Leadership teams, take note: your employees already know the best AI use cases — they just do not realise it yet.

Leadership teams, take note: your employees already know the best AI use cases — they just do not realise it yet.

After more than 15 AI use-case workshops, I can say that 20–30 use cases in four hours are always achievable.

The foundation: a transparent process. If you do not know your process, you cannot find AI opportunities.

The team then works through the process together, step by step — guided by eight questions:

1️⃣ Is the step repetitive or does it follow a clear pattern?

2️⃣ Is text, image, speech or numerical material processed?

3️⃣ Are there unstructured inputs, such as emails, PDFs or documents?

4️⃣ Does information from multiple sources need to be combined?

5️⃣ Is content created, such as text, calculations or visuals?

6️⃣ Is there manual routine work, such as searching, checking or copying and pasting?

7️⃣ Are decisions, priorities or classifications made?

8️⃣ Is relevant data available digitally?

At least one "yes" = AI potential exists.

But here is the crucial point:
it is not about the number of use cases. It is about choosing and prioritising the right ones.
More importantly, use cases alone achieve nothing.
What organisations really need is a holistic approach to AI implementation. That is why I developed the AI Maturity Test — ten dimensions that show where an organisation really stands and what needs to come next.
Because the best use-case list is useless if governance, infrastructure or leadership culture do not keep pace.

A systematic approach beats frantic activity.

💬 How do you approach this — collect use cases or build the foundation first?

👉 Write "AI Maturity Test" in the comments — I will send you the link to my free test. In just a few minutes, you get a baseline assessment: where do you stand with AI implementation? And which areas need management attention to make AI implementation successful?

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