Academic Coaches
United States · BLS Employment Projections 2024–34 (figures for SOC 25-3099 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
- —
- GPT-4 rater basis
- —
This occupation code is not included in this dataset.
This occupation code is not included in this dataset.
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
— This occupation code is not included in this dataset.
- License:
- MIT License · Copyright (c) 2024 OpenAI
Data provider: Anthropic Economic Index
Time basis: Published 2026-03-05composite index
- Observed exposure
- —
This occupation code is not included in this dataset.
Theoretical exposure index weighted by measured Claude usage, per the original report's definition.
17 tasks · usage observed in 5 · mean 26.8%
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
- Assess student learning needs and create personalized plans
- Provide one-on-one mentoring and motivation support
- Track student progress and generate performance reports
About This Occupation
If you work as an Academic Coach, AI is augmenting your role moderately. With an automation risk of 28/100 and overall exposure at 44%, progress tracking and reporting (72% automation) is the most impacted task. BLS projects +9% growth through 2034.
ISCO-08 classification
Teaching Professionals Not Elsewhere Classified
Indirect mapping — this occupation is linked to the ISCO unit group by a rule-based fallback.
Definition
ILO original text (English)
This unit group covers teaching professionals not classified elsewhere in Sub-major Group 23: Teaching Professionals. For instance, the group includes those who provide private tuition in subjects other than foreign languages and the arts, and those who provide educational counselling to students.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET25-3031.00
Substitute Teachers, Short-Term
Teach students on a short-term basis as a temporary replacement for a regular classroom teacher, typically using the regular teacher's lesson plan.
View original - ONET25-3041.00
Tutors
Instruct individual students or small groups of students in academic subjects to support formal class instruction or to prepare students for standardized or admissions tests.
View original
Frequently Asked Questions
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.