AI Readiness Scorecard for Leadership Teams

Our leadership team can explain in one sentence what AI should do for our business in the next 12 months.

We have named a senior owner for AI with time and budget to act.

Our AI initiatives are linked to two or three business goals with numbers attached.

We decide which AI pilots to stop as clearly as which to start.

Leaders use AI tools themselves every week and talk openly about it.

We know where our most important data lives and who is responsible for its quality.

Teams can access the data they need without weeks of manual work.

We have approved AI tools that employees can use safely today.

Our core systems can connect to AI services through APIs or integrations.

We can measure the cost and performance of the AI we run.

Most employees have had practical AI training linked to their own work.

We have internal champions who help colleagues use AI well.

Roles and responsibilities are being updated where AI changes the work.

People feel safe to say where AI fails or creates risk.

We hire and promote for the ability to learn and work with new tools.

We have redesigned at least one end to end process around AI, not just added a tool.

Successful pilots have a clear path to scale with budget and owners.

We measure time, quality or revenue effects of AI before and after.

Customers notice better speed or service where we use AI.

Teams share what works across departments instead of starting from zero.

We have a clear, short AI policy that employees know and follow.

We review AI use cases for privacy, bias, security and legal risk before launch.

We know which AI regulations apply to us, including the EU AI Act where relevant.

A human is accountable for every decision AI supports in critical processes.

We can explain to a customer or regulator how our AI is used.