Diagnostic · NIST AI Risk Management Framework

Are you actually ready to adopt and sustain AI?

Every week, another company announces it's going all in on AI. What rarely makes the headlines is the quiet failures that follow — expensive tools sitting underused, pilots that stall, audits no one can answer, incidents no one knows how to contain. In most cases the root cause isn't the technology. It's the absence of the governance, mapping, measurement, and management disciplines that NIST formalized in the AI Risk Management Framework.

This assessment is structured around the four AI RMF functions — Govern, Map, Measure, and Manage — and gives you a maturity tier, a per-function breakdown, the specific risks your weakest answers expose you to, and a concrete mitigation (plus how we'd help) for each.

16 questions · ~6 minutes · Instant results, no signup

The premise

What an AI readiness assessment actually answers

An AI readiness assessment answers one question: are we actually ready for this? The NIST AI Risk Management Framework gives that question a structure: four functions (Govern, Map, Measure, Manage) and a set of trustworthy-AI characteristics (validity, safety, security, accountability, explainability, privacy, and managed bias) that any production AI system should be evaluated against.

The output of the assessment isn't a grade. It's a roadmap. It tells you which AI RMF functions need investment before you deploy, which can run in parallel, and where you're already strong enough to move quickly.

Gartner and Forrester have both reported that the majority of AI pilots fail to move beyond proof-of-concept — not because of flawed technology, but because of governance, mapping, and measurement gaps that were never surfaced before deployment. Readiness is buildable. You don't need to be perfect to move forward; you need to know exactly where you stand and what the next move is.

The framework

The four functions of the NIST AI RMF

The AI RMF organizes AI risk management into four interlocking functions. Each is scored independently in this assessment, producing a readiness profile that shows not only where you stand overall but which function to prioritize first.

1. Govern

Culture, policy, accountability, oversight, and third-party / supply-chain risk. The function most often skipped — and the one auditors and regulators look at first.

2. Map

Context, use cases, stakeholders, impacts, and risk tiering of each AI system. Without it, scope creeps silently and high-risk systems get low-risk controls.

3. Measure

Analysis, testing, and evaluation against the trustworthy-AI characteristics: validity, safety, security, accountability, explainability, privacy, and managed bias.

4. Manage

Risk treatment, human oversight, change management, monitoring, incident response, and decommissioning across the AI lifecycle.

Pitfalls

Common mistakes that quietly invalidate the assessment

Treating it as a one-time event

Readiness isn't static. As your data matures and your AI portfolio grows, your profile changes. Reassess regularly, not once.

Limiting the assessment to IT

Technology is one dimension, not the whole picture. Excluding operations, legal, HR, and business leadership produces a view that misses the cultural and governance risks that actually derail projects.

Confusing readiness with enthusiasm

An excited team isn't a ready team. Enthusiasm doesn't substitute for clean data, clear governance, or the skills to act responsibly on AI outputs.

Leaving risk assessment as an afterthought

Bias, compliance exposure, and operational vulnerability are integral to readiness, not a separate exercise. Retrofitting governance onto a deployed system is expensive, slow, and incomplete.

The assessment

AI Readiness Assessment — NIST AI RMF

A structured assessment mapped to the four core functions of the NIST AI Risk Management Framework (AI RMF 1.0): Govern, Map, Measure, and Manage. You get a maturity tier, a per-function breakdown, the specific risks your weakest answers expose you to, and a concrete mitigation plus how we'd help close each one. Takes about 6 minutes.

Mapped to NIST AI RMF: Govern, Map, Measure, Manage
Maturity tier with prioritized AI-RMF-aligned roadmap
Per-function breakdown showing your biggest gaps
Risk + mitigation + how-we-help on every weak answer
Optional branded PDF report — no signup required

Question 1 of 160% complete

Govern

Is there a documented AI governance policy with a named accountable owner — not just IT by default?

AI RMF: Govern 1.1, 2.1 — policies, processes, and clear roles and responsibilities.