AI needs clear tasks
A good AI use case does not start with a tool. It starts with a task: What costs time? What repeats? Where is information searched, assessed, summarized or handed over?
Without this task clarity, AI stays impressive in demos and weak in daily work.
Data and responsibility decide
AI can only support reliably when it is clear which data may be used, who checks the result and where the workflow ends.
If these questions remain open, isolated experiments emerge instead of productive work.
My approach
I prioritize AI use cases by value, data availability, risk, technical feasibility and team acceptance.
Only then does a prototype make sense - and only if it can be integrated into real CRM, email, reporting or operational workflows.