The AI Risk Assessment tool helps enterprise teams identify where AI exposure is already present across workflows, vendors, and data handling practices.
It is designed for organisations that need a practical first-pass view of shadow AI, governance gaps, model misuse risk, compliance exposure, and vendor dependency before scaling further.
Instead of producing generic maturity language, the assessment focuses on operational risk signals that affect security, legal posture, delivery confidence, and executive decision-making.
Who this tool is for
- Leadership teams deciding whether current AI activity is safe to expand
- Security, compliance, or legal stakeholders needing a structured AI risk baseline
- Programme owners trying to prioritise mitigation before new AI deployments
What you get from it
- A clearer view of your highest-risk implementation patterns
- A practical shortlist of issues to address first
- A stronger starting point for governance, vendor review, and production readiness
What this tool evaluates
Common questions this tool helps answer
What does this assessment actually measure?
It evaluates the operational risk profile of your current or planned AI deployment, including unsanctioned usage, third-party dependency, data handling exposure, governance maturity, and implementation control.
Who should complete the AI Risk Assessment?
It is most useful for founders, CIOs, CTOs, heads of innovation, risk teams, and programme leads who need a quick but structured picture of AI risk before making delivery or investment decisions.
What should happen after the score is generated?
The output should be used as an initial triage tool. High-risk signals usually point to the need for policy definition, vendor review, data controls, role clarity, and a formal roadmap for safe deployment.
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