AI readiness scorecard

Is your organisation ready to adopt AI responsibly?

Use this quick scorecard to identify whether your next step is a small clarity sprint, a governance design engagement, or deeper platform and integration work.

1. AI inventory

You know where AI is already used, who owns it, what data it touches, and which vendor or internal system provides it.

Score 0-2

2. Use-case prioritisation

AI opportunities are ranked by value, risk, data readiness, operational dependency, and the decision they improve.

Score 0-2

3. Data and privacy controls

Teams know what cannot be sent to AI tools, how sensitive data is handled, and when privacy or legal review is required.

Score 0-2

4. Governance and decision rights

There is a clear path for approving AI uses, assigning accountability, documenting evidence, and escalating higher-risk decisions.

Score 0-2

5. Architecture and integration

AI workflows can connect to the right APIs, data platforms, identity controls, logs, and operational systems without fragile workarounds.

Score 0-2

6. Human oversight

People know when AI output must be reviewed, who can act on it, and what happens when the system is uncertain or wrong.

Score 0-2

Use this in a leadership discussion

Have each stakeholder score independently, then compare the gaps. Misalignment is useful evidence: it shows where governance, architecture, privacy, or delivery assumptions need to be made explicit before AI reaches production.