Specific AI use cases can be identified by companies systematically analyzing their processes, data, and pain points. Instead of starting from available technologies, the focus should be on specific problems, inefficiencies, or decision-making needs. This is exactly where AI delivers its greatest value.
A proven starting point is the structured review of core business processes along the value chain as part of an AI potential analysis. This involves identifying activities that are time-consuming, error-prone, or heavily data-driven—such as manual checks, evaluations of large data sets, or recurring decisions based on similar patterns. Additionally, it is worth looking at bottlenecks, media breaks, or tasks that currently have limited scalability. This is often where the first, very specific AI ideas emerge.
In the next step, potential use cases should be roughly evaluated. Key guiding questions include: What business benefit does the use case promise? How high is the implementation effort? Is the required data available and usable? And can the application be integrated into existing processes? Without this classification, you can quickly end up with a long but unreliable list of ideas.
As part of our structured AI potential analysis, we work together to identify specific use cases tailored to your needs. These are then systematically evaluated and prioritized. The result is not just a collection of ideas, but a clear basis for decision-making, allowing next steps such as AI strategy development or the development of specific solutions to be addressed in a targeted manner.
