Methodology

Applied AI Score measures how effectively someone uses AI tools to complete real workplace tasks — not whether they can recite AI trivia or describe how a model works. This page explains how the benchmark is built, scored, and kept fair.

What is measured

Every assessment evaluates eight core competencies that apply across roles:

How scoring works

A general benchmark attempt draws 12 scenario-based questions from a larger bank, weighted across the eight competencies above, and produces an Overall Score plus a per-competency breakdown.

A career-track attempt adds a second layer: 4 role-specific tasks at the candidate's chosen experience level (entry, intermediate, or advanced) for one of ten career tracks — Marketing & Advertising, Sales & Business Development, Human Resources & Recruiting, Administration & Office Support, Customer Service, Project Management, Finance & Accounting, Data & Analytics, Software / IT, and Entrepreneur / Small Business. The career-specific score is combined with the general Core Score using a documented blend — 40% Core Score plus 60% Career Score — to produce a single Overall Career Score for that track and level.

Every scored attempt is tagged with a benchmark version so that results stay comparable over time even as the question bank grows.

What a score is — and is not

Applied AI Score is a practical skills snapshot: how well someone applied AI tools to the specific tasks in this benchmark, on this attempt. It is one input among several — alongside work samples, interviews, references, and experience — and is not a certification, a guarantee of job performance, or a substitute for a full hiring or evaluation process.

Question design and review

Tasks are scenario-based rather than definitional: each one presents a realistic situation (drafting a message, verifying a claim, choosing a tool, reviewing AI-generated output) and asks the candidate to choose the strongest response. Explanations accompany every item so a candidate understands why an answer was correct, not just whether it was.

Fairness and integrity

Question order is randomized per attempt so no two candidates see identical sequencing. Score bands (Foundation, Developing, Proficient, Advanced, Expert) are fixed thresholds applied consistently to every attempt, regardless of who is taking it. We do not use any protected characteristic (race, gender, age, disability, or similar) as an input to scoring, and public result pages only display what a candidate explicitly chooses to share.

Ongoing improvement

The question bank, career tracks, and scoring weights may be refined over time as we learn from real usage. When a scoring change would affect comparability, we version it rather than silently altering past results.

Questions about methodology or a specific score can be directed through our employer contact page or your account support channel.