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AI Automation Index
Task-level automation exposure for Energy Auditors: 21 O*NET tasks scored against their work activities, plus the simulator.
Automation Exposure
21 of 21 tasks scored
Median Salary
BLS OEWS, May 2025 — this exact occupation
Employment Level
146,720 people hold this job — size, not growth
Projected 2025–35
14,800 openings a year · BLS line item
BLS OEWS publishes 53 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$44,320 – $102,410
Highest medians
Lowest medians
State figures come from the 47-4011 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Importance-weighted mean of the scored tasks. This is the headline index.
Share of weighted tasks in hands-on or machine-operating work activities.
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Share in documenting, recording, and administrative activities.
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
21 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
15 tasks
3 tasks
3 tasks
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.
Evaluate the energy performance of buildings using modeling software.
Identify and prioritize energy-saving measures.
data analysis — AI analyzes operations to flag efficiency gains
Prepare audit reports containing energy analysis results or recommendations for energy cost savings.
data analysis — Reports and budgets drafted; human owns assumptions
Identify any health or safety issues related to planned weatherization projects.
decision support — Green-tech investment risk; human owns decisions
Identify opportunities to improve the operation, maintenance, or energy efficiency of building or process systems.
data analysis — AI analyzes operations to flag efficiency gains
Calculate potential for energy savings.
data analysis — Organizational calculations from given data
Inspect or evaluate building envelopes, mechanical systems, electrical systems, or process systems to determine the energy consumption of each system.
visual inspection — Physical spec verification of facilities/equipment
Analyze technical feasibility of energy-saving measures, using knowledge of engineering, energy production, energy use, construction, maintenance, system operation, or process systems.
data analysis — Cost-effectiveness modeling from given data
Examine commercial sites to determine the feasibility of installing equipment that allows building management systems to reduce electricity consumption during peak demand periods.
visual inspection — Physical property inspection needs on-site sensory judgment
Recommend energy-efficient technologies or alternate energy sources.
decision support — Drafts advice; accountability and context owned by human
Collect and analyze field data related to energy usage.
data analysis — Energy usage analysis is standard quantitative work
Measure energy usage with devices such as data loggers, universal data recorders, light meters, sling psychrometers, psychrometric charts, flue gas analyzers, amp probes, watt meters, volt meters, thermometers, or utility meters.
data analysis — Energy usage analysis is standard quantitative work
Educate customers on energy efficiency or answer questions on topics such as the costs of running household appliances or the selection of energy-efficient appliances.
text generation — Written correspondence to customers is largely automatable
Perform tests such as blower-door tests to locate air leaks.
physical manipulation — Material characteristic testing needs physical instruments
Prepare job specification sheets for home energy improvements, such as attic insulation, window retrofits, or heating system upgrades.
decision support — Technical specs drafted; human verifies
Inspect newly installed energy-efficient equipment to ensure that it was installed properly and is performing according to specifications.
visual inspection — Physical spec verification of facilities/equipment
Analyze energy bills, including utility rates or tariffs, to gather historical energy usage data.
data analysis — Energy usage analysis is standard quantitative work
Quantify energy consumption to establish baselines for energy use or need.
data analysis — Energy usage analysis is standard quantitative work
Determine patterns of building use to show annual or monthly needs for heating, cooling, lighting, or other energy needs.
data analysis — Energy usage analysis is standard quantitative work
Compare existing energy consumption levels to normative data.
data analysis — Energy usage analysis is standard quantitative work
Oversee installation of equipment such as water heater wraps, pipe insulation, weatherstripping, door sweeps, or low-flow showerheads to improve energy efficiency.
interpersonal — Overseeing business processes requires human accountability
Verify income eligibility of participants in publicly financed weatherization programs.
decision support — Eligibility screening against rules, human decides edge cases
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<script src="https://giniloh.com/embed.js" async></script> Community Sentiment
Do you agree with the AI automation risk score calculated for this occupation?
Method
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
See the full method →Related Article
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