Carpet Installers
47-2041.00Median wage $50,340/yr13,780 employed (US)Rank #740 of 923 scored · top 80% by substitution
Lay and install carpet from rolls or blocks on floors. Install padding and trim flooring materials.
Sub-scores
0–100 · band = confidence interval from rater disagreement
Substitution17
Exposure6
Augmentation19
Substitution — the headline: capability discounted by cost, barriers and adoption.
Exposure — technical capability alone, regardless of whether anyone deploys it.
Augmentation — how much AI assists without replacing. High here + moderate substitution = a changing job, not a disappearing one.
Tasks on the substitution scale
16 rated tasks, binned by substitution score.
Position among all scored occupations
Distribution of 923 occupation scores; the marker is this occupation.
Tasks with substitution ≥ 70
0%
Run 1.0.0-draft.1 · computed 2026-08-05 · rater panel: claude-sonnet-5, claude-haiku-4-5-20251001 · intervals span rater disagreement.
Why this score
The five weighted dimensions of the composite, averaged across this occupation's tasks (importance-weighted, panel mean). Exact weights and formulas: /api/v1/methodology.
Task automatabilityw 35%7
panel mean rating 1.3/5 → substitution pressure 7/100
Technical feasibility todayw 20%5
panel mean rating 1.2/5 → substitution pressure 5/100
Cost vs. human wagew 15%6
panel mean rating 1.2/5 → substitution pressure 6/100
Adoption barriersw 20%inverted — strong barriers lower the score62
panel mean rating 2.5/5 (barrier strength) → substitution pressure 62/100
Sector adoption velocityw 10%3
panel mean rating 1.1/5 → substitution pressure 3/100
Task breakdown (16 tasks)
Substitution pressure per task, weighted by O*NET importance in the composite. Expand a task for the full rater audit trail — every rating, every model, every rationale.
Take measurements and study floor sketches to calculate the area to be carpeted and the amount of material needed.
48CI 35–61 · exposure 38 · augmentation 75 · importance 4.3/5 · click for rater detail
Take measurements and study floor sketches to calculate the area to be carpeted and the amount of material needed.
48| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Carpet installation is a fragmented, small-business-dominated sector with low digital maturity; adoption of automated measurement remains sparse in production despite technical feasibility. Pilots exist but field adoption is minimal compared to information or professional services sectors. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Construction and flooring trades are among the slower-adopting sectors for AI, with digitization of takeoff processes still uneven across small firms. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI tools that extract measurements from photos and auto-calculate areas can substantially accelerate installer workflows while preserving human judgment on material selection, waste allowance, and customer constraints. This is a natural augmentation scenario where the human remains in control. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-powered estimating tools and apps can quickly calculate area and material needs from measurements or sketches, meaningfully speeding up this part of the job. |
| Task automatability | claude-haiku-4-5-20251001 | 3/5 | AI can perform measurements from floor sketches and area calculations reliably, but real-world carpet installation requires on-site adaptation for obstacles, irregular layouts, and material waste factors that still demand human judgment. Roughly 50-60% time savings is achievable with computer vision and automated calculation tools. |
| Task automatability | claude-sonnet-5 | 2/5 | Calculating area from measurements is simple, but the physical measurement of irregular rooms and interpreting real-world floor conditions requires on-site human work AI cannot perform end-to-end today.: |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | No legal requirement mandates human measurement in most jurisdictions, and customer acceptance of AI-assisted estimates is growing in commercial settings. Light friction exists from installer liability concerns and customer preference for human site visits, but no hard regulatory barrier prevents substitution. |
| Adoption barriers | claude-sonnet-5 | 1/5 | No licensing or legal requirement mandates a human perform area calculations; it's a low-stakes computational task. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | AI-powered measurement and calculation tools are inexpensive to deploy per task ($1–5 in inference and integration overhead), while a skilled carpet installer's measurement and calculation time costs $20–40 loaded. The ratio favors AI by several multiples, though oversight integration adds modest cost. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Software-assisted calculation is cheap, but the human still must physically measure the space, so total cost savings are modest compared to a fully human-driven process. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | Products exist using image recognition and automated area calculation (e.g., measurement tools, CAD plugins), but their accuracy is material-dependent and they require human verification for complex floor plans, irregular shapes, and edge cases. Deployed systems work in controlled settings but lack reliability at production scale across diverse floor conditions. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Some estimating/takeoff software exists and can compute material quantities from digital floor plans, but real-site measurement and sketch interpretation still rely heavily on human installers. |
Draw building diagrams and record dimensions.
39CI 30–49 · exposure 33 · augmentation 63 · importance 3.8/5 · click for rater detail
Draw building diagrams and record dimensions.
39| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Carpet installation remains a traditionally-conducted, site-dependent craft with limited digital infrastructure penetration. While some larger installation firms may use digital tools, widespread AI adoption in this occupational segment remains minimal and slow. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Construction and trades sectors have historically slow digitization and AI adoption compared to office-based professional services. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can meaningfully assist installers by automating diagram generation from measurements, suggesting layout optimizations, or helping record data digitally; however, the human installer must still physically measure spaces and verify accuracy, so augmentation is moderate rather than transformative. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-powered measurement and diagramming apps (LiDAR scanning, auto-CAD generation) meaningfully speed up diagram creation and dimension recording while installer verifies results. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Drawing building diagrams and recording dimensions requires spatial understanding and precision, but current AI has limited capability to autonomously measure physical spaces or create accurate architectural diagrams from raw observation. While AI can assist with diagram generation from structured data, the task still requires significant human involvement for actual measurement and quality assurance. |
| Task automatability | claude-sonnet-5 | 3/5 | AI can generate diagrams from measurements or photos using CAD/vision tools, but accurate on-site measurement and translating irregular room geometry into diagrams still requires human verification, limiting full end-to-end automation. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Installation work requires on-site presence and physical measurement, creating some friction for full automation. However, there are no strict licensing or legal barriers preventing AI assistance with diagram and dimension recording, though accuracy liability concerns exist. |
| Adoption barriers | claude-sonnet-5 | 1/5 | No licensing or legal requirement mandates a human specifically draw diagrams; it's a practical task with minimal regulatory barrier. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Current AI tools for diagramming (CAD plugins, design assistants) still require human oversight and manual data input, making the all-in cost comparable to or potentially exceeding a human installer's time for this task. Cost advantage is not yet realized. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Consumer-grade scanning apps are cheap, but integrating them reliably into a contractor's workflow with verification still requires labor, so net savings versus a worker doing it manually are modest. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Existing products like CAD software with AI features can assist with diagram creation, but no mature AI system reliably performs end-to-end autonomous measurement, recording, and diagram drawing on construction sites. Deployed solutions require substantial human input and verification. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Some floor-plan and room-scanning apps (e.g., smartphone LiDAR-based tools) exist but are not universally deployed in carpet installation workflows and require human input for accuracy and edge cases. |
Clean up before and after installation, including vacuuming carpet and discarding remnant pieces.
24CI 15–33 · exposure 13 · augmentation 13 · importance 4.1/5 · click for rater detail
Clean up before and after installation, including vacuuming carpet and discarding remnant pieces.
24| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation is a traditional, physically localized trade with low digital maturity. Adoption of specialized cleanup automation in this sector remains minimal—most firms rely on human labor for these tasks. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Carpet installation is a low-digitization, physical trade sector with minimal AI/robotics adoption for site cleanup tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Handheld vacuums and power tools assist human workers, but AI-driven augmentation specifically (e.g., autonomous remnant sorting or smart scheduling of cleanup) offers limited productivity gains for cleanup work that is already relatively efficient with low-cost labor. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers negligible assistance for physical vacuuming and debris removal; there's no meaningful software or planning layer to augment this manual task. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While vacuuming is theoretically automatable with robotic systems, performing it selectively in active job sites with furniture and fixtures in place remains challenging. Discarding remnants requires object recognition and safe disposal—feasible in controlled settings but difficult end-to-end on construction sites. Current robots cannot reliably achieve 50% time savings with equal quality in the variable, cluttered environments typical of carpet installation. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical manipulation task requiring mobility, vacuuming, and material handling in variable job-site environments, which current AI systems cannot perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | There are minimal legal or regulatory barriers to automation of cleanup work. However, site-specific conditions, liability concerns for damage in customer spaces, and the low wage rate of cleanup labor create practical and organizational friction against substitution. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing or legal requirement mandates a human specifically for cleanup, but practical barriers like site variability, tool transport, and lack of robotic infrastructure limit substitution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Robotic vacuuming and remnant-disposal systems remain capital-intensive and specialized. When amortized over typical carpet installation job volumes, they currently cost more than hiring temporary or existing crew labor for cleanup tasks. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic substitute for this physical task, so the human remains the only cost-effective option; any robotic attempt would require far more capital and setup than the labor saved. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Robotic vacuums exist but perform poorly in the variable, obstacle-filled environments of active construction and installation sites. No deployed products reliably handle the pre- and post-installation cleanup task as a complete system, though experimental robotics show promise in controlled facilities. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs autonomous job-site cleanup, vacuuming of installed carpet, or debris disposal; robotic vacuums exist for flat open floors but not construction/installation cleanup contexts. |
Plan the layout of the carpet, allowing for expected traffic patterns and placing seams for best appearance and longest wear.
19CI 5–33 · exposure 13 · augmentation 38 · importance 4.4/5 · click for rater detail
Plan the layout of the carpet, allowing for expected traffic patterns and placing seams for best appearance and longest wear.
19| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation remains a small-firm, hands-on trade with low digitization. The sector has not shown meaningful adoption of AI-driven layout planning tools; adoption would require training and workflow changes across fragmented small contractors. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Carpet installation is a low-digitization, physical trade sector with minimal AI adoption or investment in this niche task area. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI could assist by visualizing traffic patterns, suggesting seam locations, or simulating different layouts for the installer to evaluate, moderately raising efficiency. However, the spatial and aesthetic judgment required means assistance is partial and context-dependent rather than transformative. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with visualizing layouts or calculating material estimates from room measurements, but the core spatial judgment and seam placement decisions still depend heavily on the installer's on-site expertise. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI could analyze floor layouts and generate seam placement suggestions based on traffic patterns and aesthetic rules, the task requires spatial judgment about actual site conditions, material behavior, and client preferences that demand human oversight. Current systems lack the embodied understanding of carpet materials and real-world installation constraints to achieve 50% time savings at equal quality end-to-end. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires physical assessment of a room, judgment about traffic patterns, and material handling decisions that current AI cannot execute end-to-end; no off-the-shelf system plans and lays out physical carpet installation. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Customer contact is integral—layouts must be validated with clients on-site. Professional liability for poor seaming is high, installers often hold licensing or union credentials, and the visual/qualitative nature of 'best appearance' creates resistance to full automation without human sign-off. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement typically governs this specific planning step, but it's tightly coupled to physical installation work requiring on-site human presence and judgment. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | The cost of AI analysis plus human verification and rework would likely approach or exceed the time cost of an experienced carpet installer doing the layout directly, given the spatial reasoning and material expertise required. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute performing this physical planning task, so any AI cost comparison is moot—human installers remain the only functional option. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No production systems reliably perform full carpet layout planning in deployed settings. AI can assist with traffic analysis or generate candidate seam placements, but no mature product independently plans carpet layouts at the quality and reliability expected by installers in the field. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs real-world carpet seam layout planning tied to physical installation; this remains a manual skilled-trade task. |
Cut and trim carpet to fit along wall edges, openings, and projections, finishing the edges with a wall trimmer.
17CI 10–24 · exposure 8 · augmentation 13 · importance 4.5/5 · click for rater detail
Cut and trim carpet to fit along wall edges, openings, and projections, finishing the edges with a wall trimmer.
17| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation remains a traditional, on-site, craft-oriented trade with limited digital infrastructure. The sector shows minimal adoption of automation; work is geographically dispersed, customized per job, and performed by small teams rather than centralized operations. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Flooring installation is a highly physical, low-digitization trade with minimal AI/robotic adoption and no momentum toward automating this specific manual cutting task. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could potentially assist with digital modeling or pre-site measurement planning, but the core task—physical cutting and trimming to fit—offers limited opportunity for assistive augmentation while a human remains in full control of precision fitting and finishing. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no assistance for the physical act of cutting and trimming carpet along walls, though software might help with material estimation elsewhere in the job. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While cutting and trimming operations can be partially automated in controlled factory settings, the task requires real-time spatial adaptation to irregular wall edges, openings, and architectural projections that vary by site. Current AI and robotic systems struggle with the unstructured, on-site variability and precision fitting needed to achieve equal quality, making full end-to-end automation far from the 50% time-savings threshold. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a precise physical manipulation task requiring hand-eye coordination, tool use (wall trimmer), and adaptation to irregular room geometry that no current AI or robotic system can perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | The task occurs on customer premises and requires quality fitting that directly affects customer satisfaction and product durability. While no hard legal licensing barrier exists for robots, organizational friction around quality assurance, site-specific variation, and customer preference for skilled human installers creates meaningful adoption friction. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing strictly required for carpet cutting itself, but physical dexterity, judgment for irregular cuts, and on-site variability create strong practical barriers to substitution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Specialized robotic systems capable of this task remain prohibitively expensive to develop and maintain, with high integration costs per site. A trained carpet installer's loaded wage is far lower than the capital and operational cost of a reliable robotic alternative. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic substitute, so any hypothetical automation would require expensive custom robotics far exceeding the cost of a human installer for this task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed commercial robotic systems reliably perform on-site carpet trimming and wall-edge finishing in production. Prototype research exists, but no mature product performs this task at scale in real installations with acceptable error rates for customer-facing work. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed products exist that autonomously cut and trim carpet to fit walls; this remains firmly in the domain of skilled manual labor with zero commercial robotic automation. |
Roll out, measure, mark, and cut carpeting to size with a carpet knife, following floor sketches and allowing extra carpet for final fitting.
15CI 15–15 · exposure 0 · augmentation 25 · importance 4.5/5 · click for rater detail
Roll out, measure, mark, and cut carpeting to size with a carpet knife, following floor sketches and allowing extra carpet for final fitting.
15| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation remains a low-digitization, local, craft-oriented sector with minimal AI or robotics adoption. The industry has not pursued automation of measurement and cutting steps at scale. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Flooring installation is a low-digitization, physical trade sector with essentially no AI/robotics adoption for this kind of task. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with floor layout planning or measurement verification via computer vision analysis of floor photos, but the core manual work of rolling, cutting, and fitting still requires the installer's hands and judgment in real-time. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with layout planning or optimizing cut patterns from floor sketches to reduce waste, but it offers little help with the physical measuring and cutting itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Rolling out, measuring, marking, and cutting carpet requires precise physical manipulation in variable floor layouts, dexterity, spatial judgment, and real-time adjustment to irregular surfaces. Current AI systems lack the embodied robotics capability and real-world adaptation needed to perform this end-to-end reliably. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical manipulation task requiring hand-eye coordination, spatial judgment, and precise blade cutting on flexible material; no current AI/robotic system performs this end-to-end reliably. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | While there are no hard legal licensing barriers specific to carpet cutting itself, the task is embedded in a physically onsite process requiring human inspection, judgment about fit quality, and adjustment—creating friction in full automation. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing specifically restricts carpet cutting, but physical dexterity requirements and on-site variability create strong practical barriers to automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Any robotics system capable of this task (robotic arm with vision, cutting tools, and real-time adjustment) would cost tens of thousands of dollars, far exceeding the labor cost for a single installation job or even multiple jobs. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable automated substitute, so any hypothetical robotic solution would require far more capital and setup cost than a human installer's wage for this task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed commercial product reliably performs carpet measurement, marking, and cutting autonomously in diverse residential or commercial settings. This remains a manual craft task with no production-scale automation in the market. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed products exist that measure, mark, and cut carpet in real installation environments; this remains a purely manual skilled trade task. |
Join edges of carpet and seam edges where necessary, by sewing or by using tape with glue and heated carpet iron.
15CI 15–15 · exposure 0 · augmentation 0 · importance 4.5/5 · click for rater detail
Join edges of carpet and seam edges where necessary, by sewing or by using tape with glue and heated carpet iron.
15| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation is a traditional, on-site manual trade with low digitization and fragmented small firms; adoption of automation technology in this sector has been negligible and shows no acceleration. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Flooring installation is a highly physical, low-digitization trade with minimal AI/robotics adoption and no production deployment trends. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | Current AI and robotics offer no meaningful assistance to human installers performing seaming work; the task is purely physical and requires human judgment, dexterity, and sensory feedback that augmentation tools do not yet enhance. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no assistance for the physical act of seaming carpet edges with heat and adhesive tools. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires precise physical manipulation in a 3D space (aligning carpet edges, operating heated equipment, monitoring seam quality) and fine motor control that current robotic systems cannot reliably perform at scale. The variability in carpet texture, humidity, and edge geometry makes end-to-end automation infeasible today. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical, dexterous task requiring precise manual manipulation of carpet, seaming tape, and heated irons; no current AI system can perform this physical work. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | While there are no strict licensing requirements for carpet installation, customer expectations strongly favor human craftsmanship and on-site problem-solving, and liability concerns around seam failure create some organizational friction against automation. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing strictly required for carpet seaming itself, but physical dexterity, judgment on material behavior, and customer property risk create practical barriers to any automated substitute. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The capital cost of specialized robotic systems, combined with integration and maintenance overhead, would far exceed the loaded wage of a skilled carpet installer for the foreseeable future, especially given the task's technical difficulty. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic substitute, so the human installer remains the only cost-effective option, making AI comparatively far more expensive or simply unavailable. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed commercial product reliably performs carpet seaming automation in real installations. This remains a manual, human-performed task across the industry with no production systems demonstrating the required precision and adaptability. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs carpet seaming; this remains purely a manual trade skill with no robotic automation in production. |
Install carpet on some floors using adhesive, following prescribed method.
15CI 15–15 · exposure 0 · augmentation 25 · importance 4.3/5 · click for rater detail
Install carpet on some floors using adhesive, following prescribed method.
15| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | The flooring installation sector is traditional, manual, and physically on-site; digitization is low and adoption of automation remains negligible with no visible industry-wide AI or robotics deployment. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Flooring and construction trades are among the least digitized sectors with minimal AI/robotics adoption for physical installation tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with layout planning, material estimation, or design visualization before installation, but offers minimal real-time assistance during the hands-on physical work of applying adhesive and positioning carpet. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with measurement calculations, material estimation, or pattern planning software, but offers minimal help with the core physical installation process itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Carpet installation requires physical manipulation of large materials, precise seaming, adhesive application to irregular floor surfaces, and real-time adjustment—tasks that current robotics and AI cannot perform reliably without extensive on-site customization. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical manipulation task requiring cutting, stretching, and adhering carpet material with precision; no current AI system or robot can perform this end-to-end in unstructured environments. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | While there are no strict licensing requirements for the task itself, customer expectations, liability concerns about installation quality, and the physical/specialized nature of the work create moderate friction to automation adoption. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing typically required for carpet installation, but physical dexterity, judgment on irregular surfaces, and customer property considerations create practical barriers to automation, though not regulatory ones. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The capital and integration costs for a robotic carpet installation system would far exceed the loaded wage of a skilled carpet installer, making automation economically unviable. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic substitute, so the human installer remains the only cost-effective option; any hypothetical robotic system would require far greater capital investment than a human worker. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI systems or robots perform end-to-end carpet installation in production settings; this remains entirely human-performed work requiring dexterity and spatial reasoning beyond current automation. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed products install carpet; this remains firmly in the domain of human tradespeople with no robotic flooring installation systems in commercial use. |
Measure, cut and install tackless strips along the baseboard or wall.
15CI 15–15 · exposure 0 · augmentation 13 · importance 4.0/5 · click for rater detail
Measure, cut and install tackless strips along the baseboard or wall.
15| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation remains a traditional, labor-intensive trade in small and medium firms with limited digitization. Adoption of robotics or AI in this sector is negligible; the industry continues to rely on skilled workers. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Flooring installation is a small-business, physically-based trade with very low digitization and no meaningful AI/robotic adoption trends. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with measurement planning or layout visualization, but the core task—precise cutting and physical installation—leaves limited room for meaningful augmentation without human expertise remaining central. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI tools offer negligible assistance for the physical measuring, cutting, and nailing involved in installing tackless strips. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires precise physical manipulation in variable real-world environments (wall geometry, baseboard irregularities) and installation judgment that current AI systems cannot perform end-to-end. Robotics exist for narrow, controlled settings but not for the adaptive physical work demanded here. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical, dexterity-intensive task requiring precise cutting, nailing, and fitting of strips around room perimeters with varied geometry; no current AI/robotic system performs this end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | While there is no formal licensing requirement for carpet installation itself, liability for improper installation, customer preference for human craftsmanship, and the need for on-site judgment create practical friction against automation adoption. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing is typically required for carpet installation, but physical access to homes, liability for property damage, and irregular room layouts create practical friction against automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Robotic systems capable of this work would require significant capital investment, custom setup per job, and ongoing maintenance—far exceeding the wage cost of a trained carpet installer for the same output. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI or robotic substitute performing this task, so any hypothetical automation would require expensive custom robotics far exceeding the cost of a human installer. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed product reliably measures, cuts, and installs tackless strips in diverse residential or commercial spaces. This is a skilled manual task requiring embodied robotics, which has not achieved production-scale deployment for carpet installation. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed commercial product installs tackless strips; this remains firmly in the domain of manual skilled labor with no robotics products in production for this niche. |
Nail tack strips around area to be carpeted or use old strips to attach edges of new carpet.
13CI 10–15 · exposure 0 · augmentation 0 · importance 4.0/5 · click for rater detail
Nail tack strips around area to be carpeted or use old strips to attach edges of new carpet.
13| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation remains a traditional, physically-grounded trade in small and medium-sized firms with low digitization and minimal AI adoption patterns typical of construction and skilled trades. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Flooring installation is a low-digitization, physical trade with minimal AI or robotics adoption; the sector lags far behind information/professional services in automation. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | Current AI systems offer no meaningful assistance for the hands-on physical work of nailing or positioning tack strips; the task is fundamentally manual execution rather than one where AI tooling would augment human capability. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers no meaningful assistance for the physical act of nailing tack strips; this task has no digital or cognitive component to augment. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires precise physical manipulation in variable indoor environments, positioning strips at exact perimeter locations, and adapting to room geometry. Current robotics and AI systems cannot reliably perform end-to-end physical installation with the dexterity and spatial reasoning required. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a manual, physical task requiring precise measurement, cutting, and nailing of tack strips along irregular room perimeters; no current AI system can perform this physical manipulation. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | While there are no strict licensing requirements for the task itself, the need for human judgment in room assessment, precise physical execution in varied spaces, and customer preference for skilled human labor provide modest friction against automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing barrier exists specifically for this task, but the physical nature of the work, need for on-site presence, and precision handiwork create strong practical barriers to automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Specialized robotic systems for carpet installation are expensive, require significant setup, and have high error correction costs, making them substantially more costly than the loaded wage of a trained carpet installer performing this work. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI-driven equivalent to compare cost against; a human installer's labor remains the only viable option, making AI substitution infeasible and thus costlier by default. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI or robotic systems reliably perform tack strip installation at scale in production environments. This remains a skilled manual task with no commercial automation products in real-world use. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs physical carpet tack strip installation; this remains entirely a human manual trade skill with no robotic solution in production. |
Cut carpet padding to size and install padding, following prescribed method.
10CI 5–15 · exposure 0 · augmentation 25 · importance 4.0/5 · click for rater detail
Cut carpet padding to size and install padding, following prescribed method.
10| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation is a traditional skilled trade in small, geographically dispersed firms with low digital infrastructure adoption and minimal capital for robotics investment. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Flooring installation is a low-digitization, physical trade sector showing minimal AI or robotics adoption for manual installation tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with measurement capture or layout design via computer vision, but such tools see limited uptake; the core cutting and positioning work remains manual and benefits only marginally from current AI assistance. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with measurement calculations or material estimation, but offers little direct help with the physical cutting and installation process itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Cutting and installing carpet padding requires physical manipulation in three-dimensional space with precise measurements adapted to irregular room geometry, uneven floors, and variable substrate conditions—capabilities current AI cannot perform autonomously on-site without specialized robotics. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical manipulation task requiring cutting and fitting flexible material in irregular room layouts; 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 | Physical work requiring on-site adaptation to customer properties, building codes compliance, and warranty liability for installation defects create substantial friction against automation; customer expectations for human workmanship also factor heavily. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing strictly requires a human, but physical dexterity, spatial judgment, and customer-site variability create strong practical barriers to automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The equipment, sensors, and coordination overhead required for a robot to perform this task autonomously would substantially exceed the loaded wage of a skilled carpet installer, even accounting for volume deployment. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic substitute for this physical task, 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 commercial product reliably performs autonomous carpet padding cutting and installation; this remains entirely dependent on human technicians in production environments. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs carpet padding cutting and installation; this remains firmly in the domain of skilled manual trade work with no robotic or AI installation systems in production. |
Fasten metal treads across door openings or where carpet meets flooring to hold carpet in place.
10CI 5–15 · exposure 0 · augmentation 0 · importance 4.0/5 · click for rater detail
Fasten metal treads across door openings or where carpet meets flooring to hold carpet in place.
10| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | The carpet installation sector is a small-firm, trade-based, physically distributed industry with low digitization and minimal AI/robotics adoption in production environments. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Construction and flooring trades are among the least digitized, physically-grounded sectors with minimal AI/robotics adoption for hands-on installation tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | Current AI offers no meaningful assistance for the core task of physically fastening treads; the work demands in-situ human judgment and dexterity that AI tools do not augment. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers no meaningful assistance for the physical act of cutting and fastening metal transition strips; this is a purely manual, tool-based task. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires physical manipulation in a real-world environment (fastening metal treads), precise spatial alignment, and adaptation to varying door and floor conditions. Current AI systems lack the embodied capability and fine motor control to perform this end-to-end work reliably. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a precise physical manipulation task requiring cutting, positioning, and fastening metal transition strips to flooring, which current AI systems cannot perform end-to-end without robotic hardware that doesn't exist for this purpose. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Installation work typically requires on-site human presence and judgment about fit, alignment, and safety; customer preference for licensed installers and liability concerns around flooring safety also create friction against full automation. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing typically required for this specific task, though it's often bundled into a trade requiring some skill certification or employer-based training; physical presence and dexterity are inherent requirements. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The cost of developing, deploying, and maintaining a robotic system capable of fastening treads across variable door openings would far exceed the labor cost of a human installer performing this single task. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI-driven substitute for the physical labor and tools involved, 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 fasten metal treads. This is a manual, dexterous task requiring robotic hardware that is not yet used in production carpet installation at commercial scale. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed products perform this physical fastening task; it remains entirely research-stage or nonexistent for general carpentry work of this kind. |
Move furniture from area to be carpeted and remove old carpet and padding.
10CI 5–15 · exposure 0 · augmentation 0 · importance 3.7/5 · click for rater detail
Move furniture from area to be carpeted and remove old carpet and padding.
10| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation is a fragmented, low-digitization, small-firm dominated trade. Adoption of robotics in this sector is negligible; the task remains almost entirely manual labor. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Flooring installation is a low-digitization, physically manual trade with no evidence of AI or robotics displacement occurring in this space. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | AI offers no meaningful assistance for moving furniture or removing carpet. The task is purely physical labor with no informational or analytical component that AI could augment. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no assistance for the physical acts of moving furniture or tearing out old carpet and padding. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires physical manipulation of furniture and carpet in real-world, unstructured residential/commercial spaces. Current AI systems cannot operate robotic hardware reliably to move varied furniture types or handle the dexterity and strength needed for carpet removal at scale. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical labor task requiring manipulation of heavy furniture and manual removal of tacked-down carpet and padding; no current AI system (software or robotics) can perform this end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | The task inherently requires physical presence in customer locations and hands-on manipulation, creating strong human-contact and organizational barriers. Liability for damage to furniture or property during automated removal also raises legal friction. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing or legal barrier prevents automation in principle, but the physical nature of the task and lack of any robotic system create a practical barrier to substitution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Robotics capable of this work would be prohibitively expensive to purchase, maintain, and deploy on-site compared to paying a low-wage carpet installer for the same labor output. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic substitute at any cost point for this task, so the human remains the only economically available option. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed commercial product performs end-to-end furniture moving and carpet removal. Robotics for this task remains experimental; the variability of layouts, furniture types, and carpet conditions exceeds current production capabilities. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs furniture moving and carpet tear-out; this remains firmly in the domain of human physical labor with no robotic solution in production. |
Cut and bind material.
10CI 5–15 · exposure 0 · augmentation 0 · importance 3.5/5 · click for rater detail
Cut and bind material.
10| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation remains in low-digitization, small-firm, physical-labor sectors with minimal AI adoption. There is no evidence of meaningful pilot or production deployment of automation for material cutting and binding. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Carpet installation is a small-business, physically intensive trade with minimal digitization or AI adoption in current practice. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | Current AI systems offer no meaningful assistance to carpet installers performing cutting and binding work, as these tasks depend entirely on hands-on physical execution rather than knowledge or decision support. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no assistance to the physical act of cutting and binding carpet material. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Cutting and binding carpet material requires real-time spatial reasoning, physical manipulation of flexible materials, and precise tool control in highly variable on-site conditions. Current AI systems lack the embodied dexterity and sensorimotor feedback needed to perform this task end-to-end. |
| Task automatability | claude-sonnet-5 | 1/5 | Cutting and binding carpet is a physical manipulation task requiring precise measurement, dexterity, and handling of flexible material on-site, none of which current AI systems can perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Carpet installation is a licensed trade in many jurisdictions, and installation quality directly affects customer liability. The physical, on-site nature of the work and customer presence create strong friction against automation. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing strictly requires a human, but physical presence, tool handling, and customer property considerations create practical friction against automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The capital cost of robots capable of flexible material handling, combined with integration and site-specific setup, far exceeds the loaded wage of a skilled carpet installer performing this task repeatedly across multiple jobs. |
| 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., robotics) would be far more costly than a human installer today. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed products exist that can autonomously cut and bind carpet material in production environments. Robotic systems capable of this task remain at research or prototype stages and are not in use by carpet installation companies. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed products perform physical carpet cutting and binding; this remains a manual trade skill with no robotic or AI product in production use. |
Inspect the surface to be covered to determine its condition, and correct any imperfections that might show through carpet or cause carpet to wear unevenly.
7CI 5–10 · exposure 0 · augmentation 13 · importance 4.5/5 · click for rater detail
Inspect the surface to be covered to determine its condition, and correct any imperfections that might show through carpet or cause carpet to wear unevenly.
7| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation is a traditional, site-specific trade with low digital adoption and minimal automation infrastructure. Adoption of AI in this sector remains negligible; most firms rely on skilled manual labor. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Carpet installation is a low-digitization, physical trade with minimal AI adoption; this is a laggard sector for automation of hands-on tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | Augmentation is limited because the task is primarily sensory and corrective—an installer must physically feel and fix imperfections. Vision tools could flag visible defects, but the human must still perform the repair work, offering only modest productivity gain. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI offers essentially no meaningful assistance for physically inspecting and correcting subfloor imperfections in real time. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | Inspecting and correcting surface imperfections requires physical assessment, tactile feedback, and spatially-aware remediation that current AI cannot perform. No automation system can reliably detect subsurface defects, evaluate wear patterns, or execute repairs at the quality standard needed for carpet installation. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires physical inspection of a floor surface (touch, sight, sometimes tools) and hands-on correction of imperfections like filling gaps or leveling subfloor, none of which current AI systems can perform end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Installation trades require licensed workers in many jurisdictions and carry liability for defective work. The final surface condition directly affects carpet performance and customer satisfaction, creating legal and financial accountability that limits automation substitution. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement typically governs this specific task, but it demands physical presence, tactile judgment, and craftsmanship that create strong practical barriers to remote or automated substitution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | An AI system capable of autonomous surface inspection, defect classification, and correction would require expensive robotics, specialized sensors, and integration costs that far exceed the loaded wage of a carpet installer performing this inspection task. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI alternative for the physical labor and judgment involved, so the human remains the only cost-effective option for this task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed product performs this task autonomously today. While computer vision can identify visible surface damage in controlled settings, deployed systems do not assess carpet-installation-specific criteria (levelness, adhesion, wear patterns) or execute corrections in real jobsite conditions. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs physical floor surface inspection and correction; this remains a manual, on-site skilled trade task with no AI substitute in production. |
Stretch carpet to align with walls and ensure a smooth surface, and press carpet in place over tack strips or use staples, tape, tacks or glue to hold carpet in place.
7CI 5–10 · exposure 0 · augmentation 0 · importance 4.4/5 · click for rater detail
Stretch carpet to align with walls and ensure a smooth surface, and press carpet in place over tack strips or use staples, tape, tacks or glue to hold carpet in place.
7| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Carpet installation is a traditional trade in small firms and on-site settings with low digital integration. The sector has shown minimal AI or automation adoption; work remains labor-intensive and geographically dispersed, typical of laggard sectors. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Carpet installation is a small-business-dominated, physical trade with minimal digitization or AI adoption in the field to date. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | AI offers no meaningful assistance to a carpet installer performing this hands-on physical task. The work does not involve data analysis, documentation, or digital tools where AI could augment human capability in situ. |
| Augmentation potential | claude-sonnet-5 | 1/5 | AI provides no meaningful real-time assistance during the physical stretching and fastening process itself, though it might help with unrelated planning tasks elsewhere in the job. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires physical manipulation of carpet in a space—stretching, aligning, and fastening it to floors and walls. Current AI systems cannot perform end-to-end physical installation work; the task demands dexterity, spatial reasoning in real environments, and real-time material handling that robotic systems have not reliably automated at scale. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires physical manipulation of heavy, flexible material with precise force control, stretching tools (knee kickers, power stretchers), and tactile feedback to detect wrinkles and tension—no current AI system can perform this physical labor. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Carpet installation occurs in customers' homes and businesses, creating implicit human-contact and trust requirements. Building codes and warranty standards typically require licensed or certified installers to perform the work, and liability for floor defects creates error-cost asymmetry favoring human accountability. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement specifically bars automation, but the physical dexterity, judgment for uneven surfaces, and liability for poor installation create practical friction against non-human methods. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Current robotic systems capable of any part of carpet installation are prohibitively expensive to develop, deploy, and maintain compared to the loaded wage of a carpet installer. The capital and integration costs far exceed the labor savings. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI/robotic substitute performing this task, so the comparison defaults to AI being effectively infeasible and thus not cheaper by any measure. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed commercial product reliably performs carpet installation autonomously today. While robotics research exists, production systems capable of stretching carpet, navigating varied room geometries, and securing it with multiple fastening methods do not exist in real-world deployment. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed robotic or AI product installs carpet in real job sites; this remains entirely manual skilled trade work with no commercial automation offering. |
Related occupations — Construction & Extraction
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.