Mechanical Door Repairers

49-9011.00

Median wage $55,720/yr27,120 employed (US)Rank #765 of 923 scored · top 83% by substitution

Install, service, or repair automatic door mechanisms and hydraulic doors. Includes garage door mechanics.

Sub-scores

0–100 · band = confidence interval from rater disagreement

Substitution16

Exposure9

Augmentation27

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

25 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

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%10

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

Technical feasibility todayw 20%8

panel mean rating 1.3/5 → substitution pressure 8/100

Cost vs. human wagew 15%8

panel mean rating 1.3/5 → substitution pressure 8/100

Adoption barriersw 20%inverted — strong barriers lower the score47

panel mean rating 3.1/5 (barrier strength) → substitution pressure 47/100

Sector adoption velocityw 10%4

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

Task breakdown (25 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.

Complete required paperwork, such as work orders, according to services performed or required.

CI 44–70 · exposure 58 · augmentation 75 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Field service automation is growing, but mechanical repair and maintenance remain relatively small, fragmented sectors with many independent or small-firm operators still using paper or basic digital systems; large-scale AI-driven form automation in this vertical is still emerging.
Sector adoption velocity	claude-sonnet-5	2/5	Field service and skilled trades sectors are slower adopters of AI tools generally, with paperwork automation present in some FSM platforms but not widespread among small door-repair businesses.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI-powered form assist (auto-populate fields from job data, suggest service codes, flag missing information) significantly reduces cognitive load and time for technicians and office staff, allowing faster paperwork turnaround while the human retains review and sign-off control.
Augmentation potential	claude-sonnet-5	4/5	Voice-to-text and auto-fill templates meaningfully speed up documentation for technicians while they remain responsible for accuracy and final review.
Task automatability	claude-haiku-4-5-20251001	3/5	AI can partially automate paperwork completion by extracting service details from technician notes and populating structured forms (work orders, service descriptions), but human judgment is typically required to verify accuracy, determine billing codes, and handle edge cases or special circumstances.
Task automatability	claude-sonnet-5	4/5	Filling out standardized work orders based on service details is largely a structured data-entry and summarization task that current AI (voice-to-text, mobile forms, LLM drafting) can handle with significant time savings, though field verification and edge cases still need human input.
Adoption barriers	claude-haiku-4-5-20251001	3/5	Paperwork serves legal and contractual purposes (warranty, billing, compliance); many organizations require human sign-off or technician verification for liability reasons, and regulatory requirements around service documentation create friction even if AI could fill forms accurately.
Adoption barriers	claude-sonnet-5	1/5	Paperwork completion is purely administrative with no licensing or liability requirement forcing a human to author it personally.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	While AI reduces time per form, the cost of integration, API connections to work management systems, and mandatory human review for accuracy and compliance makes the all-in cost competitive with but not clearly cheaper than a technician spending 5–10 minutes completing paperwork themselves.
Cost vs. human wage	claude-sonnet-5	4/5	Mobile dictation/transcription and templated form-filling tools are cheap per use compared to a technician's loaded wage spent manually writing paperwork, though some integration and review overhead remains.
Technical feasibility today	claude-haiku-4-5-20251001	3/5	Document automation and form-filling tools exist and are used in some field service contexts, but they often require manual review, integration with legacy systems varies, and error rates on complex multi-field documents remain material enough that most organizations still rely on human completion or heavy oversight.
Technical feasibility today	claude-sonnet-5	3/5	Field service management software with AI-assisted note-taking, dictation, and auto-population of work orders exists and is used by some trades, but not universally deployed for mechanical door repairers specifically and error correction is still common.

Order replacement springs, sections, or slats.

CI 30–66 · exposure 45 · augmentation 63 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Door repair is a traditional skilled trade with limited digital maturity; small, local repair shops dominate the sector and lack the IT infrastructure or vendor integration needed for meaningful automation adoption.
Sector adoption velocity	claude-sonnet-5	2/5	Mechanical door repair is a small-scale, low-digitization trade sector where AI adoption for back-office tasks like ordering is still nascent compared to information/finance sectors.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI-assisted inventory lookup, automated part recommendations based on door type, and supplier comparison could meaningfully speed up technician ordering decisions while the human retains responsibility for final selection and supplier contact.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist by tracking inventory, predicting needed parts, and auto-generating orders, reducing manual lookup and paperwork for the technician.
Task automatability	claude-haiku-4-5-20251001	2/5	Ordering parts requires identifying correct specifications, finding suppliers, and placing orders—tasks that AI could partially automate with inventory system access, but real-world variability in door models, supplier systems, and decision-making about part sourcing makes full end-to-end automation without human oversight unrealistic today.
Task automatability	claude-sonnet-5	4/5	Ordering parts is a structured procurement task (identifying part numbers, quantities, submitting orders) that AI systems integrated with inventory/ordering software can largely handle end-to-end today.
Adoption barriers	claude-haiku-4-5-20251001	3/5	No legal licensing requirement to order parts, but organizational friction exists: technicians need to verify part compatibility and supplier relationships are often relationship-driven rather than fully automated; some customers prefer direct technician contact for warranty and liability clarity.
Adoption barriers	claude-sonnet-5	1/5	No licensing, liability, or regulatory barrier prevents automating a parts-ordering task; it's a routine administrative function.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	The task is relatively low-cost labor (quick routine ordering) and would require integration with multiple supplier systems and inventory databases; the integration and maintenance overhead likely exceeds savings from automating this narrow task.
Cost vs. human wage	claude-sonnet-5	3/5	AI-driven ordering systems can be cheap per transaction, but small repair businesses often lack the integration/setup investment, making the realistic cost comparable to a technician spending a few minutes on the phone or website.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While e-commerce systems and basic procurement tools exist, no deployed AI product reliably handles the diagnosis-to-order workflow for specialized door parts at scale; most orders still require manual specification and supplier contact by trained technicians.
Technical feasibility today	claude-sonnet-5	3/5	Procurement automation and AI-assisted inventory reordering tools exist and are used in some maintenance/supply-chain contexts, but many small door-repair businesses still order parts manually via phone or supplier portals without AI integration.

Collect payment upon job completion.

CI 25–64 · exposure 42 · augmentation 63 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Field service adoption of automated payment collection remains slow; most door repair and HVAC firms still rely on technician cash/card handling or post-visit invoicing rather than autonomous AI systems. Pilot projects are uncommon in this sector.
Sector adoption velocity	claude-sonnet-5	3/5	Field service and trades businesses have moderately adopted digital payment tools, though adoption is slower than in fully digital sectors like finance or information services.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by generating invoices, tracking payment status, suggesting payment terms, and flagging unpaid accounts, meaningfully improving administrative efficiency while the technician retains control over the actual transaction and customer communication.
Augmentation potential	claude-sonnet-5	4/5	Digital invoicing and payment apps significantly speed up and simplify the payment collection process for the technician, even though a human still initiates and confirms the transaction.
Task automatability	claude-haiku-4-5-20251001	2/5	Payment collection involves conditional logic (invoice verification, payment method selection), but typically requires human judgment about customer disputes, payment plan negotiation, or security concerns. Current AI cannot reliably handle exceptions or complex customer interactions to achieve 50% time savings at equal quality.
Task automatability	claude-sonnet-5	3/5	Payment collection (invoicing, processing card/digital payment) can largely be handled by off-the-shelf payment apps and software, though the on-site interaction and final confirmation still involve a human presence.the physical handoff and customer trust element limit full automation.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Payment collection has regulatory barriers (PCI-DSS compliance for card processing, cash handling regulations), liability considerations around disputed or lost payments, and customer preference for human interaction during transaction completion. These create meaningful friction against full automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement to collect payment, but customer preference for a human presence and trust during in-person transactions creates some friction.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Integration of payment systems, fraud detection, and human oversight for dispute resolution makes the all-in cost of AI payment collection comparable to or potentially more expensive than a technician collecting payment directly during their visit.
Cost vs. human wage	claude-sonnet-5	4/5	Payment processing apps cost a small percentage transaction fee, far cheaper than dedicating human labor time solely to collecting payment.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While payment processing APIs exist, autonomous end-to-end collection on-site (handling cash, checks, cards, disputes) lacks reliable deployed products. Most systems require human intermediaries for security, verification, and exception handling in field service contexts.
Technical feasibility today	claude-sonnet-5	4/5	Mature mobile payment and invoicing products (Square, Stripe, QuickBooks) are widely deployed in field service industries today and reliably process payments at job completion.

Study blueprints and schematic diagrams to determine appropriate methods of installing or repairing automated door openers.

CI 23–33 · exposure 25 · augmentation 50 · importance 3.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a skilled trade concentrated in small local firms with limited digital transformation. The sector has low adoption of AI and continues to rely on technician expertise and experience rather than digital decision-support systems.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical door repair is a low-digitization, physical trade with minimal AI tool adoption in the field; blueprint-reading assistance tools are not yet common in this sector's workflows.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI tools could assist a technician by automatically extracting and organizing schematic data, highlighting relevant sections, or suggesting common repair patterns, thereby reducing time spent reviewing documentation. However, the core judgment remains human-dependent.
Augmentation potential	claude-sonnet-5	3/5	AI can help technicians quickly parse and summarize schematic diagrams or cross-reference manufacturer specs, offering moderate assistance while the technician still performs the physical planning and installation.
Task automatability	claude-haiku-4-5-20251001	2/5	AI can help analyze blueprints and suggest repair methods, but the task requires integrating spatial reasoning, equipment-specific knowledge, and safety considerations that vary by site. Current vision models can extract some schematic information, but they struggle with the nuanced judgment needed for repair method determination and cannot physically verify installations.
Task automatability	claude-sonnet-5	2/5	AI can help interpret blueprints and suggest methods, but the physical diagnosis, on-site verification, and decision-making tied to actual hardware still require a human to plan the job. Full end-to-end automation of this planning task isn't achievable with off-the-shelf tools today.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Safety-critical repairs on automated door systems often require licensed technicians, and liability for incorrect repair specifications falls on the certifying professional. Building codes, ADA compliance verification, and manufacturer requirements typically mandate human sign-off on repair determinations.
Adoption barriers	claude-sonnet-5	2/5	No formal licensing dictates who may interpret schematics, but liability for incorrect installation and the practical need for on-site judgment create moderate organizational friction against pure AI-driven planning.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	An AI system capable of reliable blueprint analysis and repair method determination would require significant setup, integration, and ongoing oversight by a technician. The cost of such a system, amortized per task, would likely be comparable to or exceed the loaded wage of a skilled door repairer performing this review independently.
Cost vs. human wage	claude-sonnet-5	2/5	Using AI to assist with blueprint interpretation requires added integration and human verification overhead, so cost savings versus a technician's own diagram-reading time are modest, not order-of-magnitude.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While OCR and schematic recognition tools exist, no deployed product reliably interprets blueprints and autonomously determines repair procedures for the full range of automated door opener systems in production use. Solutions are narrow, require human validation, and error rates remain material.
Technical feasibility today	claude-sonnet-5	2/5	Vision-language models can read schematics and answer questions about them, but no deployed product reliably interprets diverse door-opener blueprints and translates them into actionable repair/installation plans in production settings.

Set in and secure floor treadles for door-activating mechanisms, and connect power packs and electrical panelboards to treadles.

CI 5–36 · exposure 20 · augmentation 25 · importance 3.2/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a fragmented, small-firm, mostly on-site physical service sector with low digital infrastructure and slow AI adoption; no evidence of displacement through automation in production.
Sector adoption velocity	claude-sonnet-5	1/5	Building maintenance and door repair trades are a low-digitization, physical-labor sector with minimal AI or robotic adoption in field installation work.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist with diagnostics, schematics, or parts identification, but the core task is hands-on installation in variable field conditions where augmentation remains limited and human expertise still drives the work.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with diagnostics, wiring diagrams, or documentation, but offers little direct help with the physical act of setting treadles and connecting electrical components.
Task automatability	claude-haiku-4-5-20251001	3/5	AI could automate parts of this task such as documentation, circuit design verification, and parts ordering with significant setup, but physical installation—positioning treadles, securing fasteners, and making precise electrical connections—requires dexterous robotics not reliably deployed at scale in field settings today.
Task automatability	claude-sonnet-5	1/5	This is a physical installation and wiring task requiring precise manual manipulation, alignment, and electrical connection work in varied field conditions, which current AI systems cannot perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Electrical code compliance, building permits, and liability for safety-critical door mechanisms typically require a licensed electrician or mechanical contractor to perform or sign off, creating hard regulatory barriers to full automation.
Adoption barriers	claude-sonnet-5	3/5	While not formally licensed in most jurisdictions, electrical connection work often requires code compliance, safety certification, and liability considerations that favor qualified human technicians.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Current robotics and AI integration for on-site mechanical and electrical installation remains capital-intensive and labor-heavy in oversight, making total cost per installation comparable to or exceeding a skilled technician's loaded wage.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI-driven substitute for this physical task, so any AI-based approach would require expensive robotics far exceeding the cost of a human technician.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While vision systems can inspect installations and robotic arms exist in controlled factories, no mature product reliably performs end-to-end field installation of door mechanisms in varied building conditions at production scale. Research and early pilots dominate.
Technical feasibility today	claude-sonnet-5	1/5	No deployed robotic or AI product installs floor treadles or wires power packs/panelboards for door mechanisms in production settings; this remains firmly in the domain of skilled tradespeople.

Inspect job sites, assessing headroom, side room, or other conditions to determine appropriateness of door for a given location.

CI 5–30 · exposure 13 · augmentation 38 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Door repair and installation remains a fragmented, locally-operated, low-digitization sector with many small firms and strong reliance on experienced technicians; adoption of AI inspection tools has been minimal and largely experimental.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical door repair is a physical trade with low digitization and minimal AI adoption in the field for on-site assessments.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI-powered measurement tools (dimension estimation from images, building-code checklist reminders) could assist technicians by automating routine measurements and flagging obvious mismatches, while the human retains final judgment.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with reference lookups, measurement calculations, or documentation after data collection, but cannot meaningfully assist the core on-site physical assessment.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI could measure and classify headroom and side room via image analysis or sensor data, the task requires judgment about subtle spatial and structural conditions (e.g., architectural constraints, building codes, specific use cases) that demand physical presence and contextual interpretation beyond what current systems reliably handle end-to-end.
Task automatability	claude-sonnet-5	1/5	This requires physical presence at a job site to measure and assess spatial conditions, which current AI systems cannot perform end-to-end.'
Adoption barriers	claude-haiku-4-5-20251001	4/5	Door installation is typically part of licensed construction and architectural work; liability for incorrect placement could expose customers to safety and building-code violations, and many jurisdictions require a qualified human to certify appropriateness.
Adoption barriers	claude-sonnet-5	3/5	No licensing strictly requires a human, but physical presence, liability for incorrect assessments, and site-specific judgment create practical barriers to remote automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	The cost of deploying mobile robots or drones with sufficient sensor precision, integration, and human oversight to evaluate diverse job sites would likely exceed the loaded wage of a technician making a brief on-site visit.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this physical inspection task, so cost comparison favors the human by default.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Computer vision and depth sensors can detect dimensions, but no deployed product reliably assesses overall job-site appropriateness for door installation at production scale; systems exist for narrow measurement but not the holistic suitability determination this task demands.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product autonomously conducts physical site inspections and makes installation appropriateness judgments; this remains a human, on-site task.

Adjust doors to open or close with the correct amount of effort, or make simple adjustments to electric openers.

CI 5–24 · exposure 8 · augmentation 25 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Mechanical door repair is performed by small service firms with low digitization levels; adoption of AI-driven automation is negligible, and the work remains heavily human-centric with minimal sector-wide technology penetration.
Sector adoption velocity	claude-sonnet-5	1/5	Building maintenance and repair trades show minimal AI/robotic adoption; this is a low-digitization, physically-dependent sector.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist with diagnostics or work-order routing, but the core adjustment task leaves limited room for augmentation since the human must physically perform the calibration and testing on-site regardless.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with diagnostic checklists, documentation, or troubleshooting guides for electric openers, but offers little help with the physical adjustment itself.
Task automatability	claude-haiku-4-5-20251001	2/5	While some aspects (diagnostics, scheduling) could be automated, the core task requires physical manipulation of hardware and calibration that demands hands-on adjustment in situ—something current AI cannot do without a mobile robot platform, which remains rare and unreliable in real-world deployments.
Task automatability	claude-sonnet-5	1/5	This requires physical manipulation of hardware (springs, hinges, tracks, sensors) on-site, which current AI systems cannot perform without embodiment in capable robotics, far beyond off-the-shelf availability.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Licensing requirements (many jurisdictions require certified technicians for electric door openers) and safety/liability concerns around equipment adjustment create substantial legal and regulatory barriers to full automation without human sign-off.
Adoption barriers	claude-sonnet-5	2/5	No licensing typically required for basic door adjustment, though liability exists for commercial fire/safety door compliance in some jurisdictions, creating minor friction.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The task is inherently physical and site-specific, requiring a trained technician's labor; no AI solution can yet perform the work more cheaply than the human doing it, especially when factoring in integration and oversight costs.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this physical labor, so the comparison defaults to AI being effectively non-viable/more costly than a technician.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product performs this task end-to-end reliably; the physical adjustment and testing of door tension/opener mechanics requires on-site human technicians with specialized tools and judgment that AI systems cannot replicate in production today.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical door adjustment; this remains a manual trade task requiring hands-on tools and judgment at the installation site.

Prepare doors for hardware installation, such as drilling holes to install locks.

CI 5–24 · exposure 8 · augmentation 25 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair remains a traditional, small-firm, predominantly non-digitized trade with minimal automation adoption. The work is location-specific, involves heterogeneous door types, and occurs in dispersed service locations resistant to technological displacement.
Sector adoption velocity	claude-sonnet-5	1/5	The building trades and physical installation/repair sector show minimal AI or robotics adoption for hands-on tasks like this.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist with design guidance (e.g., recommending lock placement based on door type) or documentation, but the core physical task of preparation offers limited augmentation since human judgment and hands-on execution are inseparable from the work.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with measurement calculations, hardware spec lookup, or diagrams, but offers little help with the physical drilling and installation itself.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI could theoretically instruct on drilling specifications, the physical manipulation, precision alignment, and on-site assessment of door conditions require embodied robotics not yet reliably deployed. Current AI lacks the sensorimotor capability to consistently execute drilling operations at equal quality to skilled workers.
Task automatability	claude-sonnet-5	1/5	This is a precise physical manipulation task requiring positioning a door, measuring, and drilling accurately—no off-the-shelf AI system or robot can perform this end-to-end today.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Liability and safety concerns are high: misaligned locks or structural damage create customer injury and property damage risks. Building codes and installer guarantees often require certified professionals to perform or sign off on door preparation work.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement typically restricts this specific task, but physical dexterity, variable door materials/conditions, and on-site mobility needs create strong practical barriers to automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	AI systems capable of physical door preparation would require significant specialized robotics hardware, integration, and maintenance costs far exceeding the loaded wage of a skilled door repairer performing this task.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI/robotic alternative deployed at any scale, so any hypothetical automation would be far more costly than a technician with basic tools.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed commercial product reliably performs door preparation with hardware installation autonomously. This is a physical task requiring real-world manipulation and problem-solving that remains in research/prototype stages without production systems.
Technical feasibility today	claude-sonnet-5	1/5	No deployed commercial products perform mobile on-site door hardware installation; this remains firmly manual skilled trade work.

Wind large springs with upward motion of arm.

CI 10–15 · exposure 0 · augmentation 0 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a small, physically dispersed trade with low digitization and capital barriers to entry; adoption of specialized automation is minimal and unlikely.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical door repair is a low-digitization, physical trade sector with minimal AI or robotics adoption for manual tasks like this.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI provides no meaningful assistance to a technician winding a spring—the task is fundamentally manual and requires direct physical control with no digital component to augment.
Augmentation potential	claude-sonnet-5	1/5	AI offers essentially no assistance for the physical act of winding a spring; this is a purely manual, tactile skill with no digital or cognitive component to augment.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation in 3D space with precise force control and feedback—winding a large spring safely demands real-time adjustment to tension and hand positioning that current robots struggle with, and no AI system today can reliably perform this end-to-end.
Task automatability	claude-sonnet-5	1/5	This is a physical manipulation task requiring hand-arm dexterity, force application, and real-time tactile feedback while winding a spring under tension; no off-the-shelf AI system can perform this physical action today.'
Adoption barriers	claude-haiku-4-5-20251001	2/5	While there are no strict licensing barriers, the physical, safety-critical nature of the task and the need for contextual judgment create moderate friction to automation adoption.
Adoption barriers	claude-sonnet-5	3/5	While not licensed in most jurisdictions, this task involves significant injury risk (high-tension springs can cause severe harm), creating strong safety and liability-driven barriers to automation without specialized engineering.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	A robotic arm capable of safely winding large springs with proper tension control would be far more expensive to acquire, program, and maintain than the labor cost of a skilled door repair technician performing the task.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI-driven substitute for this physical task, so any hypothetical automation (e.g., custom robotics) would be far costlier than a human technician performing it directly.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI or robotic product reliably winds large springs in field conditions; this remains a manual task performed by trained technicians with no production-grade automation in use.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI or robotic product performs door spring winding in production; this remains a manual trade task performed by human repairers with specialized tools.

Lubricate door closer oil chambers, and pack spindles with leather washers.

CI 10–15 · exposure 0 · augmentation 0 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a trade-skill sector with low overall digitization, small firm dominance, and minimal reported automation adoption. This is characteristic of laggard sectors with limited AI/robotic deployment momentum.
Sector adoption velocity	claude-sonnet-5	1/5	Building maintenance and mechanical repair trades show minimal AI/robotics adoption for physical tasks like this, remaining a laggard sector for automation.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers minimal assistance for lubrication and packing tasks; the work is fundamentally manual and hands-on, with no obvious role for algorithmic support, data analysis, or decision-making that would augment human performance.
Augmentation potential	claude-sonnet-5	1/5	AI offers negligible assistance for the physical acts of lubricating chambers and packing spindles with washers, though it might help with scheduling or diagnostics elsewhere.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation of small, delicate components (leather washers, spindles) in confined spaces within mechanical door closers. Current AI and robotics lack the dexterity, sensorimotor feedback, and adaptability to reliably perform such precise mechanical assembly work at scale.
Task automatability	claude-sonnet-5	1/5	This is a hands-on physical maintenance task requiring manual dexterity to access, lubricate, and pack physical components; no current AI system can perform this manipulation.
Adoption barriers	claude-haiku-4-5-20251001	2/5	While there are no hard legal licensing barriers to automation, the task occurs primarily in small repair shops with low digitization, and customer preferences often favor human expertise for mechanical reliability. Organizational friction and capital constraints limit adoption drivers.
Adoption barriers	claude-sonnet-5	3/5	No licensing strictly requires a human, but physical access, tool manipulation, and liability for faulty door mechanisms create practical barriers to any automated substitute.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Specialized hardware (articulate robotic arms, vision systems, gripper tooling) capable of this task would cost tens of thousands of dollars, with significant integration overhead, far exceeding the loaded wage cost of a trained door repair technician for equivalent output.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute for this physical task, so AI cost is not comparable; a human technician with tools is the only viable option today.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product reliably performs lubrication and packing of door closer mechanisms at production scale. This is a specialized, hands-on task requiring tactile feedback and real-time problem-solving that exceeds current robotic capabilities in unstructured, varied equipment contexts.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical lubrication or gasket/washer packing on door hardware; this remains purely manual skilled trade work.

Remove or disassemble defective automatic mechanical door closers, using hand tools.

CI 10–15 · exposure 0 · augmentation 25 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a small, physically distributed, low-digitization service sector with aging workforces and minimal investment in automation; adoption of AI or robotics in this trade remains extremely limited.
Sector adoption velocity	claude-sonnet-5	1/5	Building maintenance and repair trades show minimal AI/robotics adoption for physical tasks like this; this is a low-digitization, manual trade sector.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could offer limited assistance via diagnostic guidance (identifying defect type from images or description) or procedure documentation lookup, but the core manual disassembly task offers minimal opportunity for meaningful human-AI collaboration or productivity enhancement.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with diagnostics, ordering parts, or providing repair manuals/guidance, but offers no direct help with the physical act of removing or disassembling the closer.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation of mechanical components in varied physical environments, precise hand-tool use, and real-time problem diagnosis. Current AI/robotic systems cannot reliably perform end-to-end disassembly of defective door closers with the dexterity, spatial reasoning, and adaptability this entails.
Task automatability	claude-sonnet-5	1/5	This is a physical manipulation task requiring hand tools, dexterity, and situational judgment to remove hardware; no current AI system can perform physical disassembly.rating This is purely a robotics/physical task, not something a language or vision model can execute.
Adoption barriers	claude-haiku-4-5-20251001	3/5	While no hard legal licensing requirement exists for door closer repair, customer preference for skilled human technicians, safety liability concerns around mechanical failure, and the need for on-site judgment and problem-solving create moderate organizational and market friction to automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing mandate requires a specific credentialed human for basic hardware removal, though safety and liability concerns around building hardware exist, but the primary barrier is physical/robotic capability, not regulatory.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost of a robotic system capable of field disassembly, plus integration and ongoing maintenance, far exceeds the loaded wage of a skilled door repairer who can handle the task with hand tools in a few hours.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI system capable of performing this physical task at all, so an all-in cost comparison favors the human by default since no AI substitute exists.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product reliably performs disassembly and removal of mechanical door closers in production settings. While robotic arms exist in controlled environments, field deployment for this task across diverse door configurations and defect types remains research-stage.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical door closer disassembly; this remains outside the scope of commercial AI products, which are digital/informational, not physical manipulators.

Repair or replace worn or broken door parts, using hand tools.

CI 5–15 · exposure 0 · augmentation 25 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is performed by small, dispersed service businesses with limited capital for investment in automation technology. The sector shows minimal AI/robotics adoption and remains heavily dependent on skilled human labor in local markets.
Sector adoption velocity	claude-sonnet-5	1/5	Building maintenance and repair trades are a low-digitization, physically-oriented sector with minimal AI/robotics adoption for hands-on repair work.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could potentially assist with diagnostics (identifying door problems from images or description) but offers minimal augmentation for the core physical repair work, which remains entirely dependent on human hands-on execution.
Augmentation potential	claude-sonnet-5	2/5	AI could help with diagnostics, parts lookup, or repair instructions via mobile apps, but offers minimal assistance to the actual physical repair process.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation of door hardware and structures in varied, unstructured environments. Current AI systems cannot operate in the physical world without specialized robotics, and general-purpose robotic manipulation remains far below the dexterity and problem-solving needed for on-site door repair.
Task automatability	claude-sonnet-5	1/5	This is a physical manipulation task requiring dexterity, mobility, and hand tool use in varied environments; no current AI system (including robotics) can perform this end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Repair work often occurs in residential and commercial properties where liability for property damage is high, customer preference for human technicians is strong, and safety concerns around unsupervised robotic operation create substantial friction against automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing typically required for this task, but physical presence, tool handling, and situational judgment on-site create practical barriers to any automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Hypothetical robotic systems capable of this work would require significant capital investment, custom integration, and maintenance costs that far exceed the labor cost of skilled technicians performing door repairs on-site.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI/robotic substitute performing this physical repair, so human labor remains the only cost-effective option.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed commercial product performs field door repair end-to-end. This is fundamentally a physical task requiring embodied robotics, which remains in early research stages rather than production deployment in the repair industry.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical door part repair/replacement; this remains far outside current robotic manipulation capabilities in unstructured environments.

Cut door stops or angle irons to fit openings.

CI 10–10 · exposure 0 · augmentation 25 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a traditional trade in small, localized service businesses with low digital integration and primarily physical, on-site work. Adoption of automation in this sector has historically been minimal.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical door repair is a low-digitization, physical trade sector with minimal AI/robotic adoption for hands-on fabrication tasks, and no evidence of production deployment in this niche.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could potentially assist with measurement guidance or cut specifications via mobile tools, but the core task of physically cutting and fitting materials offers limited augmentation value; the technician's judgment and hands-on skill remain central.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with calculating cut dimensions or generating cut lists from measurements, but offers little help with the physical act of cutting and fitting metal or wood components.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation of metal materials with precise measurements and hand-tool operation in an on-site context. Current AI systems cannot physically operate cutting tools or adapt to variable door opening specifications in real environments.
Task automatability	claude-sonnet-5	1/5	This is a physical, hands-on fabrication task requiring measurement, cutting tools, and physical dexterity at a specific job site; no AI system can perform the physical cutting or fitting.
Adoption barriers	claude-haiku-4-5-20251001	3/5	While the task itself has no strict licensing requirement, practical barriers exist: the need for on-site assessment, variable job conditions, and customer preference for a skilled human to ensure fit and quality in a service context.
Adoption barriers	claude-sonnet-5	3/5	No licensing typically required for this specific cutting task, but it occurs within a broader trade context requiring on-site physical presence, tool handling, and safety considerations that create natural friction against remote automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The cost of deploying a robotic system capable of this task—including measurement hardware, cutting tools, positioning mechanisms, and integration—would far exceed the loaded wage of a skilled door repair technician performing the work on-site.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI-based substitute for this physical cutting task, so any AI-equipped solution would require expensive robotics far exceeding the cost of a human tradesperson.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product can autonomously measure, position, and cut door stops or angle irons to fit specific openings. This remains a hands-on trade skill requiring physical presence and manual dexterity.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI or robotic product exists that reliably measures, cuts, and fits door stops or angle irons in field conditions; this remains firmly manual work.

Install dock seals, bumpers, or shelters.

CI 5–15 · exposure 0 · augmentation 25 · importance 3.4/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Mechanical door repair and dock equipment installation occur in small, geographically distributed firms with low digitization; these sectors show minimal AI adoption and remain primarily manual labor operations.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical door and dock equipment installation is a physical trade with very low digitization and no meaningful AI/robotic adoption trend in this sector.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could provide limited assistance via computer vision for pre-installation measurement or documentation, but offers minimal productivity boost for the core physical installation work that dominates this task.
Augmentation potential	claude-sonnet-5	2/5	AI could help with scheduling, parts ordering, or referencing installation manuals via a mobile assistant, but offers minimal assistance for the hands-on physical installation itself.
Task automatability	claude-haiku-4-5-20251001	1/5	Installing dock seals, bumpers, or shelters requires physical manipulation, precise positioning, and on-site assessment of loading dock geometry—tasks that current AI systems cannot perform end-to-end in the physical world without specialized robotics that are not yet deployed at scale.
Task automatability	claude-sonnet-5	1/5	This is a physical installation task requiring measuring, drilling, fastening, and manipulating heavy materials at a dock, which current AI systems cannot perform end-to-end; no software or vision system substitutes for the manual labor involved.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Installation work typically requires licensed tradespeople and on-site safety sign-offs, creating regulatory and liability barriers; customer preference for qualified human installers and warranty/insurance requirements further protect against automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing specifically restricts this to certified professionals in most jurisdictions, though safety codes and building/dock equipment standards create some procedural friction, and physical presence is inherently required.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	AI has no meaningful cost advantage here because the task is fundamentally physical—the human wage for specialized installation labor far exceeds any plausible AI infrastructure cost for a single task execution.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI system performing this physical installation task, so the AI cost is effectively infinite/nonexistent relative to a human tradesperson's wage.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No commercial AI product demonstrates reliable autonomous installation of dock equipment; this remains a physical labor task requiring human judgment, coordination, and on-site problem-solving that deployed AI systems cannot replicate.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI or robotic product installs dock seals, bumpers, or shelters in production; this remains purely manual skilled trade work with no commercial automation offering.

Cover treadles with carpeting or other floor covering materials, and test systems by operating treadles.

CI 5–15 · exposure 0 · augmentation 13 · importance 3.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a traditional trade performed by small, localized businesses with low digitization. Adoption of robotics in this sector is minimal and adoption velocity remains very slow.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical door repair is a low-digitization, physical trade sector with minimal AI/robotics adoption for hands-on installation tasks.
Augmentation potential	claude-haiku-4-5-20251001	2/5	While AI could assist with scheduling or documentation of treadle conditions, it offers minimal assistance for the core physical task of covering and testing systems on-site.
Augmentation potential	claude-sonnet-5	1/5	AI offers essentially no assistance for the physical acts of covering treadles or manually testing them by operation.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation of treadles, application of floor coverings with precise fit, and hands-on testing in a built environment. Current AI systems lack the embodied robotics and dexterity to perform the covering and testing end-to-end reliably.
Task automatability	claude-sonnet-5	1/5	This is a physical installation and manual testing task requiring hands-on manipulation of materials and mechanical treadle systems, which current AI cannot perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	The task inherently requires a licensed mechanical door repairer to inspect, test, and certify safe operation of door systems, creating both regulatory and liability barriers to full automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing requirement exists, but the physical dexterity and on-site manual nature of the task create practical barriers to any automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Performing this task would require expensive robotic systems, specialized hardware, and extensive setup—all substantially more costly than a skilled technician's labor on a per-task basis.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute, so the human remains the only cost-effective option for this physical task.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product performs this task in production. It requires specialized physical manipulation and environmental adaptation that exists only in research robotics labs, not commercial systems.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI or robotic product performs carpet covering and physical treadle testing in production; this remains purely manual work.

Bore or cut holes in flooring as required for installation, using hand or power tools.

CI 5–15 · exposure 0 · augmentation 25 · importance 2.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair and installation remains a craft trade with low digitization and limited robotic adoption. Small businesses and on-site work environments show minimal AI or robotic deployment compared to structured manufacturing.
Sector adoption velocity	claude-sonnet-5	1/5	Construction and building maintenance trades show very low AI/robotic adoption for physical on-site tasks, remaining a laggard sector for automation of manual fieldwork.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could potentially assist through measurement guidance, design layout visualization, or safety reminders, but current tools offer minimal practical augmentation for the core sensorimotor task of boring or cutting holes accurately in variable flooring conditions.
Augmentation potential	claude-sonnet-5	2/5	AI could help with measurement planning, layout guidance, or tool calibration via apps, but offers minimal direct assistance to the physical act of boring or cutting.
Task automatability	claude-haiku-4-5-20251001	1/5	Boring or cutting holes in flooring requires precise spatial navigation, real-time feedback, and adjustment in physical space. Current AI systems lack embodied manipulation capabilities and cannot autonomously operate hand or power tools on construction materials.
Task automatability	claude-sonnet-5	1/5	This is a physical manual task requiring precise tool manipulation on-site in varied environments; no current AI/robotic system can perform this end-to-end with time savings at equal quality.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Safety regulations, liability for property damage, structural integrity concerns, and the need for on-site judgment about floor composition and load-bearing requirements create strong barriers to autonomous automation. A skilled human must typically authorize and oversee such work.
Adoption barriers	claude-sonnet-5	2/5	No licensing specifically restricts this cutting task, but practical barriers include job-site variability, safety concerns, and the physical dexterity required, discouraging automation attempts.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Any robotic system capable of this task would cost tens of thousands of dollars to deploy, maintain, and program for variable floor types and door requirements, far exceeding the wage cost of a skilled tradesperson per job.
Cost vs. human wage	claude-sonnet-5	1/5	No viable AI/robotic solution exists to compare costs against; a human technician with tools remains the only practical option, making AI substitution cost-prohibitive or nonexistent.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product autonomously performs drilling or cutting tasks in real-world flooring installation. Robotic systems that might perform this exist only in controlled research or specialized manufacturing settings, not in general door repair operations.
Technical feasibility today	claude-sonnet-5	1/5	There are no deployed products or robots that autonomously bore or cut flooring holes for door installation in field conditions; this remains far beyond commercial robotics capability.

Clean door closer parts, using caustic soda, rotary brushes, or grinding wheels.

CI 5–15 · exposure 0 · augmentation 0 · importance 2.8/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a traditional, physically-localized trade performed by small service businesses with low digitization and capital investment in automation. Adoption of advanced robotics in this sector remains minimal.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical repair trades involving physical parts cleaning are a low-digitization, physically manual sector with minimal AI/robotics adoption for such granular maintenance subtasks.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers no meaningful assistance for the core cleaning task, which is physically manual and depends entirely on human judgment about component condition and appropriate cleaning method selection.
Augmentation potential	claude-sonnet-5	1/5	AI offers no meaningful assistance for the physical act of scrubbing, grinding, or chemically treating mechanical parts; this is a hands-on task with no cognitive or digital component to augment.
Task automatability	claude-haiku-4-5-20251001	1/5	Cleaning door closer parts requires physical manipulation of delicate components with caustic chemicals and rotating tools in a workshop setting. Current AI systems lack the embodied dexterity, safety awareness, and ability to handle hazardous materials needed to perform this task reliably.
Task automatability	claude-sonnet-5	1/5	This is a manual physical cleaning task requiring hand-eye coordination and dexterity to handle caustic chemicals, brushes, and grinding wheels on mechanical parts; no current AI system can perform physical manipulation like this.'
Adoption barriers	claude-haiku-4-5-20251001	4/5	OSHA regulations govern caustic chemical handling and worker safety, and liability exposure is high if automated cleaning causes component damage or chemical accidents. Human oversight and qualification requirements create legal and safety barriers to full automation.
Adoption barriers	claude-sonnet-5	2/5	No licensing or regulatory requirement mandates a human specifically perform this cleaning step, though safety handling of caustic chemicals and physical workshop conditions create practical friction against non-human execution.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost of industrial robots capable of handling caustic chemicals and precise cleaning operations, plus the engineering and safety systems required, far exceeds the loaded hourly wage of a skilled door repair technician.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI or robotic system deployed for this specific task, so any theoretical automation would require expensive custom robotics far exceeding the low cost of human labor for this simple task.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed commercial AI systems can autonomously clean door closer parts with caustic soda, rotary brushes, or grinding wheels. This task requires integrated robotics with chemical handling and fine manipulation capabilities not yet in production use at scale.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product exists that autonomously cleans door closer parts using rotary brushes, grinding wheels, or caustic soda; this remains purely a human manual labor task with no robotics product in production for this narrow use case.

Carry springs to tops of doors, using ladders or scaffolding, and attach springs to tracks to install spring systems.

CI 5–10 · exposure 0 · augmentation 13 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is performed by small, localized service firms with minimal digitization and low capital budgets, representing laggard sectors for automation adoption.
Sector adoption velocity	claude-sonnet-5	1/5	Door repair and installation is a low-digitization, physical trade with minimal AI/robotics adoption in the field today.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers no meaningful assistance for the core task of physically carrying and installing springs; the task is inherently manual with no software component to augment.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with scheduling, diagnostics, or parts lookup, but offers little to no assistance for the physical act of carrying and attaching springs.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation of heavy springs, climbing ladders/scaffolding, precise spatial positioning, and secure attachment in real-world environments. Current AI systems have no meaningful capability to perform such manual labor end-to-end.
Task automatability	claude-sonnet-5	1/5	This is a physical manipulation task requiring climbing ladders, carrying heavy springs, and precise mechanical attachment under tension—far outside current AI/robotic capability for general deployment.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Physical safety requirements, building codes, liability for improper installation (which could cause door failure), and the need for human judgment about load-bearing and alignment create substantial barriers to automation.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement specifically for this task, but safety regulations (fall protection, ladder/scaffold use) and liability for improperly installed high-tension springs create meaningful barriers to unsupervised automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Robotics capable of safely carrying springs up ladders and installing them would be far more expensive than hiring a skilled door repairer, with significant integration and safety validation costs.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI or robotic substitute, so any hypothetical automation would require expensive custom robotics far exceeding human labor costs.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product can physically carry springs, navigate vertical spaces, or install mechanical components. This remains entirely dependent on human workers with appropriate physical capability and training.
Technical feasibility today	claude-sonnet-5	1/5	No commercial product or robotic system performs this task in the field; it remains purely a human manual labor activity.

Assemble and fasten tracks to structures or bucks, using impact wrenches or welding equipment.

CI 5–10 · exposure 0 · augmentation 25 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Physical construction and repair trades have slow AI adoption; work is site-specific, involves unstructured environments, and depends on human expertise and sign-off.
Sector adoption velocity	claude-sonnet-5	1/5	Construction and building trades are among the least digitized, slowest-adopting sectors for AI or robotic automation of physical tasks.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could potentially assist with pre-planning (layout visualization, material calculations) but offers minimal direct support during the hands-on assembly and fastening work itself.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with planning, specifications, or diagnostic guidance beforehand, but offers minimal real-time assistance during the actual physical fastening and welding work.
Task automatability	claude-haiku-4-5-20251001	1/5	Assembly and fastening of tracks to structures requires physical manipulation, precise spatial alignment, and judgment about structural integrity—capabilities that current AI systems do not possess. No end-to-end automation solution exists for this on-site construction task.
Task automatability	claude-sonnet-5	1/5	This is a physical assembly and fastening task requiring manual manipulation of heavy hardware, welding, and precise fitting to building structures—no current AI system can perform this hands-on physical work.
Adoption barriers	claude-haiku-4-5-20251001	4/5	This task has strong adoption barriers: it requires on-site work in varied structural conditions, involves safety-critical equipment use (welding, impact wrenches), and typically requires licensed tradespeople to ensure compliance with building codes and safety standards.
Adoption barriers	claude-sonnet-5	3/5	No licensing mandate specifically for this task, but safety codes, structural liability, and the physical dexterity/judgment needed on-site create practical barriers to any automated substitute.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Specialized robotic systems capable of welding and fastening with impact wrenches would be substantially more expensive to deploy and maintain than paying a skilled tradesperson for occasional tasks.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute for this physical labor; robotic welding/fastening systems for bespoke on-site door installation would be far more costly than a human technician.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed products can reliably perform physical assembly and fastening of door tracks to structures. This task requires embodied robotics in unstructured environments, which remains research-stage.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical track assembly and welding on doors; this remains firmly in the domain of skilled tradespeople with specialized tools.

Set doors into place or stack hardware sections into openings after rail or track installation.

CI 5–10 · exposure 0 · augmentation 25 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair and installation occurs in small, distributed, craft-oriented businesses with low digitization. Adoption of automation in this sector is minimal; most work remains manual and site-specific.
Sector adoption velocity	claude-sonnet-5	1/5	Construction and building trades are among the slowest sectors to adopt AI/robotics for physical installation tasks, with minimal production deployment.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could potentially assist with layout planning or pre-positioning guidance via computer vision, but the core task of physically setting doors and stacking hardware into place offers limited augmentation value without full automation.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with planning, measurements, or diagnostics beforehand, but offers minimal direct assistance during the physical act of setting doors and hardware into place.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires precise physical manipulation in three-dimensional space, positioning heavy or bulky doors and hardware into specific openings with tight tolerances. Current AI and robotics cannot reliably perform this unstructured, site-specific assembly work at scale.
Task automatability	claude-sonnet-5	1/5	This is a physical manipulation task requiring lifting, positioning, and precise alignment of heavy door hardware into openings, which current AI systems cannot perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Building codes, occupational safety regulations, and liability concerns around structural installation create meaningful barriers. The human installer is typically responsible for proper fit and safety compliance, creating legal and insurance requirements that slow automation adoption.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement specifically blocks automation, but the physical nature, safety concerns, and need for precise on-site judgment create practical friction against substitution.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost of a robotic system capable of handling variable door installation tasks, plus integration and site adaptation, vastly exceeds the loaded hourly wage of a skilled door repairer who can work across many job sites.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI-driven robotic system for this task at any reasonable cost; a human worker remains far cheaper than any hypothetical automation solution today.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed products perform door installation and hardware positioning reliably in the field today. This requires real-time spatial reasoning, force control, and adaptation to varying site conditions that exceed current autonomous system capabilities.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical door/hardware installation; this remains firmly in the domain of human tradespeople with robotics at only experimental research stages for such variable installation work.

Fabricate replacements for worn or broken parts, using welders, lathes, drill presses, or shaping or milling machines.

CI 5–10 · exposure 0 · augmentation 25 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a small, geographically dispersed, low-digitization trade sector with minimal adoption of automation. Work is typically on-site, part-driven, and involves custom or one-off fabrication unsuitable for standardized automation.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical door repair is a small-scale, physically-oriented trade with minimal AI/robotics adoption in production settings.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI might assist in design or specification of replacement parts (e.g., CAD generation from measurements), but offers minimal productivity enhancement for the core task of operating metalworking machinery and fabricating parts by hand.
Augmentation potential	claude-sonnet-5	2/5	AI can help with CAD design, part specification lookup, or generating cut/machining instructions, but offers little direct assistance during the physical fabrication process itself.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires hands-on operation of specialized industrial machinery (welders, lathes, drill presses, milling machines) and precise physical manipulation in a workshop setting. Current AI systems cannot operate these machines or perform the physical fabrication work end-to-end.
Task automatability	claude-sonnet-5	1/5	This is a hands-on physical fabrication task requiring machine setup, material handling, and manual dexterity that current AI systems cannot perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Physical fabrication work requires human presence, machine operation licenses in some jurisdictions, and safety regulations governing machinery operation. Customers also typically expect a human technician to assess and execute repair work, creating organizational and regulatory friction.
Adoption barriers	claude-sonnet-5	3/5	No licensing requirement specifically bars automation, but physical workspace variability, custom part specs, and safety around machine tools create substantial organizational friction against substitution.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The cost of acquiring, maintaining, and operating robotic fabrication systems capable of replacing a skilled door repairer far exceeds the loaded wage of a human technician, especially for low-volume custom part fabrication.
Cost vs. human wage	claude-sonnet-5	1/5	AI-driven robotic fabrication for one-off custom parts would require far more expensive equipment and setup than a skilled technician using standard shop tools.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product can independently operate metalworking machinery to fabricate physical parts. This remains a skilled manual labor task requiring human operators and physical presence at the worksite.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product autonomously operates welders, lathes, or milling machines to fabricate custom replacement parts; this remains a manual skilled trade activity.

Run low voltage wiring on ceiling surfaces, using insulated staples.

CI 5–10 · exposure 0 · augmentation 25 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair and mechanical installation is a low-digitization, site-based trades sector with small firms and minimal automation infrastructure. Adoption of robotics in this space remains negligible.
Sector adoption velocity	claude-sonnet-5	1/5	Building trades and physical installation work are among the slowest sectors to adopt AI, with minimal robotic automation in this niche today.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could assist with task planning (e.g., wire routing optimization or safety checklists), but the physical execution itself offers limited augmentation opportunity since a human must perform or oversee the actual ceiling installation work.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with planning wire routes or providing installation instructions, but offers little direct assistance during the physical stapling and running of wire itself.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation in a complex 3D environment (ceiling surfaces), precise placement of small components (insulated staples), and judgment about routing safety. Current AI lacks the dexterity, spatial reasoning, and real-time adaptation needed for reliable end-to-end execution in varied site conditions.
Task automatability	claude-sonnet-5	1/5	This is a physical installation task requiring manual dexterity, ladder work, and precise stapling in real-world environments; no current AI system can perform this end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Electrical work involving wiring installation typically requires licensed electricians or qualified technicians in most jurisdictions, and liability for improper installation creates strong regulatory and legal barriers to full automation.
Adoption barriers	claude-sonnet-5	3/5	While not licensed like electrical work in most jurisdictions, low-voltage wiring may still fall under building codes and requires physical access to premises, creating moderate friction against remote automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost of a robot capable of ceiling-mounted wire installation, plus integration and site setup, far exceeds the loaded wage of a skilled tradesperson performing this task in situ. No cost advantage exists today.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI/robotic substitute, so the human is the only cost-effective option today, making AI more expensive by default since it doesn't functionally exist for this task.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product reliably performs low-voltage wiring installation on ceiling surfaces autonomously. This requires embodied robotics with advanced manipulation and environmental sensing at a sophistication level not yet in production use for this specific task.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product exists that performs physical wiring installation with staples; robotics for this specific unstructured task remain research-stage at best.

Fasten angle iron back-hangers to ceilings and tracks, using fasteners or welding equipment.

CI 5–5 · exposure 0 · augmentation 25 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is performed by small, dispersed service firms working on-site at customer locations. This sector has low digitization and high fragmentation, making it a laggard in automation adoption.
Sector adoption velocity	claude-sonnet-5	1/5	The door repair and installation trade is a low-digitization, physical field-work sector with minimal AI/robotics adoption for hands-on installation tasks.
Augmentation potential	claude-haiku-4-5-20251001	2/5	While AI might assist with route planning or job scheduling for technicians, it offers minimal assistance to the technician actually performing the fastening and welding work itself.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with planning, measurements, or diagnostic support via mobile apps, but offers little direct assistance to the physical fastening and welding process itself.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical manipulation in three-dimensional space, precise positioning of components, and operation of power tools or welding equipment in variable site conditions. Current AI systems cannot operate hardware, move in physical environments, or perform the dexterous installation work described.
Task automatability	claude-sonnet-5	1/5	This is a physical fabrication and installation task requiring precise manual manipulation of heavy hardware, welding, and overhead fastening in variable environments—well beyond current robotic or AI capability for general deployment.
Adoption barriers	claude-haiku-4-5-20251001	4/5	This task involves building code compliance, structural safety liability, and often requires a licensed tradesperson to sign off on installation. The high error-cost asymmetry (poor fastening creates safety hazards) and site-specific variability create strong adoption barriers.
Adoption barriers	claude-sonnet-5	4/5	Welding and structural installation work often requires certified welders, adherence to building codes, and liability considerations for overhead structural safety, creating significant regulatory and safety barriers.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The capital cost of robotic systems capable of this work, combined with integration and site-specific programming, far exceeds the labor cost of a skilled technician performing the installation.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI/robotic system to compare costs against; any hypothetical robotic solution for mobile overhead welding/fastening would be far more expensive than a human technician.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI or robotic system can reliably perform this task end-to-end in the field. While industrial robotics exists in controlled environments, autonomous fastening and welding of door hardware to arbitrary ceiling and track configurations remains research-stage.
Technical feasibility today	claude-sonnet-5	1/5	No deployed commercial product performs on-site welding and fastening of angle iron hangers to ceilings; this remains firmly in the domain of skilled human tradespeople.

Install door frames, rails, steel rolling curtains, electronic-eye mechanisms, or electric door openers and closers, using power tools, hand tools, and electronic test equipment.

CI 0–10 · exposure 0 · augmentation 25 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Mechanical door repair is a physical trades occupation with low digitization, small firm prevalence, and no measurable AI adoption in production; it remains a laggard sector for automation.
Sector adoption velocity	claude-sonnet-5	1/5	Construction and building trades are among the slowest sectors to adopt AI/robotics, with minimal automation penetration into physical installation work.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could marginally assist with diagnostic guidance (e.g., troubleshooting electronic-eye mechanisms via decision trees or remote video analysis), but the core task—physical installation and testing—cannot be meaningfully augmented by current AI systems.
Augmentation potential	claude-sonnet-5	2/5	AI could assist with diagnostics, documentation, or ordering parts, but offers little direct help with the hands-on installation process itself.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires physical installation of hardware components in precise locations, alignment, and testing—work that depends on spatial reasoning, manual dexterity, and real-time problem-solving in varied physical environments. Current AI systems cannot physically manipulate tools or perform on-site installation work.
Task automatability	claude-sonnet-5	1/5	This is a physical installation task requiring manipulation of heavy hardware, precise fitting, and use of hand/power tools in varied environments—far outside current AI capability without robotic embodiment.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Installation work requires licensed trades credentials in many jurisdictions, direct physical presence on-site, liability for safety and building code compliance, and signature/sign-off by a qualified technician—all hard legal and regulatory barriers.
Adoption barriers	claude-sonnet-5	3/5	No licensing mandate typically requires a human specifically, but physical dexterity, on-site judgment, and liability for faulty security/door installations create strong practical barriers to any automated substitute.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	AI systems cannot perform this task at all, making cost comparison moot—the loaded wage of a skilled door repairer remains far below any viable AI substitute cost since no substitution exists.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this physical labor, so AI cost is effectively infinite relative to a human technician's wage.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product can autonomously install door frames, rails, or electronic mechanisms. This remains entirely within the domain of human skilled trades; no production systems exist for this class of physical installation.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs physical door frame or hardware installation; this remains a purely human manual trade task today.

Operate lifts, winches, or chain falls to move heavy curtain doors.

CI 0–10 · exposure 0 · augmentation 0 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Door repair is a small, localized, non-digitized trade with low overall AI adoption; custom automation of equipment operation is not occurring in this sector.
Sector adoption velocity	claude-sonnet-5	1/5	Mechanical door repair is a physical, low-digitization trade with minimal AI or robotics adoption; this sector shows negligible movement toward automating physical equipment operation.
Augmentation potential	claude-haiku-4-5-20251001	1/5	AI offers no meaningful assistance to a human operating manual lifts or chain falls; the task is inherently hands-on physical control with no natural role for AI augmentation.
Augmentation potential	claude-sonnet-5	1/5	AI offers no meaningful assistance for the physical act of operating lifts and winches, though it might help with unrelated tasks like scheduling or diagnostics elsewhere in the job.
Task automatability	claude-haiku-4-5-20251001	1/5	Operating lifts, winches, or chain falls to move heavy curtain doors requires manual control of mechanical equipment in physical space with real-time load sensing and safety adjustments that current AI systems cannot perform end-to-end without human operation.
Task automatability	claude-sonnet-5	1/5	This is a physical manipulation task requiring on-site operation of heavy machinery to move curtain doors; no current AI system can perform this physical work end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Safety regulations, liability for load handling, and the requirement for a licensed/trained operator to physically manage heavy equipment create hard barriers to automation of this mechanical task.
Adoption barriers	claude-sonnet-5	3/5	While no licensing mandates a human specifically, safety regulations around heavy lifting equipment, liability for equipment damage or injury, and the need for physical presence create real friction against automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	Automating mechanical equipment operation would require custom robotics infrastructure far more expensive than paying a skilled door repairer to operate existing manual equipment.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute for this physical task, so any hypothetical robotic solution would require far more capital investment than simply paying a technician's wage.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product reliably operates physical mechanical equipment like lifts or chain falls; such tasks remain entirely dependent on human manual control in production environments.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product operates lifts, winches, or chain falls autonomously for door repair work in production; this remains firmly in the physical/robotics research domain, not commercial deployment.

Related occupations — Installation, Maintenance & Repair

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.