From individual-dependent expertise to connected, governed, adaptive organizational intelligence. Where your organization is, where it needs to be, and what has to become true in between.
Agentic Quotient (AQ) maps where your organization sits on the six AI maturity stages, and the gap to where it needs to be.
Buying AI tools does not move you up a level. Each level is a real change in how your organization’s know-how gets put to work, by people and by AI. The question is not “are we using AI?” It is “which stage are we at, and which stage does our work need?”
Critical expertise leaves with people. The organization is not ready to operationalize AI.
Core condition: The organization depends on individual expertise that it cannot reliably preserve or reproduce.
Identify, capture, and validate critical organizational knowledge.
People use AI independently. Productivity gains remain personal and disconnected.
Core condition: AI increases individual capability, but the gains remain largely personal.
Turn individual discoveries into repeatable team practices.
Prompts and workflows spread across teams, but execution still depends on people.
Core condition: AI practices spread across teams, but people still connect the pieces.
Connect workflows, data, tools, and decisions across team boundaries.
AI, people and systems execute proven workflows across team boundaries.
Core condition: Organizational expertise begins to translate into coordinated execution.
Make connected execution reliable through institutional knowledge, governance, and operating standards.
Governed workflows encode how the business operates, preserving and reusing expertise.
Core condition: Organizational expertise becomes a durable, governed component of the operating model.
Establish governed feedback loops that improve performance based on measured outcomes.
People and AI learn from outcomes and continuously improve how work gets done.
Core condition: The organization has a governed mechanism for improving how its expertise is applied.
Sustain measurable improvement while maintaining appropriate governance, human oversight, and control.
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. The six levels fall into three movements.
The organization moves from fragile, individual-dependent expertise toward shared, reusable knowledge and practices.
The organization converts expertise into connected, reliable, governed workflows that can operate across the business. AQ3 is the inflection point: AI stops being a set of isolated tools and starts to run coordinated work.
The organization uses measured outcomes and controlled feedback loops to improve how work gets done.
AQ measures how well an organization turns its collective expertise, judgment and institutional knowledge into repeatable, governed, AI-enabled execution. It is not a count of tools, agents or pilots, and none of those raise a score on their own. Each level asks for a different kind of evidence:
Using AI is AQ1. Putting it into real workflows that produce measured results is what moves an organization to AQ3.
Gains that stay with one person are AQ1. Practices teams share and reuse are AQ2.
A shared library of prompts and playbooks is AQ2. Knowledge that a workflow actually runs on, kept current in maintained systems, is AQ4.
Workflows that cross team boundaries are AQ3. Workflows with owners, permissions, escalation paths and audit trails are AQ4.
AQ5 needs a working improvement loop: outcomes measured, changes made and tested, and results measured again. Clever agents or the odd prompt change do not count.
The 36 questions are also read as four capabilities, so the detailed report can show strengths and gaps that a single number would hide. They are diagnostic: they never change the headline scores.
Is critical knowledge captured, accurate, reachable and reused beyond one person? Matters from AQ1.
Do systems and workflows connect end to end, and do redesigned workflows reach production? Matters from AQ3.
Are ownership, roles and handoffs, trusted information and repeatable scaling in place? Matters from AQ3.
Is value measured, are outcomes changing, and does a regular review act on the evidence? Matters from AQ4.
The stage you need depends on your work. The assessment asks where your organization needs to be within 24 months, then measures the gap from where your answers place it today. These are the questions that shape the answer. We think most organizations need at least AQ3 (AQ opinion).
How repeatable is the work? The more it repeats, the more it pays to systematize.
How concentrated is the expertise? When know-how sits in a few heads, the risk of losing it is higher.
How regulated is it? Heavier compliance raises the bar on ownership and oversight.
How much can run unattended? More automation potential means a higher ceiling.
Is expertise the product? If judgment is what you sell, making it executable is the whole game.
These questions shape an advisory view of your target. Your instrument target is the stage your leaders say you need within 24 months. Your report then shows the gap: current stage against target, stage by stage, with the first move to make.
Step 01 of the AQ methodology, AQ Readiness. Your score is free. 36 Questions · 7–10 minutes. Or have your whole leadership team take it and see where you disagree.
Get your AQ score, free → Assess your leadership team