Which AI projects are best suited for getting started?

Entry-level AI projects work best when they are clearly scoped and show results quickly. Projects with the following characteristics tend to perform particularly well:

• Clear use case: A concrete problem with an unambiguous benefit, one that works without major IT dependencies and offers a sensible expansion path.
• Confirmed feasibility: Technology, data, and target vision are aligned. Open research questions are avoided or deliberately started as a pilot.
• Available data foundation: Internal data exists and is usable. Structure and access are clarified so that value can be created quickly.
• Internal advocates and visibility: Business units are on board, the benefit is easy to explain and visible in daily work. This creates buy-in and motivation.
• Low regulatory hurdles: For the starting point, highly regulated or particularly high-risk projects should be avoided.

In short: Good entry projects start small, deliver early results, and create the foundation to embed AI in the organization step by step.