Introducing AI in your organisation, without acting for the sake of it

First, establishing where you stand: who works with which tools today, with which data and at whose expense. As a rule, far more is in use than is officially known. Then come the assessment of possible use cases by effort and impact, the selection of suitable tools, the clarification of data protection and permissions, and understandable rules for use. Finally, enabling the team is what counts, otherwise AI stays a presentation.

No. We are not tied to any vendor and we explicitly name the cases where AI is not worth it. Often the more honest recommendation is to improve the data situation first, tidy up a process or build an interface – after that, using AI is frequently unnecessary or considerably simpler. A tool without a matching use case only produces licence costs.

That is exactly who it is meant for. It is rarely about building your own models, it is about using existing tools sensibly in concrete workflows. We translate the possibilities into projects with recognisable benefit, effort and risk, and we support the rollout. We supported RHEWUM in selecting an AI cockpit that gives every member of staff secure access to capable tools.

With tasks from your daily routine, not with a tool demo. We look for activities that occur often, run the same way every time and are done by hand today, and for the most promising ones we check whether data, permissions and effort add up. In parallel we clarify which data may go into which systems – not least because in many companies people are already working with private accounts.