Computer Network Architects
United States · BLS Employment Projections 2024–34 (figures for SOC 15-1241 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
- 55.5%
- GPT-4 rater basis
- 66.4%
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
33 rated tasks · 31 tasks with β ≥ 0.5 (93.9%)
- 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
- 19.9%
Theoretical exposure index weighted by measured Claude usage, per the original report's definition.
58 tasks · usage observed in 13 · mean 19.2%
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
- Design cloud infrastructure and network architecture
- Monitor network performance and optimize configurations
- Evaluate security protocols and compliance requirements
- Coordinate with teams on infrastructure migration plans
About This Occupation
If you work as a Computer Network Architect, AI is reshaping your profession. With an automation risk of 25/100 and overall exposure at 38%, this role faces medium transformation. The highest-impact area is monitor network performance and optimize configurations at 68% automation. This is classified as an 'augment' role. BLS projects 4% growth through 2034. Architects who adopt AI-powered monitoring and auto-scaling tools can focus more on strategic design decisions and emerging cloud technologies.
ISCO-08 classification
Computer Network Professionals
Indirect mapping — this occupation is linked to the ISCO unit group by a rule-based fallback.
Definition
ILO original text (English)
Computer network professionals research, analyse, design, test and recommend strategies for network architecture and development. They implement, manage, maintain and configure network hardware and software, and monitor, troubleshoot and optimize performance.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET15-1241.00
Computer Network Architects
Design and implement computer and information networks, such as local area networks (LAN), wide area networks (WAN), intranets, extranets, and other data communications networks. Perform network modeling, analysis, and planning, including analysis of capacity needs for network infrastructures. May also design network and computer security measures. May research and recommend network and data communications hardware and software.
View original - ONET15-1241.01
Telecommunications Engineering Specialists
Design or configure wired, wireless, and satellite communications systems for voice, video, and data services. Supervise installation, service, and maintenance.
View original
Frequently Asked Questions
The Anthropic Economic Index puts observed exposure at 19.9%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 55.5% 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 why cloud architects have the lowest automation risk (25%) in the computer-and-math category, with AI driving increased demand.
[Source: AI Changing Work Blog]Mar 2026: Published evergreen blog analysis: AI exposure 38%, automation risk 25/100 in 2025.
[Source: AI Changing Work Blog]