Where your org stands. And how.
Aggregated Intelligence Posture framework. One score across People, Infrastructure, and Regulation. Maturity models have matured.
AI governance isn’t just one problem. How your people collaborate with AI, how agent-ready your infrastructure is, how prepared you are for AI-specific regulations, these all matter. Your org is only as strong as the weakest link.
Estimate your AI Posture
You’re 5-7 minutes from your estimated AI Posture and evidence checklist per vector. No cookies, no cost, no gate.
- Adaptive. Three openers set scope. Then up to five Bayesian-adaptive questions per in-scope vector. Normally fewer.
- Estimate-labeled. A point estimate per vector with full posterior on hover. Aggregate AI Posture bounded by the weakest in-scope vector.
- Evidence checklist. Per vector, the artifacts that would turn the estimate into a verified assertion.
- Client-side. Answers live in your browser tab. Aggregate analytics only. No personal identifiers.
The three vectors
AI governance is three independent problems. Each has its own evidence base, its own stakeholders, its own reference product. AI Posture aggregates them into one score so an organization knows where it actually stands.
People
How effectively humans in the organization collaborate with AI. Behavioral, not self-reported. Evidence must resolve to an artifact a third party can inspect.
Infrastructure
How ready the organization's digital systems are for AI agent interaction, from internal systems to partner integrations to public-facing surfaces.
Regulation
How completely the organization has met its AI-specific obligations across the jurisdictions that bind it.
The constraint rule
Your AI Posture is the minimum of your three vector levels. An organization Calibrating on People but Perceiving on Regulation has an AI Posture of Perceiving. This is structural, not a scoring convenience.
A Calibrating People score without a Calibrating Regulation score cannot support a defensible compliance narrative. A Calibrating Infrastructure score without Calibrating People cannot support a claim of responsible human-AI collaboration. The vectors constrain each other because the domains do.
The five-level maturity model
Each vector is scored on a shared five-level scale. The same level means the same kind of thing on every vector: the object changes, the shape of the progression does not.
| # | Level | What it means |
|---|---|---|
| 0 | N/A | Vector not in scope. N/A is a falsifiable claim — a contradicted N/A invalidates the entire assertion. |
| 1 | Perceiving | Aware the domain exists. No deliberate action yet. |
| 2 | Assessing | Inventorying current state. No deliberate practice. |
| 3 | Integrating | Deliberate practice in place. Evidence starting to accumulate. |
| 4 | Calibrating | Practice measured, tuned, defensible to outside reviewers. |
| 5 | Engineering | Systematized. Advancing the frontier, not catching up. |
Reporting format
One score, one slide. The constraining vector makes the investment case.
Aggregated Intelligence Posture: Assessing
Scope: Acme Corp, organizational
Stamped: 2026-04-20
Next review: 2026-10-20
People: Calibrating ████████░░ since 2025-09-01
Infrastructure: Integrating ██████░░░░ since 2026-02-14
Regulation: Assessing ████░░░░░░ since 2026-04-20
Constraining vector: Regulation
Recommended next action: Advance Regulation to IntegratingRead the spec
The normative definition of AI Posture lives in SPEC.md. It covers the vector set, the five-level model, the constraint rule, decay, and the relationship to NIST AI RMF, ISO/IEC 42001, and the EU AI Act.