DevOps Engineers
United States · BLS Employment Projections 2024–34 (figures for SOC 15-1299 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
- 57.1%
- GPT-4 rater basis
- 76.8%
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
28 rated tasks · 28 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
- 31.1%
Theoretical exposure index weighted by measured Claude usage, per the original report's definition.
256 tasks · usage observed in 106 · mean 37.0%
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
- Build and maintain CI/CD pipelines
- Automate infrastructure provisioning
- Monitor application performance and reliability
- Design system architecture for scalability
About This Occupation
If you work as a DevOps Engineer, AI is reshaping your profession. With an automation risk of 42/100 and overall exposure at 60%, this role faces high transformation. The highest-impact area is automate infrastructure provisioning at 78% automation. This is classified as an 'augment' role. BLS projects +18% growth through 2034. DevOps professionals who integrate AI-driven observability and automated remediation tools will manage larger, more complex systems with greater efficiency.
ISCO-08 classification
Database and Network 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 includes database and network professionals not classified elsewhere in Minor Group 252: Database and Network Professionals. For instance, the group includes information and communications technology security specialists.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET15-1212.00
Information Security Analysts
Plan, implement, upgrade, or monitor security measures for the protection of computer networks and information. Assess system vulnerabilities for security risks and propose and implement risk mitigation strategies. May ensure appropriate security controls are in place that will safeguard digital files and vital electronic infrastructure. May respond to computer security breaches and viruses.
View original - ONET15-1299.01
Web Administrators
Manage web environment design, deployment, development and maintenance activities. Perform testing and quality assurance of web sites and web applications.
View original - ONET15-1299.08
Computer Systems Engineers/Architects
Design and develop solutions to complex applications problems, system administration issues, or network concerns. Perform systems management and integration functions.
View original - ONET15-1299.09
Information Technology Project Managers
Plan, initiate, and manage information technology (IT) projects. Lead and guide the work of technical staff. Serve as liaison between business and technical aspects of projects. Plan project stages and assess business implications for each stage. Monitor progress to assure deadlines, standards, and cost targets are met.
View original
Frequently Asked Questions
The Anthropic Economic Index puts observed exposure at 31.1%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 57.1% 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: Evergreen blog post published: analysis of DevOps paradox -- 78% infrastructure provisioning automation yet +18% BLS growth projection, driven by AI infrastructure demand.
[Source: AI Changing Work Blog]