Helpers--Electricians

47-3013.00
Median wage $42,670/yr63,630 employed (US)Rank #794 of 923 scored · top 86% by substitution

Help electricians by performing duties requiring less skill. Duties include using, supplying, or holding materials or tools, and cleaning work area and equipment.

Sub-scores

0–100 · band = confidence interval from rater disagreement

Substitution15
Exposure8
Augmentation18

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

4%

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%9

panel mean rating 1.3/5 → substitution pressure 9/100

Technical feasibility todayw 20%7

panel mean rating 1.3/5 → substitution pressure 7/100

Cost vs. human wagew 15%6

panel mean rating 1.3/5 → substitution pressure 6/100

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%3

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

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.

Requisition materials, using warehouse requisition or release forms.

71

CI 70–72 · exposure 75 · augmentation 63 · importance 3.4/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510013/5Warehouse and field service sectors show moderate adoption of RPA and workflow automation, with pilots widespread but full production automation varying by firm size and legacy system integration challenges. Adoption is advancing but not yet at the speed seen in information-intensive roles.
Sector adoption velocityclaude-sonnet-52/5Construction and skilled trades sectors are generally slower adopters of digital and AI automation compared to information/professional services, though supply-chain digitization is increasing gradually.
Augmentation potentialclaude-haiku-4-5-202510013/5AI can assist by auto-populating form fields based on project codes or inventory data, checking material availability, and flagging errors—improving helper productivity without replacing the decision to request materials. The human retains oversight of what is ordered and why.
Augmentation potentialclaude-sonnet-54/5AI-enabled inventory and procurement tools can substantially speed up and reduce errors in the requisition process while a human still confirms final orders and handles exceptions.
Task automatabilityclaude-haiku-4-5-202510014/5The task of requisitioning materials using warehouse forms is largely a data-entry and form-filling task that current AI systems can automate end-to-end. With access to inventory systems and form templates, an AI agent could identify needed materials, populate requisition forms, and submit them—achieving >50% time savings compared to manual completion.
Task automatabilityclaude-sonnet-54/5Requisitioning materials via forms is a structured, repetitive data-entry/procurement task that current AI and workflow automation systems (e.g., inventory management software, e-procurement tools) can handle with minimal human input given predictable inputs like part numbers and job codes.
Adoption barriersclaude-haiku-4-5-202510012/5Few regulatory or legal barriers prevent automation of material requisitioning; it does not require a licensed professional signature. The main friction is organizational (internal process standardization, system access rights) rather than hard legal constraints.
Adoption barriersclaude-sonnet-52/5No licensing or safety-critical sign-off is required for this administrative task, though some organizational preference for human oversight of ordering may create mild friction.
Cost vs. human wageclaude-haiku-4-5-202510014/5The per-task cost of AI-driven automation (form filling, requisition submission) is substantially lower than paying a helper's loaded wage to perform the same requisition task. AI inference and integration costs are minimal for routine data-entry workflows.
Cost vs. human wageclaude-sonnet-54/5Automated requisition software or simple AI-driven form-filling/order systems cost far less per transaction than paying a human helper's time to manually fill and submit paperwork.
Technical feasibility todayclaude-haiku-4-5-202510014/5Deployed products (RPA systems, document processing tools, and workflow automation platforms) demonstrably handle requisition and inventory management at scale in production environments. Material errors are low when forms are well-structured and inventory systems are accessible, though integration complexity varies.
Technical feasibility todayclaude-sonnet-54/5Enterprise inventory and procurement systems with automated requisition workflows are already deployed widely in construction and trade supply chains, though some tasks still require human verification of quantities/specs for correct materials.

Clean work area and wash parts.

22

CI 15–29 · exposure 13 · augmentation 0 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Electrician shops and field service work are predominantly small, distributed operations with limited digitization and capital budgets. Adoption of cleaning automation in this sector is negligible; the work remains manual.
Sector adoption velocityclaude-sonnet-51/5Construction and skilled trades are among the least digitized sectors with minimal AI/robotics adoption for manual physical tasks like cleaning.
Augmentation potentialclaude-haiku-4-5-202510011/5Current AI and robotics offer no meaningful productivity assistance for manual cleaning and parts-washing tasks in an electrician's workshop context.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no productivity assistance for physical cleaning and washing tasks performed by helpers.
Task automatabilityclaude-haiku-4-5-202510012/5This task involves physical manipulation of tools and materials in a workshop environment, requiring spatial reasoning and dexterity. Current robotics can handle some cleaning in structured environments, but washing varied electrical parts with different shapes and materials remains challenging for deployed systems without significant setup.
Task automatabilityclaude-sonnet-51/5Physical cleaning of a job site and washing electrical parts requires manipulation, mobility, and perception in unstructured physical space that current AI systems cannot perform end-to-end.'
Adoption barriersclaude-haiku-4-5-202510012/5There are no strict licensing or legal barriers to automating cleaning and parts-washing; however, workshop integration challenges, space constraints, and the need for human judgment about what requires cleaning present practical friction.
Adoption barriersclaude-sonnet-52/5No licensing or regulatory requirement mandates a human for cleaning, but physical dexterity and site variability create practical barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Purchasing, integrating, and maintaining a robotic cleaning system for an electrician's helper role would far exceed the labor cost of a helper at typical loaded wages. The task is too low-value and context-dependent to justify capital investment.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic solution for this task at any deployable cost, so AI is effectively infinitely more expensive or simply unavailable compared to a low-wage helper.
Technical feasibility todayclaude-haiku-4-5-202510012/5While industrial cleaning robots exist, they are typically deployed in highly controlled settings (automotive plants, factories). Washing small, varied electrical components reliably in real electrician workshops remains primarily manual work; no mainstream product reliably handles this task's variability at scale.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs general job-site cleanup or parts washing for electrical work; this remains purely a human manual task.

Strip insulation from wire ends, using wire stripping pliers, and attach wires to terminals for subsequent soldering.

21

CI 10–33 · exposure 13 · augmentation 0 · importance 4.4/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5This task occurs primarily in skilled trades and field electrical work, sectors with low adoption of automation due to job variability, small job scales, and the need for human judgment. Most electrician helpers still perform this work manually, and adoption of robotics in this context remains negligible.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the lowest digitized, lowest AI-adoption sectors, with physical manual tasks like this seeing essentially no automation deployment.
Augmentation potentialclaude-haiku-4-5-202510011/5Current AI and automation tools offer no meaningful assistance to a helper stripping wire and attaching terminals; the task is fundamentally manual and requires real-time tactile feedback that AI systems cannot provide to augment human performance.
Augmentation potentialclaude-sonnet-51/5Current AI tools offer no meaningful real-time assistance for the physical act of stripping wires and attaching them to terminals; this is a purely manual craft task.
Task automatabilityclaude-haiku-4-5-202510012/5Wire stripping and terminal attachment require precise physical manipulation in three-dimensional space that current robotics can perform only in highly structured, repetitive settings. While automated stripping machines exist for industrial production lines, adapting them to the varied wire gauges, insulation types, and terminal configurations encountered by electrician helpers would require significant setup for each job, falling short of the 50% time-saving threshold for general practice.
Task automatabilityclaude-sonnet-51/5This requires physical dexterity to manipulate wires, strip insulation, and place them precisely on terminals in varied real-world job site conditions—current AI systems cannot perform this physical manipulation task at all.
Adoption barriersclaude-haiku-4-5-202510013/5While there are no strict licensing requirements preventing automation of this specific task, building code compliance, quality assurance standards, and organizational preference for human verification of electrical work create moderate friction; electricians or their supervisors typically inspect these connections before soldering.
Adoption barriersclaude-sonnet-52/5While electrical work often requires oversight by licensed electricians, this specific helper task itself isn't strictly licensed, though it occurs within regulated electrical installation contexts with safety and liability concerns.
Cost vs. human wageclaude-haiku-4-5-202510012/5Custom robotic solutions for wire stripping and terminal attachment are capital-intensive and require ongoing maintenance, making their per-task cost significantly higher than the wages of a helper electrician, especially when amortized across typical job volumes.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic system to compare costs against for this physical task in unstructured field settings, so a human remains the only cost-effective option today.
Technical feasibility todayclaude-haiku-4-5-202510012/5Specialized industrial equipment exists for wire stripping in controlled factory environments, but general-purpose robotic systems do not reliably perform this task with the dexterity and sensory feedback needed to avoid wire damage or poor terminal contact. Deployed robotic solutions are narrow in scope and require extensive customization, making them impractical for the variety of field work electrician helpers perform.
Technical feasibility todayclaude-sonnet-51/5No deployed consumer or commercial product performs manual wire stripping and terminal attachment in field electrical work; this remains a purely research-stage robotics challenge for unstructured environments.

Construct controllers and panels, using power drills, drill presses, taps, saws, and punches.

20

CI 10–30 · exposure 13 · augmentation 38 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Adoption is unevenly distributed: high-volume manufacturing plants use CNC and robotics, but most electrical shops and smaller contractors still rely on hand tools and helpers. Overall sector adoption of automation for panel construction remains moderate and fragmented.
Sector adoption velocityclaude-sonnet-51/5Electrical trades and construction are among the slowest sectors to adopt AI/robotics for physical fabrication tasks, with minimal digitization or automation penetration in this specific work.
Augmentation potentialclaude-haiku-4-5-202510013/5Power tools and digital layout aids can help a helper work faster and more accurately (e.g., CNC-guided drilling templates), and CAD-to-manufacturing software can reduce planning time. However, the task is already performed by hand with standard power tools, limiting the incremental productivity gains from AI assistance.
Augmentation potentialclaude-sonnet-52/5AI could assist with panel layout design or reading schematics digitally, but offers minimal help with the actual physical drilling, cutting, and punching operations described.
Task automatabilityclaude-haiku-4-5-202510012/5While some discrete steps (drilling, sawing) could be partially automated with CNC equipment, the task requires spatial reasoning, material handling, and assembly adjustments that are difficult to fully automate end-to-end. Current robotic systems struggle with variable panel geometries and the fine-grained quality control needed for electrical panels.
Task automatabilityclaude-sonnet-51/5This is a hands-on physical fabrication task requiring manual dexterity with power tools; no current AI system can perform physical drilling, tapping, and assembly work end-to-end.
Adoption barriersclaude-haiku-4-5-202510013/5Electrical panel construction is subject to safety codes and inspection requirements, but these do not mandate human performance—only that work meet standards. There is some organizational friction around integrating automation into existing helper workflows, but no hard licensing barrier prevents machine substitution.
Adoption barriersclaude-sonnet-53/5While not formally licensed work itself, electrical panel construction often occurs under supervision of licensed electricians and involves safety-critical wiring, creating moderate liability and oversight barriers, though the physical task itself has no legal licensing requirement for the helper role.
Cost vs. human wageclaude-haiku-4-5-202510012/5CNC equipment and industrial robots for panel construction are capital-intensive and require skilled technicians for setup and maintenance. For helper-level work on variable or custom panels, automation costs typically exceed the loaded wage of an electrician's helper.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical task, so AI cost comparison is not applicable; robotic solutions for this varied, low-volume fabrication work would be far more expensive than a helper electrician's wage.
Technical feasibility todayclaude-haiku-4-5-202510012/5Specialized industrial robots and CNC machines exist for some sub-tasks (drilling, cutting), but no deployed AI system reliably performs the full construction and assembly of controllers and panels. Most deployment remains in high-volume manufacturing with fixed designs, not the variable work implied here.
Technical feasibility todayclaude-sonnet-51/5No deployed products exist that autonomously construct electrical controllers and panels using power drills, drill presses, taps, and punches; this remains firmly in the human physical trades domain.

Bolt component parts together to form tower assemblies, using hand tools.

20

CI 10–30 · exposure 13 · augmentation 13 · importance 3.3/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5The construction and tower assembly sector has lagged in automation adoption compared to manufacturing or professional services. Most tower assembly remains predominantly manual, with slow pilot adoption of robotics in only the largest, standardized projects.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the least digitized, lowest-AI-adoption sectors, with physical assembly tasks seeing negligible robotic deployment.
Augmentation potentialclaude-haiku-4-5-202510012/5AI/robotic assistance for tower assembly is limited; AI vision systems can guide part positioning and check alignment, but the physical handling and problem-solving required for variable field conditions means augmentation tools remain nascent and provide only marginal productivity gains.
Augmentation potentialclaude-sonnet-51/5Current AI tools offer no meaningful real-time assistance for physical bolting and assembly work performed by hand.
Task automatabilityclaude-haiku-4-5-202510012/5Bolting component parts together requires fine motor control, spatial reasoning, and handling of varied physical components. While robotic assembly is possible in controlled manufacturing settings, adapting to variable tower geometries, misaligned parts, and field conditions remains challenging for current AI systems without significant human oversight.
Task automatabilityclaude-sonnet-51/5This is a physical manipulation task requiring hand-tool use, dexterity, and mobility around large structures; no off-the-shelf AI system can perform this end-to-end today.
Adoption barriersclaude-haiku-4-5-202510013/5Safety requirements, union representation in construction, and the need for on-site quality inspection create moderate friction to full automation. However, no explicit legal licensing barrier prevents robotic substitution, though workplace safety regulations and project specifications may mandate human oversight.
Adoption barriersclaude-sonnet-53/5No licensing requirement specifically bars automation, but safety regulations, jobsite liability, and physical unpredictability of construction environments create real friction against deploying autonomous systems.
Cost vs. human wageclaude-haiku-4-5-202510012/5Specialized robotic systems for assembly are capital-intensive with high setup and maintenance costs. For field-based tower assembly work, human helpers remain significantly cheaper than purchasing and maintaining robots, especially for one-off or small-batch jobs.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this task, so any hypothetical automation would require expensive custom robotics far exceeding human labor cost.
Technical feasibility todayclaude-haiku-4-5-202510012/5Robotic systems exist for assembly tasks in factories, but deploying them for tower assembly with variable part tolerances and field conditions requires substantial customization. Current deployed solutions handle highly standardized, repetitive assembly but struggle with the variability inherent in tower construction.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs bolting of tower assemblies autonomously in production; construction robotics for this specific task remain research-stage or absent.

Solder electrical connections, using soldering iron.

20

CI 10–30 · exposure 13 · augmentation 13 · importance 3.1/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5Adoption is confined largely to high-volume, standardized manufacturing environments. Field electricians and small-to-medium shops rarely deploy automated soldering; the work remains predominantly manual with minimal AI-driven displacement in the broader electrical installation sector.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the least digitized, lowest AI-adoption sectors, with physical hands-on tasks like this seeing negligible automation deployment.
Augmentation potentialclaude-haiku-4-5-202510012/5AI offers minimal assistance for the core soldering action itself. Machine vision for joint inspection or thermal guidance could provide marginal help, but current systems do not meaningfully raise productivity for a human performing soldering tasks.
Augmentation potentialclaude-sonnet-51/5Current AI tools offer no meaningful real-time assistance for the physical act of soldering; at most, unrelated documentation or scheduling tools might help peripherally but not this task directly.
Task automatabilityclaude-haiku-4-5-202510012/5Soldering requires precise 3D manipulation, real-time sensory feedback (heat control, joint inspection), and adaptation to component variations. While simple soldering has been partially automated in manufacturing, off-the-shelf AI systems cannot reliably perform this task end-to-end without human oversight to meet the 50% time-saving bar.
Task automatabilityclaude-sonnet-51/5This is a physical dexterity task requiring precise manual manipulation of a soldering iron on electrical connections in varied, often awkward physical environments; no off-the-shelf AI or robotic system can perform this end-to-end today.
Adoption barriersclaude-haiku-4-5-202510013/5Soldering work in electrical installation often requires licensed electricians to sign off on final connections for safety and code compliance, though helpers perform the mechanical task. Liability concerns around joint quality and safety create moderate friction to full automation.
Adoption barriersclaude-sonnet-53/5No licensing requirement specifically for soldering itself, but electrical work often falls under safety codes and supervision by licensed electricians, creating moderate procedural friction against unsupervised automation.
Cost vs. human wageclaude-haiku-4-5-202510012/5Specialized soldering robots and integrated systems are capital-intensive and require skilled technicians to maintain. The all-in cost (equipment, integration, oversight) exceeds the loaded wage of a skilled electrician's helper for most field and mixed-volume scenarios.
Cost vs. human wageclaude-sonnet-51/5Robotic soldering hardware plus setup, calibration, and site-specific engineering would vastly exceed the cost of a helper's hourly wage for this task.
Technical feasibility todayclaude-haiku-4-5-202510012/5Robotic soldering exists in controlled manufacturing settings but requires extensive setup, calibration, and typically operates on standardized boards. Deployed consumer or field-ready AI systems capable of reliable soldering across varied conditions and geometries are not mature or widely available in production.
Technical feasibility todayclaude-sonnet-51/5No deployed consumer/commercial product performs field electrical soldering autonomously; automated soldering exists only in controlled factory settings (PCB assembly lines), not in the variable jobsite contexts helpers work in.

Maintain tools, vehicles, and equipment and keep parts and supplies in order.

19

CI 5–33 · exposure 13 · augmentation 25 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Adoption of automation for tool and equipment maintenance in electrical trades remains minimal. These are hands-on, physical tasks in small to medium field operations with limited digitization and strong reliance on human technician judgment and safety accountability.
Sector adoption velocityclaude-sonnet-51/5Construction and trades support roles are among the least digitized sectors with minimal AI/robotics adoption for physical tool and inventory management.
Augmentation potentialclaude-haiku-4-5-202510012/5AI can assist with inventory tracking, maintenance reminders, and parts ordering systems, but offers limited augmentation for the core hands-on maintenance work itself. The primary value is administrative rather than transformative to the helper's core productivity.
Augmentation potentialclaude-sonnet-52/5Basic software (inventory tracking apps, maintenance scheduling tools) can assist in logging and reminders, but this offers only marginal productivity gains for the core physical task.
Task automatabilityclaude-haiku-4-5-202510012/5Physical tool and equipment maintenance requires hands-on inspection, repair, and organization in dynamic environments. While inventory tracking could be partially automated, the core maintenance tasks (cleaning, adjusting, replacing parts) remain largely manual and context-dependent, offering minimal end-to-end automation potential.
Task automatabilityclaude-sonnet-51/5This task involves physical maintenance of tools/vehicles, physical organization of parts and supplies, requiring manual dexterity and mobility that current AI cannot perform end-to-end.
Adoption barriersclaude-haiku-4-5-202510014/5Safety and liability are substantial barriers: electrical equipment maintenance requires proper certification and licensing in many jurisdictions, and errors can create fire/shock hazards. Organizational and regulatory requirements around tool accountability and maintenance standards further protect this task.
Adoption barriersclaude-sonnet-52/5No licensing requirement specifically bars automation, but the inherent physical nature of the work (robotics not deployed for this) creates a practical barrier rather than regulatory one.
Cost vs. human wageclaude-haiku-4-5-202510012/5Robotic systems capable of meaningful tool maintenance and equipment repair are expensive and require significant infrastructure. The cost per task-equivalent remains well above the loaded wage of a helper-electrician for most maintenance and organization subtasks.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute for the physical labor involved, so AI cost comparison is not applicable—the human remains the only cost-effective option.
Technical feasibility todayclaude-haiku-4-5-202510012/5Deployed products can handle basic inventory management and tracking, but no mainstream AI systems reliably perform physical maintenance, inspection quality assessment, or autonomous equipment repair at production scale in field conditions.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously maintains physical tools and equipment or physically organizes parts inventories; this remains a manual labor task.

Transport tools, materials, equipment, and supplies to work site by hand, handtruck, or heavy, motorized truck.

15

CI 15–15 · exposure 0 · augmentation 25 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Physical logistics at construction sites remain highly human-dependent with minimal AI adoption. The sector is labor-intensive and fragmented, with little evidence of autonomous systems replacing material transport on active job sites.
Sector adoption velocityclaude-sonnet-51/5Construction and skilled trades are among the least digitized sectors with minimal AI/robotics adoption for physical labor tasks like this one.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could assist with route planning or inventory tracking before transport, but offers minimal productivity enhancement for the core task of physically moving materials to a work site, which remains fundamentally manual.
Augmentation potentialclaude-sonnet-52/5AI can assist with route planning, inventory tracking, or scheduling deliveries, but offers little direct help with the physical act of transporting materials by hand or truck.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical movement and manual handling of objects in real-world environments. Current AI systems cannot operate robotic bodies reliably enough to transport tools and materials to job sites autonomously at the scale and flexibility required.
Task automatabilityclaude-sonnet-51/5This is a physical transport task requiring manipulation of tools and equipment across job sites, which current AI systems (including robotics) cannot perform end-to-end reliably or affordably.
Adoption barriersclaude-haiku-4-5-202510012/5While there are no strict licensing barriers, practical barriers include job-site safety regulations, insurance liability for autonomous vehicle operation, and the unpredictability of construction environments that make automated solutions difficult to deploy legally and safely.
Adoption barriersclaude-sonnet-52/5No licensing requirement for hauling materials, but physical site variability, vehicle operation, and safety practices create practical friction against automation despite no legal barrier.
Cost vs. human wageclaude-haiku-4-5-202510011/5A human helper with a truck costs significantly less than acquiring, operating, and maintaining robotic systems capable of autonomous job-site logistics, particularly given the need for oversight and fallback to human handling.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI system to compare cost against for this task; a human laborer or driver remains far cheaper than any experimental robotic alternative.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed commercial product reliably performs end-to-end transportation of tools and materials to electrical work sites. While warehouse robots exist for controlled environments, the variability of construction sites and the need for human judgment about what to transport make this infeasible for current AI.
Technical feasibility todayclaude-sonnet-51/5No deployed AI/robotic product autonomously transports construction tools and materials via handtruck or vehicle at job sites; this remains research-stage for mobile manipulation robotics.

Paint a variety of objects related to electrical functions.

15

CI 15–15 · exposure 0 · augmentation 0 · importance 3.1/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Electrical helper roles are concentrated in small firms and on-site work with low digitization; adoption of painting automation in this context is minimal and lagging significantly behind other sectors.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the least digitized sectors with minimal AI/robotics adoption for physical manual tasks like painting.
Augmentation potentialclaude-haiku-4-5-202510011/5Current AI offers no meaningful assistance for the core task of painting physical objects; no vision-guided or robotic augmentation tools are available to enhance a human painter's productivity in this context.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no assistance for the physical act of painting electrical components on site.
Task automatabilityclaude-haiku-4-5-202510011/5Painting objects requires dexterous manipulation, precise brush/spray control, and real-time visual feedback in varied physical environments. Current AI systems cannot autonomously perform this fine motor task end-to-end with quality equivalent to human painters.
Task automatabilityclaude-sonnet-51/5Painting physical electrical enclosures, conduit, or equipment requires manual dexterity and physical presence that current AI systems cannot perform; robotics for this niche task are not deployed.'
Adoption barriersclaude-haiku-4-5-202510012/5While no strict licensing requirement exists for painting electrical objects, organizational friction around equipment investment and setup, plus customer expectations for human craftsmanship, present moderate adoption barriers.
Adoption barriersclaude-sonnet-52/5No licensing specifically restricts painting tasks, but physical site access and manual skill create practical barriers to any automated substitution.
Cost vs. human wageclaude-haiku-4-5-202510011/5Robotic painting systems capable of this work are capital-intensive ($500k+), require specialized infrastructure, and ongoing maintenance—far exceeding the loaded wage of a helper for typical electrical painting tasks.
Cost vs. human wageclaude-sonnet-51/5There is no AI-based substitute for this physical labor, so the human remains the only cost-effective option.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed robotic or AI product reliably paints electrical objects in real-world conditions at production scale. While industrial robots exist for standardized painting, none are general-purpose systems available to electrician helpers today.
Technical feasibility todayclaude-sonnet-51/5No commercial product exists that autonomously paints electrical objects on job sites; this remains purely a manual trade task.

Measure, cut, and bend wire and conduit, using measuring instruments and hand tools.

14

CI 5–24 · exposure 13 · augmentation 25 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Electricians and their helpers work on distributed job sites with high variability; adoption of specialized robotics in this blue-collar, physical trade remains minimal. The sector is characterized by small firms, legacy practices, and limited capital investment in automation.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the least digitized, most physically-oriented sectors with minimal AI/robotic adoption for manual fabrication tasks.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could assist by providing real-time measurement validation or providing bend-angle guidance via computer vision, but hands-on manipulation and judgment remain human-dominated. Assistance is narrow and does not substantially amplify helper productivity on the core task.
Augmentation potentialclaude-sonnet-52/5AI-powered measuring tools or laser levels can assist marginally, but there is little software-based augmentation for the core physical cutting and bending work itself.
Task automatabilityclaude-haiku-4-5-202510012/5While AI-guided robots can theoretically measure and cut materials, end-to-end automation of wire/conduit bending with hand tools requires tactile feedback, real-time spatial reasoning, and adaptation to variable physical materials—capabilities current systems lack at production scale. Partial automation (measurement via vision) exists but does not meet the 50% time-saving threshold for the full task.
Task automatabilityclaude-sonnet-51/5This is a physical manipulation task requiring hand-eye coordination and tool use in variable job-site conditions; no off-the-shelf AI system can perform this end-to-end today.
Adoption barriersclaude-haiku-4-5-202510014/5Electrical work is licensed and often requires on-site inspection and sign-off by licensed electricians; automation must be overseen by qualified personnel, and liability for defective bends/cuts falls on the organization. Safety codes and quality standards create regulatory oversight friction.
Adoption barriersclaude-sonnet-53/5No licensing specifically required for this sub-task, but it occurs within regulated electrical work environments with safety and code compliance expectations that create organizational friction against unproven automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Current robotic and vision systems capable of handling wire/conduit work are expensive to acquire, integrate, and maintain, while a helper electrician's wage remains low. The all-in cost per task instance remains above human labor cost.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this physical task, so any hypothetical automation would require expensive custom robotics far exceeding human labor cost for this work.
Technical feasibility todayclaude-haiku-4-5-202510012/5Vision-based measurement systems exist in research and limited industrial settings, but reliable production systems for the complete cut-and-bend workflow with hand tools are not widely deployed in electrician workflows. No mature off-the-shelf product reliably automates this end-to-end in typical job-site conditions.
Technical feasibility todayclaude-sonnet-51/5No deployed consumer or industrial product measures, cuts, and bends conduit/wire autonomously in field electrical work; this remains beyond current robotics products in unstructured settings.

Perform semi-skilled and unskilled laboring duties related to the installation, maintenance and repair of a wide variety of electrical systems and equipment.

14

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

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Helper-electrician roles are predominantly in small and mid-sized contractors with low IT spending and distributed job sites; adoption of automation in this sector remains minimal despite digitization of scheduling and documentation tools.
Sector adoption velocityclaude-sonnet-51/5Construction and skilled trades are among the slowest sectors to adopt AI/automation, with very low digitization and reliance on physical human labor.
Augmentation potentialclaude-haiku-4-5-202510012/5AI can modestly assist through image recognition for equipment identification and defect detection, or automated documentation, but these are peripheral to the core physical labor and inspection tasks that define most of the work.
Augmentation potentialclaude-sonnet-52/5AI can help with scheduling, documentation, or diagnostic support tools used by electricians, but offers minimal direct assistance to the physical laboring duties themselves.
Task automatabilityclaude-haiku-4-5-202510012/5While AI vision systems could assist with inspection and documentation of electrical systems, the core laboring duties—physical installation, maintenance, and repair of equipment—require hands-on manipulation in real-world conditions that current robotics cannot reliably perform at scale or cost parity.
Task automatabilityclaude-sonnet-51/5This is physical manual labor involving handling materials, running conduit, and assisting with electrical installation on job sites, which current AI cannot perform without embodied robotics far beyond deployed capability.
Adoption barriersclaude-haiku-4-5-202510014/5Electrical work is heavily regulated and licensed; jurisdictions require licensed electricians to supervise or perform electrical installations, and liability for faulty work creates strong legal and organizational barriers to full automation.
Adoption barriersclaude-sonnet-52/5No licensing is required for helper-level laborers, but physical worksite variability and safety concerns around electrical equipment create practical friction against automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5The hardware, software, and ongoing oversight costs for robotic systems capable of electrical installation and repair far exceed the loaded wage of a helper-electrician, making AI substitution economically infeasible today.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute for this physical task, so any hypothetical automation would be far more expensive than a human helper's wage.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed products reliably perform the full range of semi-skilled electrical installation and repair work in production settings; robotics for complex electrical tasks remain largely research-stage with significant safety and dexterity limitations.
Technical feasibility todayclaude-sonnet-51/5No deployed AI or robotic product performs general semi-skilled electrical helper labor in real work sites today; this remains far outside current robotics deployment.

Break up concrete, using airhammer, to facilitate installation, construction, or repair of equipment.

13

CI 10–15 · exposure 0 · augmentation 0 · importance 2.9/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Construction remains a low-digitization, largely manual sector with slow adoption of automation. Helpers breaking concrete are primarily in small-to-medium job sites where capital investment in specialized robots is economically infeasible.
Sector adoption velocityclaude-sonnet-51/5Construction and skilled trades are among the slowest sectors to adopt AI/robotics for physical manual tasks, with minimal production deployment of automated demolition tools.
Augmentation potentialclaude-haiku-4-5-202510011/5AI cannot meaningfully assist a human in operating an airhammer or provide guidance that would substantially improve the speed or quality of manual concrete breaking, as the task is already straightforward physical labor.
Augmentation potentialclaude-sonnet-51/5Current AI offers no meaningful assistance to a worker physically operating an airhammer to break concrete; this is a purely manual, physical task.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical manipulation of heavy pneumatic tools in variable, on-site conditions to break concrete in ways that support subsequent electrical work. Current AI systems cannot operate physical tools in unstructured environments; it remains a manual labor task.
Task automatabilityclaude-sonnet-51/5This is a physical demolition task requiring manual manipulation of a heavy pneumatic tool against variable material; no AI system can perform this physical labor today.
Adoption barriersclaude-haiku-4-5-202510012/5While there is no formal licensing requirement for airhammer operation by helpers, significant practical barriers exist: site safety protocols, equipment familiarity, and the need for on-site physical presence and situational judgment in variable conditions.
Adoption barriersclaude-sonnet-53/5No licensing barrier specifically bars automation, but safety regulations, jobsite liability, and physical unpredictability of demolition work create practical friction against substituting equipment operators.
Cost vs. human wageclaude-haiku-4-5-202510011/5Specialized construction robots capable of concrete breaking are expensive capital equipment with high setup and maintenance costs, far exceeding the loaded wage of a helper performing this task manually.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute deployed at scale, so cost comparison favors the human worker entirely; any robotic alternative would require expensive specialized hardware exceeding human labor costs.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI system can autonomously operate an airhammer or perform concrete breaking in real construction settings. Robotics for this task exist only in research or highly controlled industrial environments, not in production use on job sites.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs concrete breaking with an airhammer; this remains purely a human physical task, robotics for this are at best experimental in narrow contexts.

Examine electrical units for loose connections and broken insulation and tighten connections, using hand tools.

12

CI 5–19 · exposure 8 · augmentation 25 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Adoption of AI/robotics for this task remains minimal; the skilled trades sector is characterized by small firms, on-site physical work, and low digitization, creating organizational and technological resistance to automation.
Sector adoption velocityclaude-sonnet-51/5Electrical trades and physical field labor are among the slowest sectors for AI/robotic adoption, with minimal deployment of automation for hands-on maintenance tasks.
Augmentation potentialclaude-haiku-4-5-202510012/5AI tools could provide modest assistance through computer vision for identifying loose connections or damaged insulation, but the primary work—physical manipulation and judgment about tightness and safety—remains with the human worker, limiting transformative productivity gain.
Augmentation potentialclaude-sonnet-52/5AI could assist with diagnostics via thermal imaging analysis or documentation, but offers little help with the core physical task of inspecting and tightening connections.
Task automatabilityclaude-haiku-4-5-202510012/5This task requires physical manipulation of small components, visual inspection for damage, and tactile feedback to detect loose connections—capabilities current AI systems largely lack in unstructured field settings. While computer vision could assist with identifying broken insulation, the end-to-end execution of tightening connections with appropriate force requires dexterous robotics not yet reliable in production.
Task automatabilityclaude-sonnet-51/5This requires physical manipulation—examining wiring, feeling for looseness, and tightening connections with hand tools in varied real-world environments—which current AI systems cannot perform end-to-end.
Adoption barriersclaude-haiku-4-5-202510014/5Significant barriers exist: electrical work often requires licensing in many jurisdictions, safety liability falls on whoever certifies the work, and industry regulations typically require qualified human sign-off on electrical repairs for code compliance and insurance purposes.
Adoption barriersclaude-sonnet-53/5While no formal licensing is typically required for helpers, electrical work carries safety and liability risks (shock, fire hazards) that create strong practical barriers to unsupervised automation, plus physical dexterity requirements.
Cost vs. human wageclaude-haiku-4-5-202510011/5Current robotic systems capable of electrical inspection and repair are extremely expensive to acquire, maintain, and deploy compared to the wage of an electrician's helper, making substitution economically unfeasible at scale.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this physical task, so any hypothetical automation would require expensive specialized robotics far costlier than a helper's wage.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI products reliably perform this task independently today. While robotic arms exist in controlled lab settings, there are no production systems that autonomously examine, diagnose, and repair electrical connections in the field without human oversight.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs physical electrical inspection and tightening tasks; robotics for fine manual electrical work remains research-stage and not commercially deployed for this purpose.

Drill holes and pull or push wiring through openings, using hand and power tools.

12

CI 5–19 · exposure 8 · augmentation 25 · importance 4.1/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Electrical installation remains a physical, on-site trade with low digitization and limited AI agent deployment; adoption patterns show no meaningful shift toward autonomous drilling and wiring in production.
Sector adoption velocityclaude-sonnet-51/5Construction and trades are among the least digitized, lowest AI/robotics adoption sectors, with physical dexterity tasks like this seeing negligible automation investment or deployment.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could assist with route planning or layout visualization, but the core physical task of drilling and pulling wire offers limited augmentation opportunities; the helper remains responsible for the actual mechanical work.
Augmentation potentialclaude-sonnet-52/5AI offers minimal direct assistance for the physical drilling/pulling itself, though tools like layout planning apps or stud-finder integrations could marginally help planning, not execution.
Task automatabilityclaude-haiku-4-5-202510012/5This task requires physical manipulation of tools and materials in three-dimensional space with precision and adaptation to varying conditions. Current AI lacks the dexterous robotic embodiment needed to reliably drill holes and thread wiring through openings; specialized robots exist but are not general-purpose end-to-end solutions meeting the 50% time-saving bar.
Task automatabilityclaude-sonnet-51/5This is a physical manipulation task requiring drilling, precise hand-eye coordination, and pulling wire through walls/conduit in varied physical environments; no AI system today can perform this end-to-end.itude, it requires embodied robotics far beyond current capability.
Adoption barriersclaude-haiku-4-5-202510014/5Electrical work is heavily regulated and often requires licensed electricians or supervised helpers under close human oversight; liability for installation faults is high and legally assigned to qualified personnel, creating strong barriers to full automation.
Adoption barriersclaude-sonnet-53/5No licensing barrier specific to this subtask alone, but physical worksite access, safety codes, and building electrical code compliance create moderate organizational and regulatory friction against unproven automated methods.
Cost vs. human wageclaude-haiku-4-5-202510011/5Specialized robotic systems capable of this work are expensive to acquire, program, and maintain, far exceeding the loaded wage cost of a helper electrician performing these tasks.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this physical task, so cost comparison favors the human helper by default since no automated alternative exists at any price point for general settings.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed commercial products reliably perform drilling and wiring tasks autonomously in unstructured electrical installation environments. Robotic solutions for these subtasks exist only in research or highly controlled settings, not in production at scale.
Technical feasibility todayclaude-sonnet-51/5No deployed products perform electrical drilling and wire-pulling in real construction/maintenance settings; this remains outside current robotics deployment even in research demos for unstructured environments.

Dig trenches or holes for installation of conduit or supports.

12

CI 5–19 · exposure 0 · augmentation 13 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Electrical helper roles are concentrated in small and mid-sized firms with low capital investment in automation; adoption of autonomous trenching remains nascent and confined to specialized high-volume projects.
Sector adoption velocityclaude-sonnet-51/5Construction and skilled trades are among the slowest sectors for AI/robotic adoption due to physical, unstructured environments and low digitization.
Augmentation potentialclaude-haiku-4-5-202510012/5AI/GPS-guided equipment can assist with locating and planning trench routes, but the physical task itself is not substantially augmented by current AI tools—workers remain the primary execution agents.
Augmentation potentialclaude-sonnet-51/5Current AI offers no meaningful real-time assistance for physical digging; planning software may help with logistics but not the task itself.
Task automatabilityclaude-haiku-4-5-202510011/5Digging trenches or holes requires physical manipulation of earth in varied outdoor/ground conditions, navigation of obstacles, and real-time adjustment to soil composition. Current AI systems cannot operate autonomous heavy machinery or perform unstructured excavation reliably.
Task automatabilityclaude-sonnet-51/5Digging trenches/holes is a physical excavation task requiring embodied manipulation of tools or machinery in variable terrain; no general AI system can perform this end-to-end today.
Adoption barriersclaude-haiku-4-5-202510014/5Trenching near utilities and structures typically requires licensed locating services, permits, and on-site supervision due to safety liability and regulatory compliance; human oversight of underground work is often legally or contractually mandated.
Adoption barriersclaude-sonnet-52/5No licensing specifically required for digging, but utility-locating regulations, safety codes, and site conditions create moderate procedural friction even for human workers.
Cost vs. human wageclaude-haiku-4-5-202510012/5Heavy equipment operation (backhoe, trencher) requires significant capital and fuel costs; human laborers remain cheaper per hour for small-scale electrical conduit installation, though costs approach parity in high-volume standardized work.
Cost vs. human wageclaude-sonnet-51/5There is no AI-driven system substituting for this labor, so the comparison defaults to AI being effectively unavailable/more costly than a human laborer with a shovel or trencher.
Technical feasibility todayclaude-haiku-4-5-202510011/5While autonomous excavation equipment exists in controlled settings (mining, construction), reliable deployment for variable trench digging in urban/suburban electrical work with utility locating requirements remains research-stage and not yet a standard product in widespread use.
Technical feasibility todayclaude-sonnet-51/5No deployed AI product autonomously digs trenches for electrical installations; excavation is done by humans with hand tools or human-operated machinery.

Thread conduit ends, connect couplings, and fabricate and secure conduit support brackets, using hand tools.

10

CI 5–15 · exposure 0 · augmentation 13 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Construction and electrical trades remain low-digitization, physically distributed sectors with limited infrastructure for robotic automation. Adoption of AI-driven systems in helper tasks is minimal; manual labor remains the standard practice.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the least digitized, lowest AI-adoption sectors, with physical tool-based tasks seeing negligible AI deployment.
Augmentation potentialclaude-haiku-4-5-202510012/5AI offers limited assistance for conduit threading and bracket fabrication; while planning tools or design software might help layout, the hands-on assembly itself is difficult to augment without removing the worker from direct task control. Marginal benefit over human expertise.
Augmentation potentialclaude-sonnet-51/5Current AI tools offer no meaningful real-time assistance for manual conduit threading, coupling, or bracket fabrication using hand tools.
Task automatabilityclaude-haiku-4-5-202510011/5Threading conduit, connecting couplings, and fabricating brackets require precise spatial manipulation, dexterous hand-tool operation, and real-time tactile feedback in constrained physical environments. Current AI systems lack embodied robotics capabilities deployed at scale to perform these fine motor tasks reliably.
Task automatabilityclaude-sonnet-51/5This is a physical manual task requiring threading conduit, connecting couplings, and fabricating brackets with hand tools in variable job-site conditions; no current AI system can perform this physical labor.
Adoption barriersclaude-haiku-4-5-202510014/5Electrical conduit work is regulated by building codes and often requires licensed or certified electricians to supervise or perform critical connections; safety and liability concerns around improper installation create legal barriers to full automation. Human sign-off is typically required.
Adoption barriersclaude-sonnet-52/5No licensing barrier specifically blocks automation of this subtask, but physical site variability, tool manipulation, and safety concerns create substantial practical friction against automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5The capital and integration costs of robotic systems capable of dexterous hand-tool operation far exceed the loaded wage of a skilled electrician's helper. The task demands low-volume, site-specific customization that favors human labor economics.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute deployed for this task, so any hypothetical automation would require expensive specialized robotics far costlier than a helper's wage.
Technical feasibility todayclaude-haiku-4-5-202510011/5No commercial products demonstrate reliable, autonomous performance of threaded conduit assembly and bracket fabrication in real job sites. This requires integrated robotic manipulation with force sensing and fine positional control that remains largely in research or specialized industrial settings, not general deployment.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs conduit threading or bracket fabrication; this remains purely a research-stage robotics challenge, if that, given the unstructured environments involved.

Trim trees and clear undergrowth along right-of-way.

10

CI 5–15 · exposure 0 · augmentation 13 · importance 3.7/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Utility and vegetation management sectors remain heavily reliant on human crews and traditional heavy equipment; adoption of autonomous systems for this task is negligible in current data.
Sector adoption velocityclaude-sonnet-51/5placeholder
Augmentation potentialclaude-haiku-4-5-202510012/5AI could assist with route planning or hazard identification via imagery analysis, but the core physical task of trimming and clearing offers limited augmentation value while humans remain in control.
Augmentation potentialclaude-sonnet-51/5placeholder
Task automatabilityclaude-haiku-4-5-202510011/5Tree trimming and undergrowth clearing require physical manipulation in variable outdoor environments with safety hazards. Current AI systems lack the embodied robotics, dexterity, and environmental adaptation needed to perform this task reliably.
Task automatabilityclaude-sonnet-51/5This is a physical outdoor manual labor task requiring mobility, dexterity, use of power tools like chainsaws, and navigation of variable terrain, none of which current AI systems can perform end-to-end."},"feasibility":{"rating":1,"rationale":"No deployed AI product performs vegetation clearing and tree trimming autonomously; this remains a manual field task done by humans or, rarely, specialized non-AI machinery."},"cost_ratio":{"rating":1,"rationale":"There is no viable AI-driven substitute for this physical task, so AI cost is effectively infinite relative to human labor cost for the same output."},"barriers":{"rating":2,"rationale":"No licensing requirement specifically for this task, but safety regulations around utility right-of-way work and use of equipment create some procedural friction."},"adoption_velocity":{"rating":1,"rationale":"Manual outdoor labor and utility maintenance sectors show minimal AI adoption; this work remains highly physical and low-digitization."},"augmentation":{"rating":1,"rationale":"AI offers essentially no meaningful assistance for the physical act of trimming trees or clearing brush in the field."}} }}```wait fix format.。Actually let me output correct JSON only.{
Adoption barriersclaude-haiku-4-5-202510014/5Physical safety hazards, liability for damage to electrical lines and property, and requirement for skilled human judgment on what to trim make this task heavily resistant to full automation. Regulatory oversight of right-of-way work adds friction.
Adoption barriersclaude-sonnet-52/5placeholder
Cost vs. human wageclaude-haiku-4-5-202510011/5Autonomous systems capable of this work would require expensive specialized robotics, terrain navigation, and safety systems—far exceeding the cost of human labor for vegetation management.
Cost vs. human wageclaude-sonnet-51/5placeholder
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed commercial products perform autonomous tree trimming and vegetation clearing at scale. This task remains in the domain of specialized heavy equipment operators and crews, not AI systems.
Technical feasibility todayclaude-sonnet-51/5placeholder

Disassemble defective electrical equipment, replace defective or worn parts, and reassemble equipment, using hand tools.

9

CI 5–14 · exposure 0 · augmentation 25 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5The electrical trade remains a physical, hands-on sector with limited automation adoption. Disassembly and reassembly tasks are performed by small firms and field technicians with minimal digital infrastructure, placing this in a laggard sector for AI/automation penetration.
Sector adoption velocityclaude-sonnet-51/5Electrical trades and physical repair work are a low-digitization, low-AI-adoption sector with minimal deployment of AI/robotics for hands-on repair tasks.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could assist with diagnostics (identifying what to replace) via computer vision or historical data, but the core manual disassembly and reassembly work itself offers minimal augmentation potential since it is fundamentally a physical task requiring dexterity and spatial reasoning.
Augmentation potentialclaude-sonnet-52/5AI could assist with diagnostic guidance, parts lookup, or repair manuals via mobile apps, but offers little direct help with the physical disassembly/reassembly work itself.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical manipulation of components with hand tools in variable, real-world contexts. Current AI systems lack embodied capabilities to reliably locate, extract, replace, and reassemble electrical parts with the precision and adaptability needed, making end-to-end automation infeasible today.
Task automatabilityclaude-sonnet-51/5This is a physical manipulation task requiring dexterity, mobile hand tool use, and adaptive troubleshooting in varied environments; no current AI system can perform this end-to-end.
Adoption barriersclaude-haiku-4-5-202510014/5Electrical work on safety-critical equipment faces regulatory oversight and liability concerns; moreover, the task inherently requires physical interaction in varied, unstructured environments where human judgment about safety and equipment-specific context is legally and practically essential.
Adoption barriersclaude-sonnet-53/5While not always requiring a licensed electrician, safety concerns around live equipment, liability for faulty repairs, and physical workplace requirements create meaningful friction against automation.
Cost vs. human wageclaude-haiku-4-5-202510012/5Robotic systems capable of fine-grained disassembly and reassembly would require significant capital investment and integration costs that currently exceed the loaded wage of a helper-electrician for equivalent output.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute performing this task, so any hypothetical automation would require expensive custom robotics far exceeding human labor costs.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed commercial robotic or AI system reliably performs this task autonomously in production. While research exists on robotic disassembly, deployed systems are not performing electrical equipment maintenance at scale in real organizations.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs disassembly, part replacement, and reassembly of electrical equipment; humanoid robotics for such unstructured manual tasks remains research-stage.

Operate heavy equipment, such as backhoes.

9

CI 5–14 · exposure 8 · augmentation 25 · importance 2.6/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Adoption of autonomous backhoes in electrician-helper contexts is negligible. The construction and utilities sectors remain relatively low-digitization domains, with manual operation the norm and autonomous equipment confined to specialized, supervised mining or quarry use cases.
Sector adoption velocityclaude-sonnet-51/5Construction and skilled trades are among the slowest sectors to adopt AI/autonomous machinery, with physical, decentralized job sites and low digitization impeding rollout.
Augmentation potentialclaude-haiku-4-5-202510012/5Augmentation potential is limited: AI could assist via real-time sensor feedback (proximity warnings, slope analysis) or teleoperation interfaces, but the core skill—precise maneuvering under dynamic jobsite constraints—remains human-dependent. Modest improvement in safety monitoring is possible but not transformative.
Augmentation potentialclaude-sonnet-52/5Some assistive technologies (GPS grade control, cameras, sensors) aid precision in equipment operation, but these are equipment-specific enhancements rather than general AI assistance, and adoption among helpers is limited.
Task automatabilityclaude-haiku-4-5-202510012/5Heavy equipment operation like backhoes involves real-time spatial reasoning, obstacle avoidance, and precise maneuvering in unstructured environments. While some autonomous earthmoving exists in controlled quarries, general jobsite operation—coordinating with other workers, adapting to changing terrain and conditions—remains beyond reliable current AI, and the safety liability is prohibitive.
Task automatabilityclaude-sonnet-51/5Operating a backhoe requires real-time physical manipulation of heavy machinery in variable outdoor terrain, which current AI systems cannot perform end-to-end; teleoperation/autonomy exists only in narrow research/pilot contexts.
Adoption barriersclaude-haiku-4-5-202510014/5Equipment operation near underground utilities, other workers, and public spaces invokes significant liability and safety regulation. Jobsite standards, insurance, and worker coordination requirements create organizational and legal friction against unsupervised autonomous operation.
Adoption barriersclaude-sonnet-54/5Operating heavy equipment on job sites typically requires certification/training, safety regulations (OSHA), and liability concerns for equipment damage or injury, creating strong barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Current autonomous or tele-operated heavy equipment solutions are research-stage or niche applications. The integration, redundancy, and safety infrastructure required far exceed the hourly loaded cost of a skilled equipment operator, making AI economically infeasible today.
Cost vs. human wageclaude-sonnet-51/5Autonomous heavy equipment systems require expensive sensor suites, integration, and safety oversight, making them costlier than a human operator for this occasional, low-volume task.
Technical feasibility todayclaude-haiku-4-5-202510011/5No commercial product reliably operates a backhoe end-to-end in typical electrical helper contexts (jobsite excavation, trenching near utilities). Autonomous construction equipment exists only in specialized, controlled settings and does not meet production-grade reliability for substituting a human operator in the field.
Technical feasibility todayclaude-sonnet-51/5No deployed consumer or industry product allows an AI to autonomously operate a backhoe for general construction/utility work; autonomous excavation remains experimental (e.g., mining/quarry demos) and not used by electrician helpers.

String transmission lines or cables through ducts or conduits, under the ground, through equipment, or to towers.

7

CI 5–10 · exposure 0 · augmentation 13 · importance 3.8/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5The electrical trades remain heavily manual and on-site; digitization and automation adoption in this sector are slow. Cable stringing is fundamentally a physical, field-based task with high logistical variation.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the least digitized, slowest-adopting sectors for AI and robotics, with this manual task showing no meaningful automation trend.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could assist with pre-planning routing through conduit maps or highlighting potential hazards via computer vision of the workspace, but the core task of physically threading cables offers limited augmentation opportunity.
Augmentation potentialclaude-sonnet-51/5Current AI tools offer no meaningful real-time assistance for the physical act of pulling and routing cables through ducts or conduits.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical manipulation of heavy cables through constrained spaces, routing decisions based on visual inspection, and situational adaptation—capabilities far beyond current AI systems. No meaningful automation exists for the embodied, spatial reasoning required.
Task automatabilityclaude-sonnet-51/5This is a physical manual labor task requiring pulling and threading cables through conduits, underground ducts, or up towers, which current AI systems cannot perform without a robotic embodiment far beyond present capability.
Adoption barriersclaude-haiku-4-5-202510014/5Electrical work has licensing and safety regulations (NEC codes, OSHA requirements), and transmission line work typically requires certified personnel oversight. Physical presence and human judgment at the worksite create strong barriers to full automation.
Adoption barriersclaude-sonnet-53/5No licensing barrier specifically blocks automation, but safety regulations, physical site access, and liability for utility work create real practical friction against introducing untested automated systems.
Cost vs. human wageclaude-haiku-4-5-202510011/5The cost of specialized robotics or autonomous systems capable of navigating constrained conduit paths and handling transmission cable would far exceed the loaded wage of a helper electrician performing this labor.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute for this physical task, so any hypothetical automation would require expensive custom robotics far costlier than human labor today.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product autonomously performs cable stringing through ducts and conduits at scale. This remains entirely manual work in production environments; robotics for this specific task are not mature or widely available.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs cable pulling/stringing through ducts or towers; this remains firmly in human-only physical labor territory with no robotic analog in production.

Install copper-clad ground rods, using a manual post driver.

7

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

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Electrical field work remains largely unmechanized and low-digitization; adoption of robotics in this sector is minimal. Helpers and apprentices continue to perform this work using traditional manual methods.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the slowest sectors to adopt AI/robotics for physical fieldwork, with minimal automation of manual installation tasks.
Augmentation potentialclaude-haiku-4-5-202510011/5AI offers no meaningful assistance for the core task of physically driving ground rods; the work does not involve data analysis, decision support, or information processing where AI could augment human capability.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no assistance for the physical act of driving a ground rod with a manual post driver.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical manipulation of heavy equipment (manual post driver) and precise placement of ground rods in outdoor terrain. Current AI systems cannot perform end-to-end physical tasks of this complexity without specialized robotics, which are not generally deployed for electrical field work.
Task automatabilityclaude-sonnet-51/5This is a physical manual labor task requiring driving a metal rod into the ground with a hand tool; no current AI system can perform this physical action.
Adoption barriersclaude-haiku-4-5-202510014/5Electrical work is heavily regulated and often requires licensed electricians or qualified helpers under supervision; liability for improper grounding is high given safety and fire risks. Many jurisdictions require human certification and sign-off on electrical installations.
Adoption barriersclaude-sonnet-53/5No licensing specifically requires a human for this exact subtask, but electrical work often falls under broader trade regulations and jobsite safety practices that favor trained human workers.
Cost vs. human wageclaude-haiku-4-5-202510011/5Specialized robotics capable of this task would be orders of magnitude more expensive to purchase, deploy, and maintain than the loaded wage of an electrician's helper performing the work directly.
Cost vs. human wageclaude-sonnet-51/5There is no AI substitute for this physical installation task, so any AI-based approach would require expensive robotic hardware far exceeding human labor costs.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI systems or robotics products currently perform ground rod installation at scale. This remains a manual, hands-on task performed by human workers in production electrical installations.
Technical feasibility todayclaude-sonnet-51/5No deployed product exists that autonomously drives ground rods; this remains outside the scope of AI/robotics products in production.

Raise, lower, or position equipment, tools, and materials, using hoist, hand line, or block and tackle.

7

CI 5–10 · exposure 0 · augmentation 0 · importance 3.4/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Construction and electrical trades remain in laggard sectors for AI adoption due to physical site constraints, safety-critical operations, and the necessity of human judgment in real-time hazard assessment. Meaningful automation adoption in this domain is minimal today.
Sector adoption velocityclaude-sonnet-51/5Construction and trades are among the slowest sectors to adopt AI/robotics for physical tasks, with adoption for on-site manual material handling essentially nonexistent.
Augmentation potentialclaude-haiku-4-5-202510011/5AI offers no meaningful assistance in the core physical task of operating hoists and positioning equipment. Human operators remain the primary agent, and no AI tools demonstrably improve their productivity for this specific mechanical task.
Augmentation potentialclaude-sonnet-51/5AI offers essentially no assistance for the physical act of raising or lowering equipment with hoists or block and tackle.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical manipulation of equipment in a real-world environment using cranes, hand lines, or block-and-tackle systems. Current AI systems lack embodied robotics and real-time spatial reasoning at the precision and safety level needed for reliable autonomous execution of positioning tasks on worksites.
Task automatabilityclaude-sonnet-51/5This is a physical manipulation task requiring hands-on operation of hoists and rigging equipment; no current AI system can perform this physical work.
Adoption barriersclaude-haiku-4-5-202510014/5OSHA regulations and jobsite safety standards typically require human operators for hoists and rigging equipment, with licensed operators and spotters mandated for certain load weights and configurations. Liability for dropped loads and worker safety creates strong legal barriers to autonomous substitution.
Adoption barriersclaude-sonnet-53/5While no licensing specifically restricts hoisting to a certified electrician, safety regulations (OSHA rigging rules) and liability for equipment/material damage create meaningful friction against unproven automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Specialized robotics capable of performing this task autonomously (if available) would require capital investment, site-specific programming, and maintenance far exceeding the loaded wage cost of a helper-electrician performing this work.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI-driven substitute for this physical task, so any hypothetical robotic solution would be far more expensive than a helper's wage given current hardware costs.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed commercial products autonomously perform the full scope of raising, lowering, and positioning equipment on electrical worksites. While industrial robotics exist, they operate in controlled environments with pre-configured tasks, not the dynamic, unstructured positioning work described here.
Technical feasibility todayclaude-sonnet-51/5No deployed product performs this physical rigging/hoisting task; robotics for such construction-site material handling remains research-stage at best.

Operate cutting torches and welding equipment, while working with conduit and metal components to construct devices associated with electrical functions.

6

CI 5–7 · exposure 0 · augmentation 25 · importance 2.5/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510012/5While some large-scale industrial electrical manufacturing uses robotic welding, the construction and electrical helper sectors remain highly manual and low-automation. Adoption of autonomous equipment is slow outside dedicated factories.
Sector adoption velocityclaude-sonnet-51/5Construction and skilled trades are among the slowest sectors to adopt AI/robotics for physical fabrication tasks, with adoption concentrated in controlled manufacturing rather than field electrical work.
Augmentation potentialclaude-haiku-4-5-202510012/5AI could provide guidance on cutting/welding parameters or safety checks via computer vision, but the core task—physically operating torches and assembling conduit—leaves little room for meaningful AI assistance while a human performs it.
Augmentation potentialclaude-sonnet-52/5AI can assist with planning, diagrams, or torque/measurement calculations, but offers minimal direct assistance during the actual physical cutting and welding process.
Task automatabilityclaude-haiku-4-5-202510011/5This task involves physical manipulation of heavy equipment (cutting torches, welding equipment, conduit) and spatial coordination in 3D space. Current AI systems cannot operate physical equipment or perform precision welding/cutting autonomously in real-world conditions.
Task automatabilityclaude-sonnet-51/5This is a hands-on physical task requiring manipulation of torches, welding equipment, and metal conduit; no off-the-shelf AI can perform this physical fabrication work end-to-end.
Adoption barriersclaude-haiku-4-5-202510014/5Safety regulations, union agreements, and OSHA requirements often mandate that welding and torch operation meet strict certification and human supervision standards. Liability for equipment damage and worker safety creates strong legal barriers to full automation.
Adoption barriersclaude-sonnet-54/5Electrical and welding work is subject to safety codes, licensing/certification requirements for welding and electrical trades, and liability concerns that require human physical presence and accountability.
Cost vs. human wageclaude-haiku-4-5-202510011/5Industrial robotic welding and cutting systems exist but are expensive to procure, integrate, and maintain. For small-scale or varied electrical component assembly, the cost of hardware, programming, and oversight far exceeds the loaded wage of a skilled helper.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical task, so any AI-based approach (e.g., specialized welding robots) would require far greater capital investment than paying a helper's wage for variable, mobile job-site work.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI systems reliably operate welding torches, cutting torches, or manipulate electrical conduit and metal components in production settings. This remains a domain requiring human skill and embodied dexterity.
Technical feasibility todayclaude-sonnet-51/5No deployed AI product performs cutting/welding of conduit and electrical metal components autonomously; robotic welding exists only in narrow, fixed industrial settings, not job-site electrical work.

Trace out short circuits in wiring, using test meter.

5

CI 0–10 · exposure 0 · augmentation 25 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Electrical trades remain largely on-site, hands-on work with slow digitization and automation adoption. Helpers are deployed for physical tasks in variable environments where robotics and remote systems are not yet standard.
Sector adoption velocityclaude-sonnet-51/5Electrical trades are a physically-oriented, low-digitization sector with minimal AI/robotic adoption for hands-on diagnostic wiring work.
Augmentation potentialclaude-haiku-4-5-202510012/5While diagnostic AI (e.g., decision support for test reading interpretation) could marginally assist, the core task of physically tracing and using test equipment in situ offers limited augmentation opportunities for a human in the loop.
Augmentation potentialclaude-sonnet-52/5AI could help interpret meter readings, suggest likely fault locations from described symptoms, or provide reference diagrams, but cannot meaningfully speed the physical tracing and testing process itself.
Task automatabilityclaude-haiku-4-5-202510011/5Tracing short circuits requires physical inspection of wiring, manipulation of test equipment in real environments, and real-time diagnosis based on spatial layout and electrical conditions. Current AI systems cannot perform the full end-to-end task of locating and diagnosing faults in live electrical systems.
Task automatabilityclaude-sonnet-51/5This requires physical manipulation of wiring, hands-on probing with a meter, and access to physical infrastructure that current AI cannot perform end-to-end without a robotic embodiment.
Adoption barriersclaude-haiku-4-5-202510015/5Electrical work is heavily regulated and licensed; jurisdictions typically require qualified, licensed electricians or authorized helpers to perform diagnostic work on live or potentially hazardous wiring to ensure safety compliance and legal liability.
Adoption barriersclaude-sonnet-53/5While not formally licensed for helpers, safety risk from electrical shock and liability for faulty diagnosis creates real friction, though not a hard legal licensing barrier at this assistant level.
Cost vs. human wageclaude-haiku-4-5-202510011/5The task requires specialized test equipment, on-site presence, and real-time decision-making; AI solutions would need robotics and environmental sensing infrastructure that vastly exceeds the cost of employing a trained electrician's helper for this work.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI substitute performing this physical diagnostic task, so AI cost is effectively infinite relative to a helper's wage for this specific action.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed AI product reliably performs independent short-circuit tracing and diagnosis in the field. This task requires physical presence, equipment handling, and real-time sensory feedback that current autonomous systems cannot provide in production settings.
Technical feasibility todayclaude-sonnet-51/5No deployed product autonomously traces short circuits in physical wiring using a test meter; this remains a manual electrical trade task performed by humans on-site.

Erect electrical system components and barricades, and rig scaffolds, hoists, and shoring.

3

CI 0–5 · exposure 0 · augmentation 13 · importance 3.1/5 · click for rater detail

Panel ratings per dimension for this task
DimensionModelRatingRationale
Sector adoption velocityclaude-haiku-4-5-202510011/5Construction, especially scaffold erection and rigging, remains a low-digitization, high-human-contact sector with slow adoption of automation. Field conditions, regulatory compliance, and liability keep human oversight central.
Sector adoption velocityclaude-sonnet-51/5Construction and electrical trades are among the least digitized, slowest-adopting sectors for AI/robotic automation of physical tasks.
Augmentation potentialclaude-haiku-4-5-202510011/5AI offers minimal assistance to helpers performing physical rigging and erection; no current tool augments the core task of physically assembling and securing structural components on site.
Augmentation potentialclaude-sonnet-52/5AI can assist with planning, safety checklists, or logistics scheduling, but offers minimal direct assistance to the physical rigging and erection work itself.
Task automatabilityclaude-haiku-4-5-202510011/5This task requires physical manipulation, spatial reasoning, and real-time environmental assessment in unstructured construction sites. Current AI systems cannot autonomously erect components, barricades, scaffolds, hoists, or shoring with the precision and safety margins demanded on jobsites.
Task automatabilityclaude-sonnet-51/5This is a physical construction task requiring manual manipulation of heavy equipment, scaffolding, and hoisting systems in unstructured environments—far beyond current AI or robotic capabilities.
Adoption barriersclaude-haiku-4-5-202510015/5This task has hard regulatory barriers: OSHA requirements mandate qualified personnel for scaffolding, hoisting, and electrical work; liability for structural safety rests with licensed professionals and site supervisors who must sign off on rigging integrity.
Adoption barriersclaude-sonnet-54/5Safety regulations (OSHA scaffolding/shoring standards) require trained, often certified personnel to erect and inspect such structures, creating strong regulatory and liability barriers to automation.
Cost vs. human wageclaude-haiku-4-5-202510011/5Physical labor for rigging and erection is performed by low-cost human workers (helpers) in field conditions where autonomous systems would require expensive robotics, site setup, and ongoing oversight—far exceeding the wage cost.
Cost vs. human wageclaude-sonnet-51/5There is no viable AI/robotic substitute, so any hypothetical automation would require expensive specialized robotics far costlier than human labor for this task.
Technical feasibility todayclaude-haiku-4-5-202510011/5No deployed product reliably performs autonomous erection of electrical system components and structural rigging in production construction environments. This remains beyond the scope of current robotics and AI integration in the field.
Technical feasibility todayclaude-sonnet-51/5No deployed AI or robotic product autonomously erects scaffolding, shoring, or electrical barricades on job sites today; this remains firmly manual labor.

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.