AI readiness: definition, areas and approach
Why the Term Matters
Readiness is often misunderstood as a hurdle you must fully clear before starting. That leads to long preparation phases without a result. We use readiness differently, as a fast position check for a concrete case. Instead of assessing the whole company, we check specifically whether a first use case can be built as a prototype with the available data and permissions.
When It Is Relevant
- There is uncertainty whether the data is sufficient for a start.
- Legal questions on data protection and responsibility are unresolved.
- The business unit and IT want to know what is realistically feasible.
- A first use case should start without nasty surprises.
When Not
When a use case is already clear and the data is obviously present, you save a formal check and build a prototype directly. And when it is only about a standard tool that needs no own data, a comprehensive readiness assessment is oversized.
Industries That Use It
- Pharma and life sciences: check whether documentation and research processes are startable with existing data and within regulatory limits.
- Public sector: clarify which procedures can realistically begin with respect to data protection and traceability.
- Trades and construction: assess whether quoting and planning data is structured enough for a first assistant.
- Media and publishing: determine whether archive and content data is usable for an AI-supported workflow.
Typical Use Cases
- A quick check of data quality and availability for a concrete case.
- A clarification of legal limits before the first build.
- A check of technical connections to existing systems.
- An honest assessment of internal skills and responsibility.
- The derivation of the first realistically startable use case.
Decision Guide
| Signal | AI readiness fits | Alternative |
|---|---|---|
| Data uncertain | targeted readiness check | data capture in the business unit |
| Use case clear, data present | rather not | build a prototype directly |
| Legal questions open | readiness with a legal view | internal clarification with data protection |
| Only a standard tool planned | oversized | test the product |
Example
A publisher wants an AI-supported research assistant for its archive and is unsure whether the data is suitable. A short readiness check examines structure, permissions and connectivity and shows that a tightly cut first case is startable. A prototype follows. This describes the approach, not an asserted metric.
Service Connection
The readiness check is part of AI consulting and flows into the AI workshop, from which a prototype for AI implementation emerges.
Sources
This framing describes common practice for a focused readiness check. Legal and technical details depend on the concrete case and the chosen systems and should be checked there.