Health Information Technologists
United States · BLS Employment Projections 2024–34 (figures for SOC 15-1211 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
- 63.6%
- GPT-4 rater basis
- 48.5%
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
17 rated tasks · 16 tasks with β ≥ 0.5 (94.1%)
- 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
- 27.6%
Theoretical exposure index weighted by measured Claude usage, per the original report's definition.
25 tasks · usage observed in 13 · mean 45.5%
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
- Implement and maintain electronic health record systems
- Analyze healthcare data for quality improvement initiatives
- Ensure data security and HIPAA compliance
- Design clinical decision support tools and dashboards
- Train clinical staff on health information systems
About This Occupation
If you work as a Health Information Technologist, AI is reshaping your profession. With an automation risk of 46/100 and overall exposure at 57%, this role faces high transformation. The highest-impact area is analyze healthcare data for quality improvement initiatives at 70% automation. This is classified as an 'augment' role. BLS projects +17% growth through 2034. Growing demand for interoperable health systems and AI-driven analytics is expanding this field even as automation handles routine data tasks.
ISCO-08 classification
Systems Analysts
Indirect mapping — this occupation is linked to the ISCO unit group by a rule-based fallback.
Definition
ILO original text (English)
Systems analysts conduct research, analyse and evaluate client information technology requirements, procedures or problems, and develop and implement proposals, recommendations and plans to improve current or future information systems.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET15-1211.00
Computer Systems Analysts
Analyze science, engineering, business, and other data processing problems to develop and implement solutions to complex applications problems, system administration issues, or network concerns. Perform systems management and integration functions, improve existing computer systems, and review computer system capabilities, workflow, and schedule limitations. May analyze or recommend commercially available software.
View original - ONET15-1211.01
Health Informatics Specialists
Apply knowledge of nursing and informatics to assist in the design, development, and ongoing modification of computerized health care systems. May educate staff and assist in problem solving to promote the implementation of the health care system.
View original - ONET15-1221.00
Computer and Information Research Scientists
Conduct research into fundamental computer and information science as theorists, designers, or inventors. Develop solutions to problems in the field of computer hardware and software.
View original
Frequently Asked Questions
The Anthropic Economic Index puts observed exposure at 27.6%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 63.6% 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
Apr 2026: ATE 0.36 by 2026 in SF Bay Tier 1 — among the earliest 84 occupations crossing the moderate-risk threshold. Workflow coverage averages 0.96 despite 2 of 16 O*NET tasks triggering P2 regulatory penalties (diagnosis coding).
[Source: arXiv 2604.00186 (Gupta & Kumar, 2026)]Mar 2026: New blog post: health IT faces 63% exposure, 51% risk but 17% BLS growth.
[Source: ACW Blog]