Gini Loh System Tools

AI Automation Index

Will AI Replace Energy Engineers, Except Wind and Solar?

Task-level automation exposure for Energy Engineers, Except Wind and Solar: 21 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

54% weighted task index

21 of 21 tasks scored

Median Salary

$122,930 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

High

154,070 people hold this job — size, not growth

Projected 2025–35

+3.7% employment change

8,800 openings a year · BLS line item

Pay by state

BLS OEWS publishes 53 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$76,100 – $162,070

Highest medians

New Mexico $162,070
Alabama $152,550
District of Columbia $151,920
Virginia $148,160
Alaska $142,390

Lowest medians

Kansas $76,100
Arkansas $76,940
Puerto Rico $81,370
Nebraska $88,490
Tennessee $96,640

State figures come from the 17-2199 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

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.

Automation potential 54%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 0%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 49%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 5%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 10/100 Low

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.

Constituent Task Mix

21 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 57%

12 tasks

Medium exposure (≥ 35%) 23%

5 tasks

Low exposure (below 35%) 20%

4 tasks

How would you survive?

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 →

Constituent Tasks

#20854 · Core · 75% automatable

Identify and recommend energy savings strategies to achieve more energy-efficient operation.

data analysis — Energy usage analysis is standard quantitative work

Analyze energy usage data. Advise others regarding green practices or environmental concerns.
#20859 · Core · 45% automatable

Collect data for energy conservation analyses, using jobsite observation, field inspections, or sub-metering.

data analysis — Energy modeling aided; field measurement human

Research energy production, use, or conservation.
#18156 · Core · 62% automatable

Monitor and analyze energy consumption.

data analysis — Consumption data monitoring is largely digital and analyzable

Monitor industrial energy consumption or management.
#20861 · Core · 75% automatable

Prepare energy-related project reports or related documentation.

text generation — Operational reports drafted from data

Prepare technical or operational reports.
#20856 · Core · 28% automatable

Monitor energy related design or construction issues, such as energy engineering, energy management, or sustainable design.

decision support — Energy operations direction needs real-time human control

Direct energy production or management activities.
#20855 · Core · 62% automatable

Conduct energy audits to evaluate energy use and to identify conservation and cost reduction measures.

data analysis — Consumption data monitoring is largely digital and analyzable

Monitor industrial energy consumption or management.
#18159 · Core · 60% automatable

Analyze, interpret, or create graphical representations of energy data, using engineering software.

data analysis — AI builds computational models; engineer validates assumptions

Create models of engineering designs or methods.
#18166 · Core · 40% automatable

Train personnel or clients on topics such as energy management.

interpersonal — Operational procedure training needs live demonstration

Train personnel on proper operational procedures.
#20857 · Core · 70% automatable

Advise clients or colleagues on topics such as climate control systems, energy modeling, data logging, sustainable design, or energy auditing.

information retrieval — Green practice advice is largely informational

Advise others regarding green practices or environmental concerns.
#18148 · Core · 60% automatable

Perform energy modeling, measurement, verification, commissioning, or retro-commissioning.

data analysis — AI builds computational models; engineer validates assumptions

Create models of engineering designs or methods.
#20858 · Core · 80% automatable

Verify energy bills and meter readings.

data analysis — Energy usage analysis is standard quantitative work

Analyze energy usage data.
#20860 · Core · 58% automatable

Review architectural, mechanical, or electrical plans or specifications to evaluate energy efficiency.

data analysis — Analyzes specs for implications; expert judgment required

Evaluate plans or specifications to determine technological or environmental implications.
#18150 · Core · 20% automatable

Inspect or monitor energy systems, including heating, ventilating, and air conditioning (HVAC) or daylighting systems to determine energy use or potential energy savings.

visual inspection — Equipment/system inspection requires physical presence

Inspect equipment or systems.
#18151 · Core · 28% automatable

Manage the development, design, or construction of energy conservation projects to ensure acceptability of budgets and time lines, conformance to federal and state laws, or adherence to approved specifications.

decision support — Energy operations direction needs real-time human control

Direct energy production or management activities.
#20862 · Core · 28% automatable

Direct the implementation of energy management projects.

decision support — Energy operations direction needs real-time human control

Direct energy production or management activities.
#18157 · Core · 62% automatable

Promote awareness or use of alternative or renewable energy sources.

text generation — Campaign content and analysis drafted; human executes strategy

Perform marketing activities.
#20864 · Core · 68% automatable

Recommend best fuel for specific sites or circumstances.

decision support — Proposes design changes; human validates feasibility

Recommend technical design or process changes to improve efficiency, quality, or performance.
#19648 · Core · 35% automatable

Write or install energy management routines for building automation systems.

physical manipulation — Operating systems requires hands-on interaction

Operate computer systems.
#20863 · Supplemental · 45% automatable

Research renewable or alternative energy systems or technologies, such as solar thermal or photovoltaic energy.

information retrieval — Green tech literature aided; engineering validation human

Research design or application of green technologies.
#18165 · Supplemental · 65% automatable

Review or negotiate energy purchase agreements.

decision support — Procurement drafting and comparison; human commits funds

Purchase materials, equipment, or other resources.
#18149 · Supplemental · 70% automatable

Consult with construction or renovation clients or other engineers on topics such as Leadership in Energy and Environmental Design (LEED) or Green Buildings.

information retrieval — Green practice advice is largely informational

Advise others regarding green practices or environmental concerns.
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Community Sentiment

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Method

How this was scored

  1. 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
  2. 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
  3. 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
  4. 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

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 →

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