Energy & Natural Resources
National Career Cluster · the map of work
Energy & Natural Resources is one of the 14 national career clusters — the U.S. Department of Education's map that divides the whole world of work into broad families, each crosswalked to occupations, education programs, and industries. This cluster spans 87 occupations across 6 sub-clusters, employing about 9,172,240 workers, with a median wage of $70,500.
What's in this cluster
A career cluster is a navigational grouping, not a measured score. The counts below come from the framework's official crosswalk; employment and pay are aggregated from BLS OEWS (national, cross-industry, May 2024) across the occupations in the cluster.
Across occupations with wage data, the middle range (25th–75th percentile of occupation medians) runs $59,220 – $95,435. This describes the cluster, not any one job or person.
Sub-clusters
The framework splits each cluster into sub-clusters — tighter families of related work. The count is the number of occupations the crosswalk places in each.
| Sub-cluster | Occupations |
|---|---|
| Resource Extraction | 35 |
| Utilities | 28 |
| Ecological Research & Development | 25 |
| Conservation & Land Management | 18 |
| Clean & Alternative Energy | 13 |
| Environmental Protection | 9 |
Largest occupations in this cluster
Occupations in this cluster with the most workers nationally (BLS OEWS, May 2024), each linked to its full profile. Employment and pay describe the occupation, not an individual.
AI exposure across this cluster
Two published studies estimate how exposed each occupation is to today's AI. The OpenAI "GPTs are GPTs" study rates the share of an occupation's tasks a large language model (with tools) could speed up by half or more; averaged across this cluster it is 29% — 39th percentile of the 14 clusters. The independent Felten/Raj/Seamans AI Occupational Exposure index averages 0.01 here.
Computed across the 83 of 87 occupations in this cluster that carry a published exposure score.
Exposure measures where AI could assist tasks — it is not a prediction that these jobs will be automated. High exposure most often means augmentation (faster work), and many high-exposure occupations are also projected to grow.
Where the work sits
The framework anchors each cluster to one or more NAICS industry sectors — the parts of the economy where this work concentrates.
- Mining, Quarrying, and Oil and Gas Extraction · NAICS 21
- Utilities · NAICS 22
Education programs that lead here
A sample of the 247 CIP 2020 instructional programs the framework crosswalks to this cluster — the fields of study that prepare people for this work.
- Acoustics
- Agricultural and Horticultural Plant Breeding
- Agriculture, General
- Agroecology and Sustainable Agriculture
- Agronomy and Crop Science
- Analytical Chemistry
- Anatomy
- Animal Behavior and Ethology
- Animal Genetics
- Animal Physiology
- Applied Economics
- Applied Statistics, General
- Aquatic Biology/Limnology
- Astronomy
- Astronomy and Astrophysics, Other
- Astrophysics
- Atmospheric Chemistry and Climatology
- Atmospheric Physics and Dynamics
- Atmospheric Sciences and Meteorology, General
- Atmospheric Sciences and Meteorology, Other
- Atomic/Molecular Physics
- Behavioral Neuroscience
- Biochemistry
- Biochemistry and Molecular Biology
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- Census NAICS 2022 U.S. Census Bureau
- CIP-2020 2020 U.S. National Center for Education Statistics
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
Data compiled June 3, 2026. Figures are estimates, not advice.
Cite this page
Singulariki. "Energy & Natural Resources." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; CIP-2020 2020; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026. https://singulariki.com/clusters/energy-natural-resources
Singulariki. (2026). Energy & Natural Resources. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/clusters/energy-natural-resources
@misc{singulariki-energy-natural-resources,
title = {Energy & Natural Resources},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; Census NAICS 2022; CIP-2020 2020; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans. Accessed June 7, 2026},
url = {https://singulariki.com/clusters/energy-natural-resources}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.