# Energy Auditors

> Conduct energy audits of buildings, building systems, or process systems. May also conduct investment grade audits of buildings or systems.

- **SOC code:** 47-4011.01
- **Canonical URL:** https://singulariki.com/roles/role-47-4011-01
- **Also known as:** Energy Auditor, Energy Consultant, Energy Rater, Home Performance Consultant, Building Performance Consultant, Building Science and Energy Specialist, Building Scientist, Energy Advisor
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Identify and prioritize energy-saving measures.
- Prepare audit reports containing energy analysis results or recommendations for energy cost savings.
- Identify any health or safety issues related to planned weatherization projects.
- Identify opportunities to improve the operation, maintenance, or energy efficiency of building or process systems.
- Calculate potential for energy savings.
- Inspect or evaluate building envelopes, mechanical systems, electrical systems, or process systems to determine the energy consumption of each system.
- Analyze technical feasibility of energy-saving measures, using knowledge of engineering, energy production, energy use, construction, maintenance, system operation, or process systems.
- Examine commercial sites to determine the feasibility of installing equipment that allows building management systems to reduce electricity consumption during peak demand periods.
- Recommend energy-efficient technologies or alternate energy sources.
- Collect and analyze field data related to energy usage.
- 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.
- Perform tests such as blower-door tests to locate air leaks.

**Emerging tasks** (O*NET):
- Evaluate the energy performance of buildings using modeling software.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Customer and Personal Service _(knowledge)_
- Building and Construction _(knowledge)_
- Mathematics _(knowledge)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Written Expression _(ability)_
- Reading Comprehension _(essential_skill)_
- Speaking _(essential_skill)_
- Engineering and Technology _(knowledge)_
- Active Listening _(essential_skill)_
- Critical Thinking _(essential_skill)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Physics _(Specialized Skill)_
- Writing _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Microsoft Word _(hot technology, in demand)_
- Python _(hot technology, in demand)_
- R _(hot technology, in demand)_
- Structured query language SQL _(hot technology, in demand)_
- Adobe Photoshop _(hot technology)_
- Autodesk AutoCAD _(hot technology)_
- C++ _(hot technology)_
- IBM SPSS Statistics _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 54th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 56th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 72nd percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 37th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 53rd percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -0.8% growth (Declining); 14.8k annual openings; 147.6k → 146.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $72,120; 137,210 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-47-4011-01_