nonmedical logistical task.
Adoption barriersclaude-sonnet-51/5No licensing, regulatory, or liability barriers prevent automation of this task itself; the limitation is purely technological/physical capability, not legal or organizational restriction.
Cost vs. human wageclaude-haiku-4-5-202510011/5Mobile manipulation robots capable of stocking tasks remain expensive (six figures), require infrastructure changes, and need ongoing maintenance and oversight, making them substantially more costly than paying orderlies for this routine labor at current scales.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI-driven robotic solution for this specific physical restocking task at comparable cost to a low-wage human worker performing it directly.
Technical feasibility todayclaude-haiku-4-5-202510012/5Some mobile manipulation prototypes exist in research settings, but no deployed products reliably stock mixed supply inventories across diverse hospital environments at production scale. Current systems require extensive customization and struggle with variable item geometry and placement rules.
Technical feasibility todayclaude-sonnet-51/5No deployed product in hospital or facility settings autonomously stocks utility rooms or cleaning carts; this remains a manual physical task performed by staff.

Serve or collect food trays.

22

CI 14–30 · exposure 20 · augmentation 25 · importance 2.4/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Health care is a laggard sector in automation of patient-facing tasks; orderly roles remain almost entirely human-staffed. Pilot robotics exist in a small number of advanced hospitals, but production displacement is minimal and adoption remains slow due to safety and regulatory concerns.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/orderly roles are physical, low-digitization jobs with minimal AI or robotic adoption in production settings currently.
Augmentation potentialclaude-haiku-4-5-202510012/5Automated tray carts and mobile robots can reduce walking and heavy lifting, but the task of serving food (verification, patient interaction, special requests) and collecting trays (checking consumption, patient safety) still require human judgment and presence. Assistance is limited to logistics, not the core service element.
Augmentation potentialclaude-sonnet-52/5AI can assist with route optimization or inventory tracking for meal delivery, but offers little direct productivity boost to the physical act of serving/collecting trays.
Task automatabilityclaude-haiku-4-5-202510012/5While collection of trays in controlled environments could be partially automated by robots, the full task of serving and collecting food trays involves variable layouts, patient safety concerns, dietary requirements confirmation, and adaptability to different hospital or facility settings. Current general-purpose systems lack the dexterity and context-awareness to perform this consistently at 50% time savings without significant setup per location.
Task automatabilityclaude-sonnet-52/5Physically serving and collecting food trays requires mobility, manipulation, and navigation in dynamic hospital settings that current general-purpose AI cannot perform end-to-end; some robotic delivery carts exist but are narrow and supervised.”, ratio of automatable time is low. Given schema, rating 2 reflects limited automatable share. (See rationale field text).
Adoption barriersclaude-haiku-4-5-202510014/5Health-care facilities have strict liability, safety, and infection-control requirements; food service and patient handling involve direct human contact and regulatory oversight that create strong friction against full automation. Facilities prefer human staff for dietary verification, patient communication, and safety accountability.
Adoption barriersclaude-sonnet-53/5No licensing requirement, but hospital infection control, patient safety, and physical logistics create real friction against replacing humans with machines for this task.
Cost vs. human wageclaude-haiku-4-5-202510012/5Robotics capable of tray service remain expensive (hardware, maintenance, integration) and typically require human staff for safety checks and patient interaction. The all-in cost of such systems currently exceeds the loaded wage of entry-level orderlies in most care settings.
Cost vs. human wageclaude-sonnet-51/5Robotic or automated solutions for tray delivery require expensive hardware, facility integration, and maintenance, making them costlier per task than paying a low-wage orderly today.
Technical feasibility todayclaude-haiku-4-5-202510012/5Limited robotic and autonomous systems exist in narrow hospital contexts (tray delivery robots), but they operate in structured environments with human oversight and do not reliably handle the full serving-and-collection workflow. No mature production system performs this task end-to-end without human intervention across diverse care settings.
Technical feasibility todayclaude-sonnet-51/5No widely deployed product autonomously serves and collects patient food trays reliably; hospital delivery robots remain pilot-stage and require human staff for room entry, tray handling, and patient interaction.

Separate collected materials for disposal, recycling, or reuse, in accordance with environmental policies.

20

CI 10–30 · exposure 13 · augmentation 13 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Healthcare and institutional waste management remain largely manual and low-digitization sectors. Adoption of autonomous sorting is concentrated in industrial recycling and is rare in orderly-heavy settings like hospitals where waste streams are highly mixed and policy-sensitive.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/janitorial functions are low-digitization, physically embodied work with minimal AI/robotics adoption in production settings currently.
Augmentation potentialclaude-haiku-4-5-202510012/5Current AI offers limited assistance; basic computer vision for material identification could help, but the physical manipulation, policy compliance, and real-time decision-making remain human-dependent. AI augmentation potential is modest for this task.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no meaningful assistance for the physical act of separating and disposing of collected materials.
Task automatabilityclaude-haiku-4-5-202510012/5Material separation requires visual identification, sorting into multiple categories, and compliance with context-specific policies. While computer vision can identify some materials, the heterogeneity of waste streams, policy variations, and need for reliable categorization make full end-to-end automation with 50% time savings infeasible with current systems.
Task automatabilityclaude-sonnet-51/5This is a physical sorting task requiring manipulation of waste materials, bins, and biohazardous items in a hospital setting, which current AI cannot perform end-to-end without robotic embodiment.
Adoption barriersclaude-haiku-4-5-202510013/5Material handling automation faces moderate barriers: facility design constraints, variability in waste composition, and some regulatory oversight of waste handling. However, no strict licensing requirement binds the task to a human, and economic viability is the primary constraint.
Adoption barriersclaude-sonnet-53/5Biohazard and medical waste handling in hospitals is subject to environmental and safety regulations, and physical presence is required, though the task itself isn't inherently a licensed-professional function.
Cost vs. human wageclaude-haiku-4-5-202510012/5Robotic sorting systems and computer vision solutions for waste separation remain capital-intensive and require significant integration and maintenance, making per-task costs comparable to or exceeding orderly wages, especially in small or mid-sized facilities.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI-driven substitute for this physical task, so any hypothetical automation (specialized robotics) would be far more costly than human labor today.
Technical feasibility todayclaude-haiku-4-5-202510012/5No deployed systems reliably perform autonomous waste sorting across diverse material types and facility policies at scale. Research prototypes exist, but production deployments are rare and typically limited to high-volume homogeneous streams (e.g., cardboard), not the mixed-material separation orderlies handle.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs physical waste sorting and disposal in healthcare facilities; robotic waste sorting exists only in narrow industrial recycling contexts, not hospital orderly work.

Carry messages or documents between departments.

18

CI 10–26 · exposure 8 · augmentation 13 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Healthcare settings have been slow to adopt autonomous delivery robots at scale; most adoption remains in pilot projects or isolated high-tech facilities. The task is embedded in low-digitization, physical-presence-dependent work where organizational change is gradual.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/facilities roles show low AI adoption for physical logistics tasks; hospitals adopt AI mainly in clinical decision support and administrative software, not physical courier replacement.
Augmentation potentialclaude-haiku-4-5-202510012/5Digital message platforms and tracking systems can assist with some coordination, but they do not meaningfully augment an orderly who still must physically walk and deliver items. Augmentation potential is limited because the core task is fundamentally manual and spatial.
Augmentation potentialclaude-sonnet-51/5AI offers minimal assistance to the physical act of carrying items between departments; digital messaging systems could reduce need for physical carrying but that's substitution of the task, not augmentation of the orderly performing it.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical navigation through buildings and delivery of physical items (documents, messages), which current AI systems cannot perform without specialized robotics. While document digitization could reduce the task's frequency, the core physical act of carrying and delivering remains outside the scope of general AI automation today.
Task automatabilityclaude-sonnet-52/5Physical carrying of documents between departments is a physical-world task that current AI (software-based) cannot perform without robotics; even where digitization is possible, the task as stated is physical transport, not automatable end-to-end today.
Adoption barriersclaude-haiku-4-5-202510013/5Physical security, human familiarity with in-person communication, and organizational preference for human presence in patient-facing areas create moderate friction. There are no strict licensing barriers to deployment of automated systems, but workflow integration and staff acceptance provide meaningful resistance.
Adoption barriersclaude-sonnet-52/5No licensing requirement for this specific task, but hospital workflows, chain-of-custody for medical documents, and physical infrastructure create moderate organizational friction against automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5The cost of deploying autonomous delivery robots (hardware, infrastructure, integration, maintenance) far exceeds the loaded wage of an orderly ($15–25/hour in most US healthcare settings). This task does not achieve the cost advantage needed for substitution.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI system performing physical message/document delivery cheaper than an orderly; robotic delivery systems exist in niche hospital settings but are capital-intensive and not a direct AI-inference cost comparison.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI product reliably performs physical document delivery between departments in real hospital or office environments. Autonomous delivery robots exist in research and narrow pilot settings, but are not production-standard in typical healthcare facilities where orderlies work.
Technical feasibility todayclaude-sonnet-51/5No deployed product has orderlies physically replaced by AI for inter-department document/message transport in hospitals; this remains a manual, human physical task.

Disinfect or sterilize equipment or supplies, using germicides or sterilizing equipment.

18

CI 5–30 · exposure 13 · augmentation 25 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Healthcare remains relatively slow in adopting disinfection automation due to regulatory burden, capital constraints in many facilities, and infection-control risk aversion; while large hospital systems are piloting automated systems, widespread production adoption remains limited.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/janitorial functions involving physical sterilization show minimal AI adoption; this is a low-digitization, physical-labor-dependent task in a sector that lags in automating manual hygiene work.
Augmentation potentialclaude-haiku-4-5-202510013/5AI-driven monitoring systems and scheduling optimization can assist orderlies by tracking sterilization cycles, flagging equipment due for disinfection, and ensuring compliance documentation, improving efficiency without removing human responsibility for final verification and handling.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no meaningful assistance for the physical act of disinfecting or sterilizing equipment using germicides.
Task automatabilityclaude-haiku-4-5-202510012/5While germicide application and sterilization equipment operation are mechanically simple, the task requires contextual judgment about what items need sterilization, proper handling of hazardous chemicals, and verification of sterile conditions—factors that prevent end-to-end automation from achieving consistent 50% time savings without substantial setup and oversight.
Task automatabilityclaude-sonnet-51/5This is a physical hands-on task requiring manipulation of equipment and supplies with germicides; no current AI system can perform the physical disinfection process end-to-end.
Adoption barriersclaude-haiku-4-5-202510014/5Regulatory requirements (FDA, CDC, OSHA) mandate strict protocols for sterilization verification and chain-of-custody documentation; healthcare facility liability for infection control failures creates strong institutional friction against full automation without human oversight and sign-off.
Adoption barriersclaude-sonnet-53/5Infection control protocols, hospital accreditation standards, and liability for improper sterilization create moderate procedural barriers, though the task itself isn't legally restricted to licensed professionals only.
Cost vs. human wageclaude-haiku-4-5-202510012/5Specialized sterilization equipment and germicides require ongoing chemical/energy costs and maintenance; the loaded cost of robots or automated systems capable of handling diverse hospital equipment remains substantially higher than the modest wage of orderlies performing this task.
Cost vs. human wageclaude-sonnet-51/5There is no AI-based substitute for this physical task, so comparing inference cost to human wage is not applicable; any robotic solution would require significant capital investment exceeding orderly wages.
Technical feasibility todayclaude-haiku-4-5-202510012/5Robotic systems for equipment disinfection exist in controlled laboratory and healthcare settings, but deployed solutions are limited to narrow, repetitive scenarios (e.g., UV chamber automation); general disinfection across varied equipment types and supply handling remains primarily manual in production healthcare environments.
Technical feasibility todayclaude-sonnet-51/5No deployed AI product performs equipment sterilization; existing automation in this space is limited to specialized robotic UV/hydrogen peroxide room disinfection systems, not general equipment/supply sterilization by orderlies.

Clean and sanitize patient rooms, bathrooms, examination rooms, or other patient areas.

15

CI 5–25 · exposure 13 · augmentation 25 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Healthcare is conservative in adopting autonomous cleaning automation; most deployments remain pilots or limited to after-hours, non-patient-contact scenarios. Widespread production adoption is rare relative to other sectors, reflecting regulatory caution and liability concerns.
Sector adoption velocityclaude-sonnet-51/5Healthcare facility housekeeping/janitorial functions are a low-digitization, physically-intensive sector with minimal AI/robotics adoption in production settings for full-room sanitation tasks.
Augmentation potentialclaude-haiku-4-5-202510012/5AI or robotics offer limited augmentation today; mobile disinfection robots can assist with UV or electrostatic spraying, but the orderly must still perform manual cleaning, inspection, and quality assurance. The human remains entirely in the loop and gains only narrow task support.
Augmentation potentialclaude-sonnet-52/5Some assistive tools exist (UV-C disinfection robots, sensor-based cleanliness verification) that can supplement human cleaning efforts, but they address only narrow sub-components rather than transforming the overall task.
Task automatabilityclaude-haiku-4-5-202510012/5Physical cleaning and sanitization require dexterous manipulation of tools, navigation of varied room layouts, and handling of biological hazards. Current robotics can perform limited repetitive cleaning in controlled environments, but cannot reliably handle the variability, obstacle avoidance, and quality assurance needed for patient rooms at 50% time savings with equal quality.
Task automatabilityclaude-sonnet-51/5Cleaning and sanitizing physical patient spaces requires physical manipulation of objects, surfaces, and equipment that current AI systems, including robots, cannot perform reliably or comprehensively across varied hospital environments.'
Adoption barriersclaude-haiku-4-5-202510014/5Healthcare facilities face regulatory requirements for infection control documentation, liability concerns around contamination failures, and strong institutional preference for human oversight of sanitation in patient areas. Many jurisdictions and healthcare protocols mandate human verification of sanitization standards.
Adoption barriersclaude-sonnet-54/5Infection control regulations, liability concerns for improperly sanitized patient areas, and the need for adaptable human judgment in varied contamination scenarios create strong practical barriers to full automation.
Cost vs. human wageclaude-haiku-4-5-202510012/5Robotic cleaning systems cost tens of thousands of dollars with ongoing maintenance, integration, and training overhead. An orderly's loaded wage is typically $30–40k annually, making the capital and operational cost-per-task significantly higher than human labor in most settings.
Cost vs. human wageclaude-sonnet-51/5Specialized cleaning robots and hospital-grade disinfection systems are capital-intensive relative to the low wage of orderly labor, making the human currently cheaper for this multifaceted physical task.
Technical feasibility todayclaude-haiku-4-5-202510012/5A few robotic cleaning systems exist in research and limited pilot deployments (e.g., UV disinfection robots, floor-cleaning robots), but none performs the full end-to-end task reliably in production healthcare settings. Error rates in navigation, missed spots, and inability to adapt to clutter remain material barriers.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously cleans and sanitizes full patient rooms/bathrooms today; commercial cleaning robots exist for simple floor mopping/UV disinfection but not comprehensive room sanitation including surfaces, fixtures, and biohazard handling.

Change soiled linens, such as bed linens, drapes, or cubicle curtains.

14

CI 5–24 · exposure 8 · augmentation 13 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare organizations have shown minimal adoption of autonomous systems for this task; the sector remains highly manual and conservative due to regulatory constraints, infection control concerns, and the physical nature of the work.
Sector adoption velocityclaude-sonnet-51/5Healthcare support and janitorial-type physical tasks show minimal AI/robotics adoption; this is a manual, low-digitization task with no meaningful automation trend.
Augmentation potentialclaude-haiku-4-5-202510012/5AI/robots offer minimal assistance to a human orderly performing this task; the core work is physical manipulation of contaminated textiles, where current technology cannot meaningfully amplify human productivity without replacing the human entirely.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no assistance for the physical act of stripping and replacing linens, curtains, or drapes.
Task automatabilityclaude-haiku-4-5-202510012/5Changing soiled linens requires physical manipulation of fabric, removal of contaminated materials, and proper handling of biohazardous waste—capabilities that current robotics and AI systems cannot reliably perform end-to-end in varied hospital/clinical environments. Only narrow, highly structured scenarios with specialized hardware could approach 50% time savings.
Task automatabilityclaude-sonnet-51/5This requires physical manipulation of fabric in a hospital setting, bending, lifting patients or moving them safely, and handling contaminated materials—no current AI or robotic system can perform this dexterous, variable task end-to-end.
Adoption barriersclaude-haiku-4-5-202510014/5Healthcare environments have stringent infection control protocols, regulations (OSHA, CDC guidelines), and liability requirements that mandate proper handling of biohazardous materials; human oversight and certification are effectively required by law and institutional policy.
Adoption barriersclaude-sonnet-52/5No licensing requirement exists for this specific task, but infection control protocols, patient safety, and physical care standards create practical barriers to any automated substitute.
Cost vs. human wageclaude-haiku-4-5-202510011/5Specialized robotic systems capable of handling contaminated linens would require significant capital investment and maintenance, far exceeding the loaded wage of an orderly, with no mature cost-effective solution available.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute, so any theoretical automation would require expensive custom robotics far exceeding the cost of a low-wage human worker.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed commercial products reliably perform this task autonomously in production healthcare settings. Experimental robotic arms exist but lack the dexterity, contamination-handling protocols, and adaptive control needed for real-world use at scale.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs autonomous linen-changing in clinical or institutional settings; this remains far beyond commercial robotics capability today.

Collect and transport infectious or hazardous waste in closed containers for sterilization or disposal, in accordance with applicable law, standards, or policies.

7

CI 0–14 · exposure 5 · augmentation 13 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare facilities operate as laggard sectors for automation in service roles due to regulatory scrutiny, liability concerns, and the entrenched use of human orderlies for waste transport. Adoption of autonomous systems for this task remains minimal in production.
Sector adoption velocityclaude-sonnet-51/5Healthcare support and janitorial-adjacent physical labor sectors show minimal AI/robotic adoption for hazardous material handling; this remains a low-digitization, physically demanding niche.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could assist via route optimization or real-time inventory tracking of waste containers, but the core task—identifying, handling, and physically transporting biohazardous materials—remains primarily dependent on human judgment and compliance verification.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no assistance to the physical act of collecting and transporting hazardous waste containers, though it might marginally help with compliance documentation.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical navigation of hospital/clinical environments, identifying and handling biohazard containers, and ensuring compliance with safety protocols. Current robots cannot reliably identify hazardous waste in real-world settings, navigate complex indoor environments safely, or meet liability requirements for pathogen handling.
Task automatabilityclaude-sonnet-51/5This is a physical manual task requiring picking up, transporting, and handling hazardous waste containers throughout a facility—no current AI system can perform this physical labor.
Adoption barriersclaude-haiku-4-5-202510015/5OSHA regulations, CDC guidelines, and state laws mandate specific handling, containment, and tracking of infectious waste, typically requiring human verification and legal accountability. Liability exposure for improper biohazard handling is severe, creating a near-absolute requirement for human oversight and sign-off.
Adoption barriersclaude-sonnet-54/5Handling infectious/hazardous waste is governed by strict regulatory, safety, and biohazard-handling standards, and requires trained personnel following legally mandated procedures, creating strong barriers to any automated substitution.
Cost vs. human wageclaude-haiku-4-5-202510012/5Specialized mobile robots capable of handling biohazardous material reliably remain expensive to procure, integrate, and maintain, while orderlies earn modest wages. The capital and oversight costs likely exceed the savings from automation for typical facilities.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI-driven alternative to compare costs against; a human orderly remains the only practical means of performing this physical transport task.
Technical feasibility todayclaude-haiku-4-5-202510012/5While some automated waste handling systems exist in controlled industrial settings, they operate in pre-engineered environments with standardized waste streams. Healthcare facilities lack deployed AI systems that can autonomously collect and sort infectious waste across the variability of clinical environments while maintaining regulatory compliance.
Technical feasibility todayclaude-sonnet-51/5No deployed AI product handles physical waste collection and transport; this remains entirely a human/robotics physical task that is not commercially solved.

Lift or assist others to lift patients to move them on or off beds, examination tables, surgical tables, or stretchers.

4

CI 0–7 · exposure 0 · augmentation 38 · importance 4.8/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5While mechanical patient lifts (non-AI) are common, AI-driven autonomous patient lifting adoption in hospitals remains negligible. Pilots exist but production deployment is rare due to safety concerns and regulatory hesitation.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/orderly roles involving physical patient transfer show minimal AI or robotic adoption; this remains a manual, low-digitization task.
Augmentation potentialclaude-haiku-4-5-202510013/5Exoskeleton technology and smart lift-assist devices can reduce strain on orderlies and provide real-time guidance, moderately boosting productivity and safety, though the human remains the primary agent performing the lift.
Augmentation potentialclaude-sonnet-52/5Mechanical lift aids and scheduling/coordination software can support the process, but AI itself offers little direct augmentation to the physical act of lifting patients.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical manipulation of human bodies in healthcare settings—moving patients safely requires real-time tactile feedback, balance assessment, and adaptive force control that current robots cannot reliably perform end-to-end. No AI system today can autonomously lift a patient with consistent safety and dignity.
Task automatabilityclaude-sonnet-51/5This is a physical patient-handling task requiring bodily strength, balance, and careful coordination with a human patient; no AI system can perform physical lifting or transfer of a person.
Adoption barriersclaude-haiku-4-5-202510015/5Healthcare liability is extremely high—injury to patients during automated lifting creates severe legal exposure, and most jurisdictions expect human supervision or direct human contact for patient safety. Regulatory bodies (OSHA, CMS) implicitly or explicitly require human judgment in patient handling.
Adoption barriersclaude-sonnet-54/5Patient safety, liability for injury, and clinical/physical-contact requirements create strong barriers against replacing humans in direct patient handling, though not a strict licensing requirement specific to orderlies.
Cost vs. human wageclaude-haiku-4-5-202510011/5Specialized lifting robots remain expensive (tens of thousands of dollars in capital, plus maintenance), while orderly labor is inexpensive. The all-in cost per lift episode remains well above human wage equivalents.
Cost vs. human wageclaude-sonnet-51/5There is no AI substitute for physical lifting, so any comparison would require robotics far more expensive and less reliable than human labor for this task today.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs full patient lifting autonomously in production healthcare settings. While research robots exist, they lack the dexterity, contextual awareness, and regulatory clearance for routine patient handling.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs manual patient lifting/transfer; mechanical lift devices exist but are tools operated by humans, not autonomous AI systems performing the task.

Transport patients to treatment units, testing units, operating rooms, or other areas, using wheelchairs, stretchers, or moveable beds.

3

CI 0–5 · 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 is a conservative, heavily regulated sector with slow digital adoption for autonomous systems. Patient safety concerns and liability exposure have kept automation of direct patient care tasks to minimal pilots.
Sector adoption velocityclaude-sonnet-51/5Healthcare support and physical patient-handling roles are among the slowest sectors for AI/robotic adoption due to safety, cost, and infrastructure constraints.
Augmentation potentialclaude-haiku-4-5-202510012/5AI offers limited assistance for this primarily physical task; some route-planning or scheduling support is possible, but the core transportation work remains fundamentally manual and requires human presence and judgment.
Augmentation potentialclaude-sonnet-52/5AI could assist with scheduling, routing, or coordination of patient transport, but offers minimal direct enhancement to the physical act of moving patients.
Task automatabilityclaude-haiku-4-5-202510011/5Physical transportation of patients using wheelchairs, stretchers, or moveable beds requires autonomous mobility in unpredictable hospital environments, real-time patient interaction, and physical manipulation. Current AI systems cannot reliably perform this end-to-end task.
Task automatabilityclaude-sonnet-51/5Physically transporting patients requires manual handling, navigation of hospital environments, and physical presence; no current AI system can perform this end-to-end without a robotic embodiment, which is not deployed at scale.
Adoption barriersclaude-haiku-4-5-202510015/5Hospital regulations, patient safety liability, accreditation requirements, and the need for human judgment in responding to patient needs (comfort, medical emergencies, communication) create hard barriers to full automation of patient transport.
Adoption barriersclaude-sonnet-54/5Patient safety, liability for falls or medical incidents during transport, and the need for human judgment in emergencies create strong organizational and regulatory friction against automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Autonomous patient transport systems remain prohibitively expensive (hardware, maintenance, integration, safety oversight) compared to the relatively low-cost labor of orderlies in most healthcare settings.
Cost vs. human wageclaude-sonnet-51/5Any robotic solution capable of this task would require expensive specialized hardware, safety systems, and maintenance, making it more costly than employing an orderly today.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product performs hospital patient transport at scale today. While autonomous transport robots exist in research settings, they lack the reliability, safety certification, and real-world hospital integration needed for production use with vulnerable patients.
Technical feasibility todayclaude-sonnet-51/5While experimental autonomous hospital robots exist in research and limited pilots, no mature product reliably transports patients using wheelchairs, stretchers, or beds in production at scale.

Provide physical support to patients to assist them to perform daily living activities, such as getting out of bed, bathing, dressing, using the toilet, standing, walking, or exercising.

3

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

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare sectors are digitization-laggards for physical care tasks; robot pilots remain extremely rare in production; no measurable displacement of orderlies has occurred, and adoption is limited to small research or premium facilities.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/direct care work is a low-digitization, physical-labor sector with minimal AI/robotic adoption for hands-on patient assistance.
Augmentation potentialclaude-haiku-4-5-202510012/5Current technology offers minimal real augmentation for the core physical assistance task; exoskeletons or lifting aids could reduce orderly strain, but they do not materially amplify the orderly's ability to provide safe, dignified patient assistance in the varied contexts described.
Augmentation potentialclaude-sonnet-52/5AI can assist with scheduling, monitoring, or fall-detection alerts, but offers minimal augmentation to the core physical support task itself.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical manipulation of the human body in variable, safety-critical contexts (transfer, balance, mobility assistance). Current robotics cannot reliably handle the dexterity, force control, and adaptive responsiveness needed to safely assist patients with diverse physical limitations, nor can they operate in unstructured home or clinical environments at scale.
Task automatabilityclaude-sonnet-51/5This requires hands-on physical assistance and manipulation of human bodies, which current AI systems (software-based) cannot perform; even advanced robotics are not deployed for this at scale.
Adoption barriersclaude-haiku-4-5-202510015/5Patients require direct human contact for dignity, consent, and safety; liability is severe if a robot injures a vulnerable person; regulatory oversight of autonomous patient care is strict; organizational resistance and patient/family preference for human caregivers create strong adoption friction.
Adoption barriersclaude-sonnet-54/5Direct physical care involves safety, liability, and often regulatory/certification requirements for handling patients, creating strong barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Humanoid or specialized patient-assistance robots remain extremely expensive (hundreds of thousands of dollars per unit), with high maintenance costs, while orderlies earn modest wages; the all-in cost per patient-interaction is far above human labor.
Cost vs. human wageclaude-sonnet-51/5Physical assistive robotics are far more expensive than orderly wages when including hardware, maintenance, and safety oversight, with no viable AI-only substitute.
Technical feasibility todayclaude-haiku-4-5-202510011/5While assistive robots exist in research and limited pilot deployments, no mature production systems reliably perform the full range of physical assistance tasks (bathing, dressing, toileting, safe transfers) with the adaptability and safety margins required in real clinical or home settings today.
Technical feasibility todayclaude-sonnet-51/5No deployed products provide physical patient handling and mobility assistance; humanoid/assistive robots for this remain research or pilot stage.

Turn or reposition bedridden patients, alone or with assistance, to prevent bedsores.

3

CI 0–5 · 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 remains a laggard in task automation due to regulatory constraints, patient safety concerns, and high liability risk. Even in advanced hospital systems, patient repositioning is still predominantly manual labor with minimal AI agent deployment.
Sector adoption velocityclaude-sonnet-51/5Long-term care and hospital support staff roles involving physical patient handling show minimal AI/robotic adoption; this remains a highly manual, low-digitization function.
Augmentation potentialclaude-haiku-4-5-202510012/5AI can provide minor assistance through alerts or reminders about repositioning schedules, but offers limited augmentation of the physical task itself. Exoskeleton or lifting-aid technology could assist human workers, but current AI does not substantially enhance productivity on the core repositioning activity.
Augmentation potentialclaude-sonnet-52/5Sensor-based alerts or scheduling reminders (e.g., turning schedules) can support orderlies, but the physical repositioning itself receives negligible AI augmentation beyond basic reminder systems.
Task automatabilityclaude-haiku-4-5-202510011/5Turning and repositioning bedridden patients requires physical manipulation of a human body in a medical context, demanding real-time adjustment to patient comfort, safety, and medical conditions. Current AI systems lack embodied robotics capable of reliable, safe patient handling at scale.
Task automatabilityclaude-sonnet-51/5This requires direct physical manipulation of a vulnerable patient's body, a manual task with no software or robotic system able to safely perform it today.
Adoption barriersclaude-haiku-4-5-202510015/5Patient safety, liability, and direct physical contact with vulnerable individuals create hard barriers. Healthcare regulations and duty-of-care standards require human oversight and accountability; automation of patient handling faces significant regulatory and organizational friction.
Adoption barriersclaude-sonnet-54/5Direct physical care of bedridden patients carries high liability for injury (e.g., skin tears, falls, pressure injury litigation) and typically requires trained staff, though not always a licensed professional specifically.
Cost vs. human wageclaude-haiku-4-5-202510011/5Specialized medical robotics for patient handling remain prohibitively expensive (six figures to millions), far exceeding the loaded wage of orderlies performing this task. Integration and maintenance costs compound the economic barrier.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical task, so any hypothetical robotic solution would be far more costly than an orderly's wage given current robotics costs and safety requirements.
Technical feasibility todayclaude-haiku-4-5-202510011/5While specialized patient-handling robots exist in research and limited pilots, no deployed products perform full repositioning tasks reliably in standard hospital or care settings. Existing systems lack the dexterity, contextual judgment, and safety assurance required for independent patient care.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs autonomous patient repositioning in real care settings; assistive lift devices exist but require full human operation and judgment.

Position or hold patients in position for surgical preparation.

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 settings are conservative adopters of automation in direct patient care, particularly for tasks requiring physical contact and in high-stakes surgical environments where human expertise is deeply embedded.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/physical patient-handling roles show minimal AI or robotic adoption; this is a low-digitization, high-touch physical task with no meaningful automation trend.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could provide guidance (e.g., anatomical references or positioning checklists) to assist an orderly, but the task is primarily physical execution where current AI offers minimal productivity enhancement.
Augmentation potentialclaude-sonnet-51/5AI offers no meaningful assistance for the physical act of positioning or holding a patient in place during surgical prep.
Task automatabilityclaude-haiku-4-5-202510011/5Positioning patients for surgery requires physical manipulation of potentially unconscious or immobilized bodies in sterile environments—a task that demands dexterity, force control, and real-time adaptation to patient anatomy. Current AI systems cannot perform this end-to-end; robotic arms exist but are not deployed for this specific surgical prep work.
Task automatabilityclaude-sonnet-51/5This is a physical manipulation task requiring hands-on positioning of a patient's body, which current AI systems and robots cannot perform safely or reliably outside narrow research contexts.,
Adoption barriersclaude-haiku-4-5-202510015/5Patient positioning in surgical contexts involves direct patient contact and safety-critical physical manipulation; regulatory and clinical protocols require trained human staff to perform or directly supervise this task, and liability for incorrect positioning falls on medical staff.
Adoption barriersclaude-sonnet-54/5Patient safety, sterile field protocols, and liability concerns mean this must be performed by trained staff under clinical supervision, creating strong organizational and safety barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5The cost of specialized robotics, integration, maintenance, and oversight would far exceed the loaded wage of an orderly. Current systems are not economically viable for this task.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this task, so any hypothetical automation would require expensive specialized robotics far costlier than an orderly's wage.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs patient positioning for surgery today. While surgical robots exist for other tasks, positioning patients remains a manual skill performed by trained orderlies in all operating rooms.
Technical feasibility todayclaude-sonnet-51/5No deployed products position or physically hold patients for surgical preparation; this remains entirely a human physical task in clinical settings.

Answer patient call signals, signal lights, bells, or intercom systems to determine patients' needs.

3

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

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare facilities remain heavily dependent on human orderlies for immediate, in-person patient response. Adoption of AI in this role is minimal due to regulatory, safety, and patient-contact requirements.
Sector adoption velocityclaude-sonnet-51/5Healthcare support/orderly work is a physical, low-digitization role with minimal AI-driven displacement in current adoption data.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could potentially assist by pre-filtering routine requests (e.g., predicting common needs), but the core task—responding to live signals and assessing patient needs—fundamentally depends on human presence and judgment, limiting meaningful augmentation.
Augmentation potentialclaude-sonnet-52/5Smart call systems and triage software can help prioritize or route calls, but they offer only marginal assistance to the core physical task of responding to and helping patients.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires real-time physical presence in a healthcare facility and direct engagement with patients to assess needs based on contextual cues. Current AI systems cannot monitor physical signals or respond in-person without human intermediaries, making full end-to-end automation infeasible.
Task automatabilityclaude-sonnet-51/5This requires physical presence to respond to a patient's call, assess their need, and often provide physical assistance—no current AI system can perform the end-to-end physical response.
Adoption barriersclaude-haiku-4-5-202510015/5Healthcare regulations and patient safety protocols typically require licensed or trained human staff to respond to patient calls and assess needs. Patients also have strong preference for human contact, and liability concerns around missed or misinterpreted calls create hard barriers to automation.
Adoption barriersclaude-sonnet-54/5Direct patient contact, safety liability, and the need for physical intervention (moving patients, checking vitals) create strong practical barriers even though not always strictly licensed for orderlies.
Cost vs. human wageclaude-haiku-4-5-202510011/5The task involves human presence, responsiveness, and judgment; any AI augmentation would still require a human orderly to be available on-site, making the all-in cost comparable to or higher than the human labor cost.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical task, so AI cost is effectively infinite relative to the human orderly's wage for this specific action.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI system can independently monitor call signals, physically respond to patients, and determine their needs without human staff present. This requires embodied presence in healthcare facilities that no production system provides.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously responds to hospital call lights and performs the physical patient care actions required; this remains firmly in the human domain.

Transport bodies to the morgue.

3

CI 0–5 · exposure 0 · augmentation 13 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Healthcare and morgue facilities operate in heavily regulated, low-automation sectors with strong organizational and legal reasons to retain human oversight of this sensitive process.
Sector adoption velocityclaude-sonnet-51/5Hospital support and physical logistics roles show minimal AI/robotic adoption; this remains a manual, low-digitization task with no measurable displacement trend.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could marginally assist by managing route optimization or documentation workflows, but the core physical and custodial aspects of body transport offer limited augmentation value and are not candidates for AI assistance.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no assistance to the physical act of transporting a body; there is no meaningful software or robotic augmentation applicable to this specific task.
Task automatabilityclaude-haiku-4-5-202510011/5Transporting bodies to the morgue requires physical manipulation in sensitive, regulated environments with strict handling protocols and dignity considerations that current autonomous systems cannot reliably manage end-to-end.
Task automatabilityclaude-sonnet-51/5This is a physical task requiring lifting, transporting, and handling a body via wheelchair, gurney, or stretcher through a hospital, which current AI systems cannot perform without embodied robotics far beyond deployed capability.
Adoption barriersclaude-haiku-4-5-202510015/5This task involves legal custody of human remains, strict chain-of-custody requirements, regulatory compliance, and societal expectations that a licensed human be responsible for handling deceased individuals with appropriate care and documentation.
Adoption barriersclaude-sonnet-54/5Handling of deceased bodies involves dignity, chain-of-custody, infection control, and institutional protocols that create strong organizational and ethical barriers to non-human handling, though not a strict licensing requirement.
Cost vs. human wageclaude-haiku-4-5-202510011/5A human orderly performing this task costs far less than building, maintaining, and insuring specialized robotics to handle bodies in medical/morgue settings, making automation economically unfeasible.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this task, so any hypothetical automation would require expensive specialized robotics far exceeding the cost of a human orderly.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI system can autonomously transport human remains to a morgue; this task remains entirely manual and would face severe legal, ethical, and operational barriers to automation.
Technical feasibility todayclaude-sonnet-51/5No deployed product moves human remains through hospital corridors to a morgue; this remains outside the scope of any commercial robotics or AI system in production.

Respond to emergency situations, such as emergency medical calls, security calls, or fire alarms.

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-4-5-202510011/5Emergency response occurs in healthcare, fire, and security sectors that remain heavily dependent on human workers. Adoption of AI for actual emergency response (rather than dispatch aids) is minimal, and organizational and regulatory structures reinforce human-led response.
Sector adoption velocityclaude-sonnet-51/5Healthcare facility support roles involving physical emergency response show minimal AI adoption; this remains a low-digitization, physical-labor context.
Augmentation potentialclaude-haiku-4-5-202510012/5AI can assist with dispatch optimization or preliminary triage flagging, but during the emergency response itself, AI provides minimal real-time assistance to orderlies actually attending to patients or scenes. Augmentation is limited to pre-response planning rather than in-the-moment support.
Augmentation potentialclaude-sonnet-52/5AI can assist with alerting, triage suggestions, or dispatch coordination, but offers little augmentation to the core physical act of responding to an emergency.
Task automatabilityclaude-haiku-4-5-202510011/5Responding to emergency situations requires real-time physical presence, situational judgment under uncertainty, and rapid coordination with human teams—capabilities far beyond current AI systems. Emergency response fundamentally depends on embodied action and human decision-making that cannot be fully automated today.
Task automatabilityclaude-sonnet-51/5Emergency response requires physical presence, rapid physical intervention, and situational judgment that current AI cannot perform end-to-end; no time-saving substitution is feasible.
Adoption barriersclaude-haiku-4-5-202510015/5Emergency response is heavily regulated and typically requires licensed or certified personnel. Legal, liability, and duty-of-care requirements mandate that a human be physically present and accountable, creating hard legal barriers to automation.
Adoption barriersclaude-sonnet-55/5Emergency response involves safety-critical, often licensed or trained personnel, liability concerns, and immediate physical/human-contact requirements that make automation infeasible and heavily regulated.
Cost vs. human wageclaude-haiku-4-5-202510011/5Current AI systems cannot perform emergency response at any cost-effective level because they cannot physically respond or assume the liability. The cost of AI-assisted dispatch is negligible compared to the irreplaceable cost of human responders.
Cost vs. human wageclaude-sonnet-51/5There is no AI system that can substitute for a human physically responding to an emergency, so cost comparison favors the human by default.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI product reliably performs emergency response end-to-end. While AI can support triage or dispatch via algorithms, the actual response—attending to patients, securing scenes, coordinating evacuation—requires human orderlies and cannot be replaced by current systems.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously responds to medical, security, or fire emergencies by physically acting; this remains entirely a human physical-response task.

Restrain patients to prevent violence or injury or to assist physicians or nurses to administer treatments.

0

CI 0–0 · exposure 0 · 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 sectors have been slow to automate patient care tasks involving direct physical contact or restraint, reflecting regulatory constraints and ethical concerns. Adoption remains negligible due to regulatory and liability barriers rather than technical limitations.
Sector adoption velocityclaude-sonnet-51/5Healthcare direct-care physical tasks show minimal robotic or AI adoption; this is a low-digitization, hands-on task with no meaningful automation trend.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could potentially assist with monitoring patient behavior or alerting staff to escalation risks, but augmentation is minimal because the core task requires immediate physical intervention where human judgment and presence are irreplaceable.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no assistance to the physical act of restraining a patient, though it might help with documentation or protocol reminders unrelated to the core task.
Task automatabilityclaude-haiku-4-5-202510011/5This task involves physical restraint of patients and requires real-time assessment of patient safety, de-escalation judgment, and precise physical intervention that current AI systems cannot perform. The task is inherently embodied and interactive, requiring immediate responsive action that no deployed AI system can execute reliably.
Task automatabilityclaude-sonnet-51/5Physically restraining a person requires bodily strength, real-time force judgment, and physical presence that no current AI system or robot can provide safely or reliably.'
Adoption barriersclaude-haiku-4-5-202510015/5This task is deeply regulated and requires licensed healthcare personnel. Patient safety law, liability, licensing of orderlies, and the inherent requirement for human judgment and physical presence in patient care create hard legal and ethical barriers to automation.
Adoption barriersclaude-sonnet-55/5Physical restraint involves legal liability, safety regulations, and required trained human judgment/authorization, making it a hard barrier against automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Deploying robotic systems or autonomous restraint mechanisms would be substantially more expensive than the loaded wage of an orderly, and would introduce unacceptable liability and safety risks. The capital and maintenance costs far exceed current human labor costs.
Cost vs. human wageclaude-sonnet-51/5There is no AI substitute performing this physical action, 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 AI product can physically restrain patients or independently execute this task. While monitoring systems and alerts exist, they do not perform the core restraint function itself, which requires licensed human workers in healthcare settings.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs physical patient restraint; this remains entirely a human physical task in clinical settings.

Related occupations — Healthcare Support

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.