Begin with friction, not software.
Begin with friction, not software
Ask where your team repeats the same low-judgement task, searches for the same information, or loses time moving work between people. Those patterns are more useful than a list of popular AI products.
Choose a narrow first use case
A focused workflow is easier to test, safer to change, and clearer to measure. Examples might include turning meeting notes into structured actions or drafting a first response that a person reviews.
Keep a person responsible
AI output needs ownership. Decide who checks accuracy, handles unusual situations, and can turn the system off. Useful automation supports judgement rather than hiding it.
Measure the real change
Track time saved, error rates, adoption, and the quality of the handoff, not the novelty of the tool. Expand only when the evidence supports it.
Once you have picked a candidate workflow, map it before you automate it. If you would rather have this framework ask you the questions, the AI Opportunity Check runs the same reasoning over one process in about three minutes and is quite willing to tell you not to bother.
Turning a map into something dependable is what business systems is for, and the longer version of this framework is in our practical guide to AI for small businesses.
