Our Mission & Standards

AI is changing work.
People need an evidence layer.

JobsVsAI measures how artificial intelligence is reshaping occupational tasks, helping professionals understand what is vulnerable, what remains uniquely human, and where to move next.

The Problem

Career decisions need more than dramatic headlines

Most public discussion around AI and employment swings between tech-utopian optimism and sensational doom. Neither extreme helps an individual professional decide whether to specialize, retrain, adopt new tools, or transition careers.

Broad predictions based on job titles alone ignore how work actually happens. Two occupations with similar titles can have completely different task compositions, physical demands, and regulatory environments.

Our Approach

Evidence first. Action second.

We believe career intelligence must be grounded in task-level evidence rather than speculation. We decompose occupations into discrete work activities from O*NET 30.3, evaluate those activities against verified AI capability benchmarks, and apply structural modifiers for physical reality, human dependency, and adoption economics.

A high score is a signal to adapt, not a prediction of unemployment. Our mission is to help people make informed career moves with confidence.

Core Philosophy

Know what AI can change.
Know what you can do next.

JobsVsAI is career decision infrastructure—not a fear calculator. We provide the intelligence layer for navigating modern work.

Integrity & Research Standards

The principles guiding our research

How we ensure independence, reproducibility, and rigorous disclosure.

01

Evidence before inference

Every score originates from validated task statements, not high-level impressions of an occupation's prestige or title.

02

No pay-to-rank

Scores, rankings, and career comparisons are 100% algorithmic and independent of commercial advertisers or corporate sponsors.

03

Limitations published

Where proxy models are used or evidence coverage is partial, confidence scores and provisional shares are disclosed openly.

04

Uncertainty shown

Preliminary estimates are displayed as ranges rather than fake precision points, and excluded from headline rankings.

05

Traceable sources

Data connects directly to O*NET 30.3 classifications and our published Frontier AI Capability Index.

06

Actionable outcomes

Every risk assessment is paired with human advantage highlights, action plans, and realistic career transition paths.