The most common question today is "what can we do with AI?". It is a fair question, but it starts at the end. It pays to ask first in which processes a better, or faster, decision would really change results.
The conditions that matter
Every use case rests on three conditions. Available, reliable data for that process. A person who owns the final decision and knows when not to trust the system. A way of telling, after a few weeks, whether it is working.
When one of these is missing, the project can still go ahead, but it is an experiment. Treat it as one, with a small scope and a date to decide whether to continue.
Rules before rollout
Meanwhile, many people already use generative AI tools on their own. Ignoring that is not caution. A few clear rules are needed on what data not to share, which tools to use and how to check the output.
AI doesn't replace the foundations: it tests them. The businesses that get value from it are, almost always, the ones that have already put their data and responsibilities in order.