Resources
In-depth guides on AI skills assessment methodology, hiring practices, integrity, and workforce benchmarking.
The State of AI Fluency 2026
The first AI fluency benchmark measured from real behaviour, not self-reported. Average score, percentiles, the ten personas, and where the skill gaps actually are — baseline edition from 412 assessments (now 1,800+).
AI Assessment Methods Compared [2026]
Self-report surveys, quizzes, simulations, and conversational assessments each measure different things. What works, what doesn't, and how to choose.
Why Conversational AI Assessment Works
Self-reported AI skills correlate poorly with actual ability (r = 0.07–0.24). Conversational assessment measures real behaviour, not checkboxes.
AISA's Assessment Framework: Validity & Evidence
AISA's AI skills assessment audited against 10 world-class assessment qualities — with ratings, evidence, and what we're building next.
Free AI Skills Assessment: Test Your AI Skills
Free AI skills assessment through conversation, not quizzes. Scored across 5 dimensions and 11 criteria. Get your AI skills certificate.
The 10 AI Persona Types: AI Fluency Profiles
AISA's 10 AI persona types — from Bystander to Oracle. What each persona means, how they differ, and what they signal about AI fluency.
2026 AI Skills Report: Assessment Data Insights
AI proficiency patterns across roles, dimensions, and personas — what AISA's scoring surfaces and why it matters for hiring and L&D.
Hiring AI-Native Builders: Beyond Tech Interviews
Traditional tech interviews were built for writing code from scratch. AI-native work demands different skills — here's how to assess them.
The AI Skills Gap: Benchmark & Upskill
For L&D leaders: measure your team's AI proficiency with evidence-based assessment, identify gaps, and build targeted upskilling plans.
Beyond Multiple Choice: Preventing AI Cheating
MCQ-based AI assessments are trivially gamed. AISA's conversational architecture generates unfakeable evidence of real proficiency — here's how.
The AISA Rubric: 5 Dimensions, 11 Criteria
The AI fluency framework behind AISA — 11 criteria across 5 dimensions. What each measures, how scoring works, and why demonstrated skill wins.
The Science Behind AISA
In 2026, Anthropic published the AI Fluency Index — the largest empirical study of AI fluency to date, analysing nearly 10,000 conversations. AISA covers 93% of the behaviours Anthropic identified as markers of AI fluency and goes even deeper with 4 additional dimensions. The U.S. Department of Labor's AI Literacy Framework (TEN 07-25) defines what every worker needs to know about AI — AISA covers 100% of its 25 sub-competencies.Read our analysis: Anthropic's AI Fluency Study & AISA · DOL AI Literacy Framework & AISA
AISA's framework is developed by a team with deep roots in tech, behavioural science, and AI product leadership — the rubric is informed by backgrounds spanning the Metropolitan Police, Harvard, Crowdbotics (Silicon Valley), and the European School of Economics.
