Security and Fire Alarm Systems Installers
49-2098.00Median wage $60,070/yr86,340 employed (US)Rank #463 of 923 scored · top 50% by substitution
Install, program, maintain, and repair security and fire alarm wiring and equipment. Ensure that work is in accordance with relevant codes.
Sub-scores
0–100 · band = confidence interval from rater disagreement
Substitution28
Exposure23
Augmentation46
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
13%
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%24
panel mean rating 2.0/5 → substitution pressure 24/100
Technical feasibility todayw 20%21
panel mean rating 1.8/5 → substitution pressure 21/100
Cost vs. human wagew 15%25
panel mean rating 2.0/5 → substitution pressure 25/100
Adoption barriersw 20%inverted — strong barriers lower the score50
panel mean rating 3.0/5 (barrier strength) → substitution pressure 50/100
Sector adoption velocityw 10%17
panel mean rating 1.7/5 → substitution pressure 17/100
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.
Prepare documents, such as invoices or warranties.
82CI 76–89 · exposure 80 · augmentation 75 · importance 4.1/5 · click for rater detail
Prepare documents, such as invoices or warranties.
82| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 4/5 | Service and trades industries are adopting AI-powered invoicing and documentation at accelerating pace, especially in digitized firms. Cloud-based invoice and warranty systems are industry standard, enabling rapid automation. |
| Sector adoption velocity | claude-sonnet-5 | 3/5 | Field service and trades businesses are moderate adopters of digital admin tools, with software adoption common but AI-specific document automation still emerging in smaller firms. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI assists by auto-populating fields, checking for completeness, formatting professionally, and flagging missing data before human sign-off. This materially reduces technician time on administrative overhead while maintaining human control. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-assisted templates and auto-fill significantly speed up document preparation, letting installers focus on technical work while software handles paperwork. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | Document generation for invoices and warranties is highly automatable with current AI and document-processing systems. Once order/installation data is captured, AI can reliably populate templates, calculate costs, and generate formatted documents, meeting the 50% time-saving threshold easily. |
| Task automatability | claude-sonnet-5 | 4/5 | Generating invoices and warranty documents from structured job data (parts used, labor hours, customer info) is a templated text/data task well within current AI and software automation capabilities.through form-filling and generative text.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | Minor barriers exist around liability signing and company policy preferences for human sign-off on certain documents, but no licensing or legal requirement mandates human document preparation. Most organizations can automate with light oversight. |
| Adoption barriers | claude-sonnet-5 | 1/5 | No licensing or legal requirement mandates a human prepare these administrative documents; software-generated invoices/warranties are standard practice. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 5/5 | AI-driven document generation (templating, API calls, minimal oversight) costs far less than human labor for document preparation. The cost per invoice is typically pennies once systems are configured, versus minutes of human wage. |
| Cost vs. human wage | claude-sonnet-5 | 5/5 | Automated invoicing software costs a small fraction of the technician or admin time required to manually prepare documents, especially at scale. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 5/5 | Multiple deployed products (accounting software, CRM platforms, invoice generators) routinely handle this task in production across service industries. Reliability is mature and integration with business systems is standard practice. |
| Technical feasibility today | claude-sonnet-5 | 4/5 | Mature invoicing/CRM software (e.g., QuickBooks, ServiceTitan) with AI-assisted document generation is already deployed widely in field service industries. |
Order replacement parts.
71CI 65–77 · exposure 70 · augmentation 75 · importance 3.7/5 · click for rater detail
Order replacement parts.
71| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Field service and installation companies show moderate adoption of automated ordering through work-order systems and supplier APIs; larger firms integrate more deeply, while smaller installers often rely on manual processes. Adoption is expanding but not yet dominant. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Security/fire alarm installation is a trade-based, physically-oriented sector with generally slower AI and software adoption compared to information/finance industries, though basic inventory software is common. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can reliably suggest or auto-fill part numbers, check stock, flag out-of-stock items, and route orders to optimal suppliers, substantially accelerating the human decision-making and transaction process while the technician remains in control. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-driven inventory and procurement assistants can significantly speed up part identification and ordering, letting technicians focus on installation work while a system flags low stock or suggests reorders. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | Current AI can identify needed parts from work orders, cross-reference inventory systems, and generate purchase orders with significant time savings. The task involves structured data lookup and order placement, which are readily automatable, though some human verification of part specifications against system requirements may still be prudent. |
| Task automatability | claude-sonnet-5 | 4/5 | Ordering replacement parts is a structured, transactional task (identifying part numbers, checking inventory systems, placing orders) that off-the-shelf procurement/ERP automation and AI agents can handle with high time savings once integrated with supplier catalogs. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | Few regulatory or legal barriers exist to automating parts ordering. Main friction points are organizational (legacy systems, preferred supplier relationships, human oversight preferences) and technical (ERP/inventory system integration), not legal or liability-based. |
| Adoption barriers | claude-sonnet-5 | 1/5 | There is no licensing, liability, or human-contact requirement for ordering parts; it's a routine back-office task with minimal regulatory or organizational friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | AI-driven ordering (API calls, data lookups, purchase order generation) costs far less than human labor to research, call suppliers, or manually place orders. The per-order cost is typically measured in cents to low dollars. |
| Cost vs. human wage | claude-sonnet-5 | 4/5 | Automated ordering via inventory management software is far cheaper per transaction than having a technician spend time on calls or manual entry, though initial integration with supplier systems has some cost. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 4/5 | E-commerce and inventory management APIs are widely deployed; many suppliers offer API-driven ordering. Production systems in field service and procurement already automate parts ordering at scale, though integration specifics vary by supplier and organizational system complexity. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Procurement software and AI-assisted ordering tools exist and are used in field service industries, but many installers still rely on manual lookup and phone/vendor-specific portals, so reliability varies by company size and system integration. |
Provide customers with cost estimates for equipment installation.
62CI 52–72 · exposure 62 · augmentation 75 · importance 3.9/5 · click for rater detail
Provide customers with cost estimates for equipment installation.
62| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Security and HVAC/electrical contractors are moderately digitized, with CRM and estimating tools fairly common. However, many small installers still rely on manual processes or spreadsheets; adoption is not laggard but slower than finance or professional services. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Security/fire alarm installation is a physical, moderately digitized trade sector where AI adoption for quoting is emerging but not widespread or fast-moving compared to information-sector norms. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can rapidly draft estimates, pull part numbers and labor rates, and format professional documents, significantly accelerating the technician's workflow. The human remains in the loop for final review, customer communication, and scenario adjustment, making this strong augmentation. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI tools can quickly generate itemized cost estimates, pull pricing data, and draft proposals, meaningfully speeding up the estimator's work even though a human still finalizes site-specific details. |
| Task automatability | claude-haiku-4-5-20251001 | 4/5 | AI can reliably extract customer requirements, access pricing databases, calculate labor costs based on job complexity, and generate professional estimates. This requires minimal human judgment beyond initial specification gathering, allowing 50%+ time savings. Some customer-specific negotiation or custom scenarios may still need human review. |
| Task automatability | claude-sonnet-5 | 3/5 | Generating a cost estimate from a defined scope (equipment list, labor hours, site conditions) can be templated and largely automated, but capturing site-specific factors typically requires a human visit or judgment call, limiting full end-to-end automation. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | No legal licensing requirement mandates human sign-off on estimates. Customer preference for human contact and sales relationship is present but declining; liability and error costs are moderate and easily managed through standard disclaimers and human review. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement mandates a human generate quotes, though customer trust, liability for inaccurate estimates, and property access needs create moderate friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | Inference cost for generating estimates is minimal (under $0.01 per estimate), while a technician's time for detailed manual estimates costs $50–150+. Integration and oversight adds modest cost, but the ratio strongly favors AI, likely 10–50× cheaper per estimate. |
| Cost vs. human wage | claude-sonnet-5 | 3/5 | Software-based estimating tools are cheap per-quote, but the necessary site inspection and judgment component still requires paid technician time, keeping overall cost roughly comparable to a human-driven process with software assistance. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 4/5 | Deployed CRM and estimating software (Salesforce, ServiceTitan, etc.) already automate much of estimate generation for field service companies. AI-powered pricing tools exist in production at scale, though they typically work within structured pricing frameworks rather than fully autonomous end-to-end estimation. |
| Technical feasibility today | claude-sonnet-5 | 3/5 | Estimating/quoting software with AI-assisted pricing exists and is used in trades, but most installers still rely on manual site assessment and human-adjusted quotes rather than fully autonomous AI-generated estimates. |
Keep informed of new products and developments.
47CI 39–55 · exposure 30 · augmentation 75 · importance 3.8/5 · click for rater detail
Keep informed of new products and developments.
47| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 3/5 | Security companies are moderately digitizing, with some using internal knowledge management and AI monitoring tools, but many smaller installers still rely on vendor relationships and manual research; adoption is uneven across the sector. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | This is a niche trade (installation/skilled trades) with lower overall AI tool adoption compared to information-sector jobs, though general awareness-tools usage is creeping in. |
| Augmentation potential | claude-haiku-4-5-20251001 | 4/5 | AI can substantially boost a human installer's productivity by curating relevant product updates, technical specifications, and industry news, reducing time spent searching while the installer applies domain expertise to evaluate applicability and competitive impact. |
| Augmentation potential | claude-sonnet-5 | 4/5 | AI-powered search, summarization, and personalized alerts can meaningfully speed up how technicians learn about new products, standards, and codes. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can aggregate and summarize product announcements and technical documentation, staying truly informed requires contextual judgment about relevance, reliability, and applicability to specific installation scenarios. Current AI struggles with the selective evaluation needed to filter signal from noise in a specialized field. |
| Task automatability | claude-sonnet-5 | 2/5 | AI can help surface new product releases and industry news via summarization tools, but the task requires ongoing personal awareness, trade-show attendance, and hands-on evaluation that isn't fully replaceable end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | No legal or licensing requirement mandates human-only information gathering; companies can deploy AI news monitoring and technical briefing systems without regulatory friction. The main barrier is organizational habit and installer preference for human judgment. |
| Adoption barriers | claude-sonnet-5 | 1/5 | There are no licensing, regulatory or liability barriers to using AI aids for staying informed; it's a low-stakes informational task. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 4/5 | AI-powered information monitoring and summarization tools are inexpensive (often free or low-cost subscriptions) compared to the time a human would spend manually searching industry sources, attending seminars, or reading catalogs. |
| Cost vs. human wage | claude-sonnet-5 | 3/5 | Using AI tools to scan trade publications or manufacturer bulletins is cheap, but the marginal cost savings versus a technician occasionally reading trade press is modest, not order-of-magnitude. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 3/5 | AI tools like news aggregators, RSS feeds with ML filtering, and technical document summarizers exist and are used in production, but they are partial solutions requiring human validation and cannot independently assess which developments matter for an installer's business. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | News aggregators, RSS/AI summarizers and newsletters exist and are used informally, but no deployed product specifically curates security/fire alarm product updates reliably for technicians at scale. |
Demonstrate systems for customers and explain details, such as the causes and consequences of false alarms.
33CI 30–35 · exposure 25 · augmentation 50 · importance 4.4/5 · click for rater detail
Demonstrate systems for customers and explain details, such as the causes and consequences of false alarms.
33| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Security system installation remains a hands-on, local service industry with moderate digitization. While some companies offer virtual consultations, the majority of demonstration and sales still happen in-person, and uptake of AI-assisted or automated demos is nascent. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Security/fire alarm installation is a physical trades sector with low overall AI adoption; digitization of customer-facing explanation is still nascent. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can assist technicians by generating clear explanations of alarm causes and consequences, preparing visual aids, or drafting customer-facing documentation. This support can improve consistency and efficiency without removing the human from the demonstration loop. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI can help installers prepare talking points, FAQs, and personalized explanations of false-alarm causes, improving the quality and efficiency of the human-led demonstration. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can generate explanatory content and draft technical descriptions, customer demonstrations require interactive dialogue, adaptive communication for diverse audiences, and real-time troubleshooting—tasks that demand human judgment and presence. Current AI cannot reliably substitute for the full demonstration experience at the required quality threshold. |
| Task automatability | claude-sonnet-5 | 2/5 | Explaining system operation and false-alarm causes is largely verbal/informational, but the task is bundled with in-person physical demonstration of installed hardware, which current AI cannot perform end-to-end.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 3/5 | Customer expectations for in-person demonstrations, sales relationships, and the need to build trust around security systems create moderate friction against full automation. However, no strict legal requirement mandates a licensed technician conduct demos, lowering the barrier below full regulatory protection. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing requirement specifically for this explanatory task, though customer preference for a live human demonstrating hardware and liability concerns around false-alarm consequences create moderate friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Meaningful customer demonstration still requires human presence and expertise; any AI system that could assist would require integration, oversight, and human oversight to ensure customer satisfaction. The all-in cost would remain comparable to or exceed having a technician perform the task directly. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | AI could cheaply generate explanatory content, but the physical demonstration and trust-building interaction still require a human technician, so overall cost savings are limited. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed product reliably performs in-person system demonstrations to customers. Chatbots can answer FAQs about alarm systems, but they cannot physically show equipment operation, adapt to customer confusion in real time, or build the trust required for high-value security system sales. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | Chatbots and AI assistants can answer FAQs about alarm systems, but no deployed product performs live on-site customer demonstrations combined with tailored explanations reliably today. |
Consult with clients to assess risks and to determine security requirements.
26CI 23–30 · exposure 25 · augmentation 50 · importance 4.0/5 · click for rater detail
Consult with clients to assess risks and to determine security requirements.
26| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Security installation remains a trade-heavy, local-service sector with limited digitization and slow AI adoption; most firms are small or mid-sized with low automation velocity and continuing reliance on field professionals for client interaction. |
| Sector adoption velocity | claude-sonnet-5 | 2/5 | Security/alarm installation is a physical trades sector with historically low digitization and slow AI adoption compared to information-sector benchmarks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can assist by analyzing risk data, generating compliance checklists, or providing relevant case examples during a consultation, which could speed up the information-gathering phase and help the installer present options more systematically. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI can help installers prepare risk checklists, research building codes, draft proposals, and analyze site photos/floor plans, meaningfully aiding parts of the consultative process. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can gather and analyze some risk data, the task fundamentally requires two-way consultation, nuanced judgment about client needs, and building trust—elements that demand human interaction and contextual understanding that current AI systems cannot reliably handle end-to-end at 50% time savings with equal quality. |
| Task automatability | claude-sonnet-5 | 2/5 | This requires physical site assessment, reading client-specific spatial and behavioral context, and building trust—AI can support but not replace this consultative, judgment-heavy interaction end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Security risk assessment often involves liability concerns, regulatory compliance in certain jurisdictions, and client preference for human judgment and accountability; insurers and clients typically expect a licensed or qualified human to sign off on security recommendations. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing mandate for the consultation itself in most jurisdictions, but liability for inadequate security assessment and client preference for a trusted human advisor create real friction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | The cost of AI systems for consultation (infrastructure, training data, oversight, error correction) combined with necessary human supervision makes the all-in cost comparable to or higher than a human installer-consultant's loaded wage for this consultative work. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Human consultation still requires site visits and relationship-based trust; AI tools reduce some prep/documentation time but don't replace the billable consultative visit, so cost savings are modest. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed product reliably performs client consultation and needs assessment for security systems in production; AI can support risk analysis or generate templates, but assessing client risk and determining requirements requires human judgment and rapport that existing systems cannot replace dependably. |
| Technical feasibility today | claude-sonnet-5 | 2/5 | No deployed product performs full client risk consultation and requirement determination for security installs; some AI-assisted questionnaires or checklists exist but are narrow aids, not autonomous consultants. |
Inspect installation sites and study work orders, building plans, and installation manuals to determine materials requirements and installation procedures.
24CI 18–30 · exposure 20 · augmentation 50 · importance 4.1/5 · click for rater detail
Inspect installation sites and study work orders, building plans, and installation manuals to determine materials requirements and installation procedures.
24| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Security systems installation is a field-based, low-digitization sector with small to medium firms; adoption of AI-driven planning remains slow and largely experimental rather than in mainstream production workflows. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Security/fire alarm installation is a small-business-dominated, physical trade sector with low AI adoption and few production AI tools for this specific workflow. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can assist by automatically extracting key data from plans and manuals, cross-referencing specifications, and flagging potential conflicts, reducing manual document review time while the technician makes final site assessment and procedure decisions. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI can help interpret building plans, cross-reference manuals, and generate materials lists, providing useful support even though the on-site inspection remains human-driven. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | AI can extract and summarize information from documents (work orders, plans, manuals) but site inspection requires physical presence and nuanced spatial reasoning that current systems cannot perform autonomously, limiting time savings to document processing only. |
| Task automatability | claude-sonnet-5 | 2/5 | Requires physical site inspection and judgment about real-world building conditions; AI can assist with parsing plans and manuals but cannot itself walk the site or verify physical constraints today.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Safety and liability concerns are substantial: building code compliance, site hazard identification, and responsibility for material accuracy carry legal weight; installers and their firms bear liability for incorrect materials or installation procedures. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing strictly requires a human for site inspection, but liability for incorrect installation planning and the need for physical presence create moderate friction against full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | AI document processing is cheap, but the integrated cost of site inspection oversight, error handling, and human verification approaches or exceeds the loaded wage of a skilled technician performing the inspection directly. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | AI could cheaply assist with document review, but the physical inspection component still requires a paid technician on-site, keeping overall cost comparable to human labor. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Document analysis and procedure lookup via AI are partially deployed, but reliable end-to-end site assessment and materials determination still requires human interpretation of complex building plans and site-specific factors that AI struggles with consistently. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs autonomous site inspection combined with materials/procedure determination for alarm installation; this remains a human-led physical task. |
Adjust sensitivity of units, based on room structures and manufacturers' recommendations, using programming keypads.
21CI 18–25 · exposure 20 · augmentation 50 · importance 4.0/5 · click for rater detail
Adjust sensitivity of units, based on room structures and manufacturers' recommendations, using programming keypads.
21| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Security installation remains a trade-based, field service sector with limited digital transformation and slow AI adoption relative to information-intensive sectors. Most firms are small to medium-sized with legacy processes and on-site, hands-on work patterns. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Alarm and security installation is a low-digitization, physically dispersed trade with minimal AI agent deployment in the field; adoption of AI for hands-on installation tasks is essentially nonexistent. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can assist by retrieving manufacturer sensitivity tables, suggesting parameters based on room dimensions, and flagging potential code violations—useful guidance that improves technician efficiency and reduces manual lookup time, though the technician retains full decision authority. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI can assist by referencing manufacturer specs, generating recommended sensitivity settings based on room dimensions, or diagnosing false-alarm patterns, helping the technician make better-informed manual adjustments. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI could theoretically guide sensitivity adjustments via text, the task requires hands-on physical interaction with keypads and real-time assessment of room structures that vary significantly. Current AI systems cannot autonomously manipulate physical keypads or reliably interpret complex spatial layouts for calibration decisions without human oversight. |
| Task automatability | claude-sonnet-5 | 2/5 | This requires physical presence at the installation site, hands-on interaction with hardware keypads, and situational judgment about room layout that current AI cannot execute end-to-end.It could theoretically be guided by AI-generated recommendations, but the physical adjustment is not automatable today. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Security system installation is regulated under fire and building codes; many jurisdictions legally require a licensed, certified technician to sign off on system calibration and compliance. Liability for false alarms or missed threats creates strong error-cost asymmetry that deters full automation. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Fire and security alarm systems are often subject to code compliance, inspection, and certification requirements, and improper sensitivity settings carry real liability and safety risk, creating strong barriers to non-human execution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | Integration of AI assistance (document review, parameter suggestion) would still require the human technician to be on-site for physical adjustment and verification. The total installed cost of AI tooling and oversight would likely approach or exceed the time savings on a per-task basis. |
| Cost vs. human wage | claude-sonnet-5 | 2/5 | Without a robotic or remote-actuation system, AI cannot substitute for the technician's physical labor, so there's no meaningful AI cost basis to compare favorably against human wages for this specific physical action. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | No deployed product reliably performs end-to-end sensitivity adjustment of security systems autonomously. While AI can assist with documentation and basic parameter lookup, the physical manipulation and context-specific judgment required for safe, code-compliant installation remain beyond production AI capability. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product autonomously performs physical sensitivity calibration on security/fire alarm hardware in the field; this remains a manual technician task. |
Examine systems to locate problems, such as loose connections or broken insulation.
18CI 14–21 · exposure 20 · augmentation 50 · importance 4.4/5 · click for rater detail
Examine systems to locate problems, such as loose connections or broken insulation.
18| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Security and alarm installation remains a traditionally craft-based sector with slow digital adoption. While some firms use thermal or visual inspection aids, systematic AI-driven examination in production is minimal and adoption of autonomous inspection remains in early pilot phases. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | This is a physical, hands-on trade with low digitization and slow AI adoption for on-site diagnostic and repair work compared to office/information-based occupations. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI could assist technicians by flagging potential defects in visual inspection footage or highlighting areas needing closer attention, moderately improving inspection speed and consistency. However, the task inherently requires human judgment and physical access, limiting augmentation gains. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI-enabled diagnostic tools, thermal imaging analysis, or predictive maintenance software can help technicians pinpoint likely fault locations faster, though the physical examination itself remains human-performed. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Examining physical systems for loose connections or broken insulation requires hands-on inspection and tactile assessment in real-world environments. While vision-based AI could identify some visual defects remotely, most work requires physical access, manipulation, and contextual judgment that current AI systems cannot perform end-to-end autonomously. |
| Task automatability | claude-sonnet-5 | 2/5 | Diagnosing physical faults like loose wiring or broken insulation requires hands-on inspection, testing equipment, and physical access that current AI cannot perform end-to-end; at most AI could assist with diagnostic logic given sensor data. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Building codes and insurance requirements typically mandate that licensed electricians or certified technicians perform safety-critical inspections of alarm and electrical systems. Liability for missed faults creates strong legal and regulatory barriers to full automation without human sign-off. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Fire and security alarm systems are subject to safety codes and often require licensed/certified technicians to inspect and certify system integrity, creating strong regulatory and liability barriers to full automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Current AI inspection tools (cameras, image analysis) still require human technicians to perform the actual examination work, position equipment, and interpret results. The cost of deploying specialized hardware and oversight typically exceeds the cost of direct human inspection. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute performing the physical inspection, so any AI cost would be additive to, not a replacement for, the human technician's labor. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | Computer vision systems can detect some surface-level defects in controlled imaging scenarios, but deployed products lack the spatial reasoning, 3D navigation, and physical manipulation needed to systematically examine complex wiring and connections in installed systems. Real-world deployment remains limited. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product autonomously performs physical inspection and fault localization in fire/security alarm wiring; this remains a manual, tool-based diagnostic task performed by technicians. |
Test backup batteries, keypad programming, sirens, or other security features to ensure proper functioning or to diagnose malfunctions.
17CI 14–20 · exposure 16 · augmentation 50 · importance 4.3/5 · click for rater detail
Test backup batteries, keypad programming, sirens, or other security features to ensure proper functioning or to diagnose malfunctions.
17| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | Security installation remains a fragmented, small-to-medium business sector with low tech adoption rates. Most firms are not digitized; remote diagnosis and robotic testing are rare in production, with adoption confined to demos or large integrators. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | This is a physical, low-digitization trade with minimal AI/robotic penetration into fieldwork; adoption of automation in this specific task is negligible. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI could assist by analyzing sensor data, flagging common failure modes (dead batteries, programming errors) from logs, or guiding technicians through checklists, raising diagnostic speed. However, the physical test and hands-on troubleshooting remain human-driven. |
| Augmentation potential | claude-sonnet-5 | 3/5 | AI-enabled diagnostic software, smart sensors, and mobile apps can help technicians log results, flag anomalies, and guide troubleshooting steps, improving efficiency without replacing the hands-on work. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | Testing security features involves physical interaction with hardware (pressing buttons, measuring voltage, triggering alarms), visual inspection of components, and diagnostic judgment about whether failures require repair. While AI could assist with diagnostics via image analysis or data logs, current systems cannot physically access, manipulate, or reliably test these components end-to-end. |
| Task automatability | claude-sonnet-5 | 2/5 | Diagnostic testing requires physical inspection, hands-on manipulation of hardware, and interpretation of ambiguous fault signals in varied installation contexts, which current AI cannot perform end-to-end.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Security system testing often involves activation of sirens and alarms affecting customer premises, and incorrect testing could trigger false alarms with legal liability. Installer licensing and liability insurance create organizational and regulatory friction, and customer preference for a qualified human technician on-site is strong. |
| Adoption barriers | claude-sonnet-5 | 4/5 | Fire and life-safety systems are subject to code compliance, inspection certifications, and liability requirements that typically mandate a qualified human technician to verify and sign off on system functionality. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 2/5 | The physical testing task requires either a mobile robot (expensive, nascent) or human technician ($25–45/hr loaded). AI-assisted diagnostics via sensor data might reduce some analysis time, but the core testing work remains labor-intensive and human-dependent, keeping costs near parity. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | AI cannot yet substitute for the physical labor and diagnostic judgment involved, so there is no viable AI-based cost alternative to the human technician. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed product today can autonomously perform physical testing of security system components, keypad programming, or siren activation. This requires embodied interaction with installed hardware and integration with live customer systems that AI robots lack in production settings. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed products autonomously test physical security/fire alarm hardware components like batteries and sirens in the field; this remains a manual technician task. |
Test and repair circuits and sensors, following wiring and system specifications.
16CI 5–26 · exposure 13 · augmentation 38 · importance 4.4/5 · click for rater detail
Test and repair circuits and sensors, following wiring and system specifications.
16| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 2/5 | The security installation sector remains fragmented with many small operators and has not yet digitized sufficiently for rapid AI tool adoption; adoption is early-stage and limited to diagnostic support rather than end-to-end automation. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Installation and repair trades are physical, low-digitization occupations with minimal AI/robotics deployment in production settings currently. |
| Augmentation potential | claude-haiku-4-5-20251001 | 3/5 | AI can meaningfully assist by diagnosing faults from sensor data, suggesting repair sequences, or checking designs against specifications, improving technician efficiency on the analytical portions of the task without replacing hands-on work. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI can assist with diagnostic guidance, wiring diagram lookup, or troubleshooting documentation, but offers limited direct assistance for the physical testing and repair steps. |
| Task automatability | claude-haiku-4-5-20251001 | 2/5 | While AI can analyze circuit diagrams and sensor specifications digitally, physical testing and repair requires hands-on manipulation of hardware, soldering, measurement tools, and real-world troubleshooting that current systems cannot perform end-to-end. Diagnosis support is feasible, but execution remains manual. |
| Task automatability | claude-sonnet-5 | 1/5 | This requires physical hands-on testing, wiring manipulation, and repair of alarm circuits and sensors on-site, which current AI cannot perform end-to-end.the task is fundamentally physical manipulation. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Most jurisdictions require licensed electricians or certified alarm installers to legally perform circuit testing and repair work on safety-critical systems, creating a hard licensing barrier. Liability for system failures also falls on the licensed technician. |
| Adoption barriers | claude-sonnet-5 | 3/5 | Electrical and alarm system work often requires licensed technicians and code compliance, plus liability concerns for faulty life-safety systems, though not always requiring formal certification depending on jurisdiction. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The task involves specialized physical equipment access, real-time troubleshooting judgment, and equipment liability that make human technicians necessary. AI tools that assist cost less than human labor but do not eliminate the technician's substantial wage burden. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute performing this physical repair work, so AI cost is effectively infinite relative to a human technician's wage for this output. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 2/5 | AI products can assist with circuit analysis and fault identification from data, but no deployed system reliably performs physical circuit testing and repair autonomously. Existing tools support technicians rather than replacing the hands-on work required. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed products physically test and repair circuits and sensors; this remains a manual electrician/technician task requiring physical tools and dexterity. |
Drill holes for wiring in wall studs, joists, ceilings, or floors.
13CI 10–15 · exposure 0 · augmentation 13 · importance 4.2/5 · click for rater detail
Drill holes for wiring in wall studs, joists, ceilings, or floors.
13| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Adoption of automation in field installation trades remains very low; this sector is characterized by on-site manual labor, small crews, and low digitization. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | The construction and trades sector shows minimal AI adoption for physical installation tasks, with automation efforts focused on design and diagnostics rather than manual drilling work. |
| Augmentation potential | claude-haiku-4-5-20251001 | 1/5 | Current AI provides no meaningful assistance to a technician actually drilling holes; the task requires real-time physical control and tactile feedback that AI cannot augment. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could marginally assist with planning wire routes or identifying stud locations via imaging apps, but offers negligible help with the physical act of drilling itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires precise physical manipulation in 3D space, judgment about structural integrity, and adaptation to varied site conditions—capabilities current AI systems fundamentally lack. Physical robots capable of this work are not deployed in general construction settings. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical drilling task requiring hands-on manipulation of tools within building structures; no current AI system can perform this end-to-end without robotic hardware that doesn't exist for this application. |
| Adoption barriers | claude-haiku-4-5-20251001 | 2/5 | While there are no strict licensing requirements for the drilling itself, the task occurs within regulated fire safety installations where qualified installers must oversee the work, creating modest organizational friction. |
| Adoption barriers | claude-sonnet-5 | 3/5 | While no formal licensing mandates a human specifically drill holes, building codes, structural safety concerns, and the practical need for on-site judgment about stud/joist placement create meaningful friction against automation. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The cost of a specialized drilling robot, integration, and maintenance far exceeds the loaded wage of a skilled tradesperson for this straightforward manual task. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI-driven alternative to a human physically drilling holes, so any hypothetical robotic solution would be far more expensive than a technician's labor for this task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI or robotic systems reliably perform structural hole-drilling in uncontrolled building interiors at production scale. This remains an entirely human-performed task in real installations. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs autonomous drilling for wiring installation in residential/commercial construction settings; this remains firmly in the physical trades domain untouched by AI products. |
Feed cables through access holes, roof spaces, or cavity walls to reach fixture outlets, positioning and terminating cables, wires, or strapping.
10CI 5–15 · exposure 0 · augmentation 25 · importance 4.4/5 · click for rater detail
Feed cables through access holes, roof spaces, or cavity walls to reach fixture outlets, positioning and terminating cables, wires, or strapping.
10| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Security and fire alarm installation remains a craft trade in small and mid-sized firms with limited digitization. Adoption of automation in this sector has been minimal; technicians still perform manual routing and termination as standard practice. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | The construction and low-voltage installation trades are physical, low-digitization sectors with minimal AI/robotic adoption for hands-on wiring tasks. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with pre-installation planning (cable path visualization or layout recommendations), but offers minimal real-time productivity gains during the hands-on routing and termination work itself. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI offers limited assistance here beyond planning cable routes or documentation; the physical feeding and termination work sees negligible productivity uplift from current tools. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires navigating complex 3D spatial environments, physical manipulation of cables through confined spaces, and precise positioning in context-specific locations. Current AI systems cannot perform end-to-end physical installation work in unstructured building environments. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical manipulation task requiring dexterity to route cable through confined, irregular spaces and terminate connections—current AI systems and robotics cannot perform this end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Building and electrical safety codes typically require licensed electricians or installers to perform cable installation and termination, creating legal and liability barriers to automation. Customer preference for certified professionals and site-specific sign-off also protect this task. |
| Adoption barriers | claude-sonnet-5 | 2/5 | No licensing strictly requires a human for basic cable pulling, though electrical/fire-safety codes and building access constraints create moderate practical friction against any automated substitute. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Specialized installation technicians earn loaded wages of $60–80k annually, while developing and deploying autonomous cable-routing robots would cost hundreds of thousands to millions per unit with high maintenance overhead, making human labor far cheaper. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI/robotic substitute, so the all-in cost of an AI performing this task is effectively infinite compared to a human installer's wage. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed commercial product reliably performs autonomous cable routing and termination in diverse building structures. The task demands embodied manipulation, spatial reasoning, and adaptation to site-specific obstacles that existing robotics or AI systems do not handle in production. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product exists that can navigate roof spaces or cavity walls and physically feed and terminate cabling; this remains purely a human manual trade skill. |
Install, maintain, or repair security systems, alarm devices, or related equipment, following blueprints of electrical layouts and building plans.
7CI 5–10 · exposure 0 · augmentation 25 · importance 4.4/5 · click for rater detail
Install, maintain, or repair security systems, alarm devices, or related equipment, following blueprints of electrical layouts and building plans.
7| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | The security installation sector remains predominantly manual and localized, with work tied to physical infrastructure, building diversity, and regulatory compliance. Adoption of AI in production settings for this task is minimal. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Electrical/security installation trades are physical, low-digitization work with minimal AI or robotics adoption in production settings. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI can assist marginally by analyzing blueprints, recommending equipment configurations, or generating checklists, but the core skill—physical installation and troubleshooting—is not substantially augmented by current systems. Assistance remains peripheral to the main task. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI can help with reading/interpreting blueprints, generating documentation, or troubleshooting guidance, but offers little assistance with the hands-on wiring, mounting, and physical repair work itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task fundamentally requires on-site physical installation, maintenance, and repair of hardware equipment in diverse building environments. Current AI systems cannot navigate physical spaces, handle tools, or perform hands-on wiring and equipment assembly at scale. |
| Task automatability | claude-sonnet-5 | 1/5 | This is physical installation, wiring, and hands-on repair work requiring manipulation of hardware, drilling, running cable, and reading blueprints on-site; current AI has no embodied capability to perform this end-to-end. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Most jurisdictions require security system installers to hold licenses or certifications, and many regions mandate that installations comply with legal codes signed off by qualified professionals. Liability for faulty installations creates substantial legal barriers to full automation. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing mandate universally requires a human specifically for installation in all jurisdictions, but physical access to buildings, liability for faulty security installations, and lack of any automation alternative create strong practical barriers to substitution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | AI offers no direct cost substitution for the physical labor component. The task requires licensed technician wages, and any AI assistance (e.g., blueprint interpretation) provides only marginal value relative to human labor costs. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI substitute performing the physical labor, so any 'AI' cost comparison is moot—human labor remains the only option, making AI effectively infinitely costlier for the physical core of the task. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product can perform end-to-end physical installation, maintenance, or repair of security systems. While AI can assist with reading blueprints or providing guidance, actual execution remains entirely dependent on human technicians. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product installs or physically repairs security/alarm equipment; robotics for such varied, unstructured physical tasks in diverse buildings remains research-stage at best. |
Mount and fasten control panels, door and window contacts, sensors, or video cameras, and attach electrical and telephone wiring to connect components.
7CI 5–10 · exposure 0 · augmentation 25 · importance 4.4/5 · click for rater detail
Mount and fasten control panels, door and window contacts, sensors, or video cameras, and attach electrical and telephone wiring to connect components.
7| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | Security system installation is a field-service, physical task with low digitization. Adoption of AI for the core mounting and wiring work is minimal; human technicians remain the industry standard. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | The security/alarm installation trade is a physical, on-site field service sector with minimal AI/robotics adoption and low digitization of the core hands-on work. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could assist with diagnostics or planning (e.g., recommending optimal camera placement), but core installation—mounting, fastening, wiring—remains human-dependent; augmentation potential is limited to planning stages. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI can help with wiring diagrams, planning layouts, or troubleshooting guidance, but offers little assistance for the physical mounting and wiring execution itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires physical manipulation in varied, real-world environments—mounting equipment on walls, fastening components, running wiring through buildings. Current AI systems cannot perform these embodied, spatially-aware actions reliably or at scale. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical installation task requiring drilling, mounting hardware, running wiring through walls, and manual dexterity in varied job-site conditions, none of which current AI systems can perform. |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Installation of security systems often requires licensing or bonding in many jurisdictions, and customer preference for qualified human installers (for warranty and liability reasons) creates strong adoption friction. |
| Adoption barriers | claude-sonnet-5 | 3/5 | While not licensed like electrical work in all jurisdictions, low-voltage wiring often requires certification, building code compliance, and liability considerations that add friction to any automated substitution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | Installation labor remains far cheaper than purchasing, deploying, and maintaining specialized robotics for mounting and fastening tasks in diverse residential and commercial environments. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no AI-driven substitute for physical mounting and wiring, so the human installer remains the only viable and cost-effective option. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed AI product can independently mount panels, fasten sensors, or route wiring in customer installations. This requires mobile manipulation and real-time spatial reasoning that exceeds current robotic and AI capabilities in production. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product installs or fastens physical security equipment; this remains purely a research/robotics frontier problem with no field-ready automation. |
Mount raceways and conduits and fasten wires to wood framing, using staplers.
7CI 5–10 · exposure 0 · augmentation 25 · importance 4.0/5 · click for rater detail
Mount raceways and conduits and fasten wires to wood framing, using staplers.
7| Dimension | Model | Rating | Rationale |
|---|---|---|---|
| Sector adoption velocity | claude-haiku-4-5-20251001 | 1/5 | This task is performed by small to mid-sized installation companies, many of which operate with limited digitization. Adoption of robotic systems in this sector remains minimal; the work is primarily done on-site in varied environments that favor human flexibility over automation. |
| Sector adoption velocity | claude-sonnet-5 | 1/5 | Construction and low-voltage installation trades show minimal AI/robotics adoption for physical fastening tasks, reflecting a laggard, low-digitization sector. |
| Augmentation potential | claude-haiku-4-5-20251001 | 2/5 | AI could potentially assist with planning optimal raceway routes or identifying mounting points through visual inspection, but the core physical execution requires human hands and cannot be meaningfully augmented by current AI tools. |
| Augmentation potential | claude-sonnet-5 | 2/5 | AI could assist with planning layouts or generating installation instructions, but it offers little direct help with the physical mounting and fastening work itself. |
| Task automatability | claude-haiku-4-5-20251001 | 1/5 | This task requires precise physical manipulation in three-dimensional space, identification of correct mounting locations on wood framing, and dexterous use of tools like staplers. Current AI systems cannot perform autonomous physical installation tasks of this complexity in unstructured environments. |
| Task automatability | claude-sonnet-5 | 1/5 | This is a physical manual installation task requiring hand-eye coordination and dexterity in variable job-site conditions; current AI systems (software or robotics) cannot perform this end-to-end.' |
| Adoption barriers | claude-haiku-4-5-20251001 | 4/5 | Electrical system installation typically requires licensed electricians or certified installers in most jurisdictions, and fire alarm systems are often subject to building codes and inspections that mandate professional installation and sign-off. |
| Adoption barriers | claude-sonnet-5 | 3/5 | No licensing requirement specifically bars automation, but physical site variability, safety codes, and the need for skilled manual adjustment create practical friction against non-human execution. |
| Cost vs. human wage | claude-haiku-4-5-20251001 | 1/5 | The capital cost of a robotic system capable of this task, including perception, manipulation, and integration, would far exceed the cost of a skilled technician performing the work. Operating and maintaining such a system would remain prohibitively expensive compared to human labor. |
| Cost vs. human wage | claude-sonnet-5 | 1/5 | There is no viable AI-driven substitute, so the effective cost of AI performing this task is undefined/infinite compared to a human installer. |
| Technical feasibility today | claude-haiku-4-5-20251001 | 1/5 | No deployed robotic or AI system currently performs this installation task reliably in production settings. While research exists in robotic manipulation, production systems that can autonomously mount conduits, route wires, and secure them with staplers on varied wood framing do not exist at scale. |
| Technical feasibility today | claude-sonnet-5 | 1/5 | No deployed product performs raceway mounting or wire fastening on wood framing; this remains outside the scope of any commercial AI/robotics offering. |
Related occupations — Installation, Maintenance & Repair
How to read this
A high substitution score does not mean this job disappears — it means a large share of its current tasks face replacement pressure, so the mix of tasks is likely to change. High augmentation alongside substitution typically means the occupation reorganizes around the protected tasks. Wide confidence intervals mean the rater panel disagreed: treat those scores as open questions, not verdicts.
What would change this score
New model capabilities (automatability, feasibility), falling inference costs (cost ratio), regulation and licensing shifts (barriers), and measured sector adoption (velocity) all re-enter at every index release. Each release is recomputed, versioned and kept queryable — scores are claims with a date on them, not permanent labels.