Industrial Ecologists
United States · BLS Employment Projections 2024–34 (figures for SOC 19-2041 occupational group)
AI exposure in published research
Figures below are reproduced from external datasets without modification. Where a dataset does not cover this occupation, the value is shown as — rather than as zero.
Data provider: OpenAI · "GPTs are GPTs"
Time basis: 2023 baselineex-ante estimate
Scored against GPT-4-generation capability.
- Human rater basis
- 71.3%
- GPT-4 rater basis
- 52.9%
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
38 rated tasks · 38 tasks with β ≥ 0.5 (100.0%)
- Version:
- gh-main-0471612
- License:
- MIT License · Copyright (c) 2024 OpenAI
Data provider: Anthropic Economic Index
Time basis: Published 2026-03-05composite index
- Observed exposure
- 5.5%
Theoretical exposure index weighted by measured Claude usage, per the original report's definition.
86 tasks · usage observed in 5 · mean 5.5%
Data: Anthropic Economic Index — labor_market_impacts, CC-BY, https://huggingface.co/datasets/Anthropic/EconomicIndex
AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.
- Version:
- hf-lmi-2026-03
- License:
- CC BY 4.0
- Observation period:
- — (not applicable to this release)
- Model:
- — (not stated by the source)
- Definition source:
- https://www.anthropic.com/research/labor-market-impacts
2023 prediction vs observation-based index published 2026-03-05
One card (GPTs are GPTs) is a 2023 estimate of what AI could theoretically do; the other (Anthropic Economic Index) is built from observed usage and was published on 2026-03-05 — that is its publication date, not the period it observed. They measure different things, so the two figures cannot be added, averaged, or ranked against each other. The older figure is kept here as a baseline for comparison rather than removed.
Caution: the Anthropic figures — observed exposure and task penetration — take the Eloundou β as one of their inputs. The two sides resembling each other is therefore not evidence that the earlier prediction came true; reading it that way is circular reasoning.
The Anthropic figures are measured on Claude users, who are not the whole economy and not the whole workforce.
The mapping of O*NET tasks and occupation codes was performed by AI Changing Work. The source figures themselves were not modified.
These indices are not forecasts. Which point in time each one belongs to is stated on the badge on its card.
Task Breakdown
- Conduct life cycle assessments of products and industrial processes
- Model material and energy flows through industrial systems
- Advise organizations on circular economy and waste reduction strategies
- Analyze environmental impact data and compile sustainability reports
About This Occupation
If you work as an Industrial Ecologist, AI is progressively transforming your profession. With an automation risk of 27/100 and overall exposure at 42%, this role faces medium transformation. The highest-impact area is analyzing environmental impact data and compiling sustainability reports at 65% automation. This is classified as an 'augment' role. BLS projects +7% growth through 2034. AI-enhanced life cycle assessment tools and material flow analysis platforms are accelerating sustainability work, while strategic advisory and stakeholder engagement remain human-driven.
ISCO-08 classification
Environmental Protection Professionals
Definition
ILO original text (English)
Environmental protection professionals study and assess the effects on the environment of human activity such as air, water and noise pollution, soil contamination, climate change, toxic waste and depletion and degradation of natural resources. They develop plans and solutions to protect, conserve, restore, minimize and prevent further damage to the environment.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET19-1031.00
Conservation Scientists
Manage, improve, and protect natural resources to maximize their use without damaging the environment. May conduct soil surveys and develop plans to eliminate soil erosion or to protect rangelands. May instruct farmers, agricultural production managers, or ranchers in best ways to use crop rotation, contour plowing, or terracing to conserve soil and water; in the number and kind of livestock and forage plants best suited to particular ranges; and in range and farm improvements, such as fencing and reservoirs for stock watering.
View original - ONET19-2041.00
Environmental Scientists and Specialists, Including Health
Conduct research or perform investigation for the purpose of identifying, abating, or eliminating sources of pollutants or hazards that affect either the environment or public health. Using knowledge of various scientific disciplines, may collect, synthesize, study, report, and recommend action based on data derived from measurements or observations of air, food, soil, water, and other sources.
View original - ONET19-2041.03
Industrial Ecologists
Apply principles and processes of natural ecosystems to develop models for efficient industrial systems. Use knowledge from the physical and social sciences to maximize effective use of natural resources in the production and use of goods and services. Examine societal issues and their relationship with both technical systems and the environment.
View original
Frequently Asked Questions
The Anthropic Economic Index puts observed exposure at 5.5%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 71.3% under human raters. Both figures are reproduced from published research without modification.
They come from two published datasets: the Anthropic Economic Index (labor_market_impacts, CC BY 4.0) and the OpenAI "GPTs are GPTs" exposure rubric (MIT License, Copyright (c) 2024 OpenAI). AI Changing Work maps them onto O*NET occupation and task codes and does not calculate exposure scores of its own. AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.
No. They are a diagnosis of exposure as measured at the time each source dataset was published. AI Changing Work publishes no prediction of future automation or job displacement for this occupation.
Recent Changes Affecting This Occupation
Mar 2026: Published evergreen blog post analyzing AI impact on industrial ecologists (42% exposure, 27% risk, augment mode)
[Source: AI Changing Work Blog]