Agentic Quotient · AQ

Every company can buy AI.
Few can put their own expertise to work.

AQ measures how much of what your organization knows is actually executable — by people and AI. Take the assessment and see your score benchmarked against your industry.

Free · 35 questions · about 12 minutes · No login to start

New here? AQ in one breath

Agentic Quotient (AQ) is a common-sense way to decide the smartest way to get work done — hire a person, add AI, combine the two, or rethink the work.

Built for the people making that call — founders, CHROs, and department leaders. Not sure it's for you? See who needs it & why →

What you get

A number, a benchmark, and a plan — not another framework to read

The AQ Assessment turns a fuzzy question — “how ready are we, really?” — into something you can act on. Thirty-five questions: thirty across the five stages of the AQ Engine, then five on your profile.

01

Your AQ score

A 0–100 rating across the five stages of the AQ Engine — Capture, Operationalize, Amplify, Improve, Govern — mapped to the AQ0–AQ5 maturity levels.

02

An industry benchmark

Where you land against comparable organizations, your Destination AQ, and which stage is quietly holding you back.

03

Recommended moves

A sequenced shortlist — the stage throttling your AQ and the specific move that raises it — instead of a vague “become more AI-ready.”

Built for CEOs, CHROs, and transformation leaders deciding where AI actually changes the work — and where human judgment still wins.

Why AQ matters

Companies don’t lose because they picked the wrong model

They lose because decades of expertise stay trapped inside individuals, documents, and meetings — invisible to the AI they just paid for. AI amplifies what’s been captured and made repeatable. Everything else walks out the door when people do.

Low AQ

Buys more AI tools. Knowledge lives in people’s heads. Every departure is a loss. The same budget keeps producing the same little.

High AQ

Makes expertise executable. Best practices become systems people and agents run. The same AI budget produces more, and compounds.

The AQ Engine

Five stages that turn what you know into what you can execute

Each stage builds on the one before it — from expertise trapped in people to a system that improves itself.

1

Capture

Get expertise out of people’s heads and into systems.

2

Operationalize

Turn it into workflows and rules that produce the same result every time.

3

Amplify

Put people and AI to work running those systems together, at scale.

4

Improve

Feed every result back in, so the system sharpens instead of going stale.

5

Govern

Make ownership and oversight explicit enough to scale safely.

The AQ Maturity Model

Six levels, from knowledge eroding to an organization that improves itself

AQ0Eroding. Knowledge leaves when people do.
AQ1Individual. People use AI on their own.
AQ2Team. Teams share prompts and workflows.
AQ3Connected. Agents execute across systems.◆ the decisive shift
AQ4Operational. Institutional knowledge is the operating playbook.
AQ5Adaptive. Humans and agents improve the system continuously.
What a higher AQ is worth

The case for AQ isn’t that it’s elegant — it’s that raising it moves the numbers

Institutional memory

Knowledge stops leaving with people.

Faster onboarding

New people reach competence against a system, not by osmosis.

Return on AI

The same AI budget produces more.

Operational leverage

Expertise executes everywhere it’s relevant, at once.

Compounding advantage

The system gets better with use.

Durable differentiation

The advantage isn’t for sale.

Find out where you actually stand

Thirty-five questions, about twelve minutes. A score, an industry benchmark, and a shortlist of the smartest moves to make next.

Get your AQ score →