Computer Forensics Analysts
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
- 59.1%
- GPT-4 rater basis
- 79.5%
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
22 rated tasks · 21 tasks with β ≥ 0.5 (95.5%)
- 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.
— This occupation code is not included in this dataset.
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
- Recover and analyze deleted files and data artifacts
- Conduct chain-of-custody documentation for digital evidence
- Testify as expert witness in court proceedings
About This Occupation
If you work as a Computer Forensics Analyst, AI is augmenting your data recovery and pattern detection capabilities. With an automation risk of 30/100 and overall exposure at 58%, this role faces high transformation. File recovery and analysis sees the highest automation at 65%. BLS projects +32% growth through 2034.
ISCO-08 classification
Information and Communications Technology Operations Technicians
Indirect mapping — this occupation is linked to the ISCO unit group by a rule-based fallback.
Definition
ILO original text (English)
Information and communications technology operations technicians support the day-to-day processing, operation and monitoring of information and communications technology systems, peripherlas, hardware, software and related computer equipment to ensure optimal performance and identify any problems.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET15-1299.04
Penetration Testers
Evaluate network system security by conducting simulated internal and external cyberattacks using adversary tools and techniques. Attempt to breach and exploit critical systems and gain access to sensitive information to assess system security.
View original - ONET15-1299.06
Digital Forensics Analysts
Conduct investigations on computer-based crimes establishing documentary or physical evidence, such as digital media and logs associated with cyber intrusion incidents. Analyze digital evidence and investigate computer security incidents to derive information in support of system and network vulnerability mitigation. Preserve and present computer-related evidence in support of criminal, fraud, counterintelligence, or law enforcement investigations.
View original - ONET15-1299.07
Blockchain Engineers
Maintain and support distributed and decentralized blockchain-based networks or block-chain applications such as cryptocurrency exchange, payment processing, document sharing, and digital voting. Design and deploy secure block-chain design patterns and solutions over geographically distributed networks using advanced technologies. May assist with infrastructure setup and testing for application transparency and security.
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 59.1% 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.