AQ aligns your leadership team on one AI strategy for the whole organization. It maps where you stand on six AI maturity stages, shows the stage your work actually needs, and spells out the gap between the two.
Your AQ is your stage, AQ0 to AQ5. The scores behind it show why. Agentic Quotient (AQ) maps where your organization sits on the six AI maturity stages, and the gap to where it needs to be.
Step 01, AQ Readiness · Free score · Full report $25 · 36 Questions · 7–10 minutes · No login · Team assessments from $50
Below AQ3, AI makes individuals faster but your knowledge still lives in people’s heads. It walks out the door, and every AI tool has to be fed by hand. At AQ3 and above, proven work runs through systems that people and AI execute together. That is where we expect AI spending to start paying back (hypothesis, being tested).
People use AI on their own. Teams swap prompts. Results depend on who did the work. Spending goes up, returns stay flat, and nobody can say how ready the company really is.
Know-how is captured and runs as shared workflows. AI executes the repeatable path, people handle the exceptions, and someone owns every automated decision. The same AI budget compounds.
Most AI arrives bottom up: a function builds a tool for its own problem, a technical team ships an agent and then tries to get the business to adopt it. Those builds can deliver real value, but they are not a strategy. Each one runs on its own data and its own slice of the company’s know-how, so nothing compounds. AQ aligns the leadership team on one view of the whole organization first, so every build adds to a single system of intelligence.
Each function and technical team builds its own tools. Every project has to be sold to the rest of the organization. Knowledge and data are duplicated, nobody owns how the pieces fit, and value stays where it was built.
Leaders agree where the organization stands and what AI is for. Shared knowledge, data and controls are decided once, in a governed intelligence layer, with MCPs connecting it to every outside system. Every new build plugs into the same foundation, so each one makes the next cheaper and better.
Data warehouses and pipelines store and move data, but they do not decide what AI may know, where it may act, or who answers for the result. We recommend one governed intelligence layer on top of the data architecture, with each outside system connected once through a governed MCP connector. This is our view of how to close the gap, not part of your AQ score.
Organizations don’t create lasting value simply by adopting more AI. They create it by turning collective expertise into connected, governed execution – and building systems that learn from outcomes and improve over time.
AI pays back when leaders agree where the company stands and what AI is for. Each AQ tool answers one question, in order, so you go from where you are today to what to change and who it affects.
Your stage today (AQ0 to AQ5), the stage you need within 24 months, and the gap between them.
Why: you cannot plan the move until your leaders agree on the starting point. Take it alone, or send one link to your whole leadership team.
Get your AQ score, free →Assess your leadership team →A role broken into its tasks: what AI can take over, what it can assist, and what must stay human.
Why: it shows where AI can pay back in the work people actually do.
Rate a role →Your whole workforce mapped: where the work goes, when, and where the people go.
Why: you can plan for your people before the change reaches them.
Map your workforce →Free results in every tool. Full reports and team assessments are on the pricing page. Two more tools, Workforce Strategy and Capability Strategy, are on the tools page.
36 Questions · 7–10 minutes. Your AI Readiness, AI Execution and Agentic Potential, your AQ Constraint, and the gap to where you need to be.
Get your AQ score, free →