When small teams begin using AI, it is easy to explore a range of tools first and only then discuss what to do with them. I prefer to look for a starting point in the team's working week: What happens repeatedly? Which tasks involve searching back and forth across several documents? Which first drafts start from a blank page every time? These specific pieces of work usually make a better first step than trying to make the entire business AI-driven.
A task worth trying should have consistent inputs, a clear output, and someone who can check the result. Examples include turning a project meeting into a task list, drafting answers to common questions from verified product information, or preparing different versions of an article whose ideas are already established. The more clearly the task is defined, the easier it is to see what the tool has actually helped with.
Once a task is chosen, document the existing approach. How long does it take to complete? At which step does work usually have to be redone? What makes the result ready to deliver? These records need not be complicated, but they help the team avoid judging effectiveness solely by how quickly something is generated. If drafting takes less time but review and revision take substantially more, the process needs to be redesigned before its use is expanded.
Next, bring the reliable source materials, task requirements, and output format together in a short brief. Specify which information must come directly from the source materials, where suggestions are allowed, and which questions must be referred to the person in charge. When customer information is involved, first confirm permission to use it and check the tool's data handling settings, then decide what information to provide. The process should account for these practical working conditions.
A trial can cover a small set of real tasks, with someone who understands the business checking the results and recording the types of errors. Is information missing? Are the instructions unclear? Or does the task itself require more judgment? Making adjustments one by one according to the cause makes it easier to build experience than repeatedly switching tools. At the end of the trial, decide whether to keep, revise, or stop the approach.
For a small team, a good first step should produce a working method that can be handed over: who provides the materials, which part AI handles, who reviews the work, and where the results are saved. Only when that method reliably helps the team get its work done does AI move from individual experimentation into organizational capability. Further expansion should follow processes that have already been tested.