A business can decide its priorities before running an AI trial. What it cannot know in advance is how well a particular tool will handle its work, or how much checking that result will need.
I would keep those two kinds of decision separate. Plan what matters to the business now, then test the uncertain parts before committing to a wider rollout.
Make the decisions that do not need a trial
You can decide which problem deserves attention, what you are prepared to spend investigating it and which uses are outside the business’s limits. You can also decide who is responsible for customer information and who can approve a new service.
Write those decisions plainly. They give a trial boundaries without pretending to know its result.
Turn an assumption into a question
Suppose a fictional business plans to use AI to draft customer reports because it expects to halve preparation time. Before building that saving into a staffing or delivery commitment, ask what a trial must establish.
It may need to test whether the tool finds the relevant facts, whether the reports answer each customer’s questions and how long review takes. Supplier terms and existing records can answer some other questions without a trial, such as contract costs and current report volumes.
Let the result change the plan
Imagine the trial finds that straightforward reports are quicker, while reports involving disputed figures need as much work as before. The next plan could limit AI drafting to the straightforward reports, retain the existing method for the rest and use a smaller saving estimate.
That is a specific change supported by the trial. It does not show that the same tool will suit sales emails or personnel records. Those uses have different information and consequences.
Keep the uncertain findings visible. If the trial missed the busiest month, say so. If review capacity limits how many reports can be handled, use that limit when planning expansion.
A strategy becomes useful when it says what the business will do, why and what would cause it to reconsider. A long list of possible AI uses contributes little until those choices are made. The next-project guide helps compare the candidates once you have evidence from the first.
About Jay
I’m Jay Janes, a Practical AI Advisor and founder of Reformat Labs. I write about choosing useful work for AI, checking the results and supporting the people using it.