The strongest companies do not begin with a tool list. They start with a process that takes too long, produces costly mistakes, or asks capable people to repeat low-value work. AI is a possible answer, not the starting point.
A strong use case is not the most impressive one. It is the one where a better decision or a minute saved can be connected to a business result.
Start with friction, not the tool
Talk to the people doing the work. Look for moments where they read many documents, compare information, classify requests, search for knowledge, or produce the same initial draft again and again. Then ask about volume, error cost, and how consistently the output can be described.
Assess five dimensions
- Value: can an improvement affect time, quality, risk, or revenue?
- Feasibility: are input and output clear enough to describe?
- Data: are reliable examples, feedback, or source systems available?
- Risk: can human review remain proportionate to the decision?
- Adoption: will someone own and use the changed process?
Do not default to full automation
For an initial use case, a system that prepares, classifies, or flags can create more value than one that acts autonomously. The model proposes, a person handles ambiguous cases, and feedback improves the system. Risk decreases and impact becomes measurable.