How to Choose Your First Business AI Use Case

What makes a business problem suitable for a first pilot?

Look for a task with repeated inputs and a recognizable definition of good work. Preparing an internal meeting brief may be suitable if the source material is accessible and someone can verify the summary. Making an autonomous employment decision is a very different proposition: mistakes can directly affect people and may require specialized oversight.

The first pilot should be bounded enough that the owner can explain what is included in one sentence. “Use AI across sales” is too broad. “Produce an internal draft account brief from approved notes before the weekly account review” is specific enough to test.

Do not confuse frequency with value. A task can occur every day and still be trivial. Ask what improving it would enable: faster responses, fewer missed details, more capacity for customer work, or a better informed decision. If nobody can explain the connection, investigate a different task.

Which questions should executives use to screen ideas?

Use the same questions for every candidate so the most polished demonstration does not automatically win. A simple written comparison exposes missing owners and inaccessible data before the company invests in implementation.

• Value: what observable business outcome would improve?
• Inputs: do usable source materials exist, and may this system process them?
• Reviewability: can a qualified person spot a wrong or incomplete output?
• Ownership: who will change the process and support its users?
• Reversibility: can the team return to the existing process if the pilot fails?
• Evaluation: can you compare performance against a recorded baseline?

How do you compare two promising use cases?

Consider two illustrative candidates: drafting an internal operations summary and answering customers automatically. Both involve generating text, but they have different consequences. An internal summary can be checked before a meeting. A customer answer can create a commitment or misstate a policy before anyone notices.

The internal summary may therefore make a more manageable first experiment, even if the customer application appears to offer more upside. That is a sequencing judgment, not a claim that customer-facing AI is always unsuitable. The organization can build evaluation and escalation capability before expanding the scope.

Avoid hiding judgment inside a weighted spreadsheet. Scoring can help a group compare its assumptions, but a high value score should not cancel out an unresolved data restriction. Treat critical prerequisites as gates. If an input cannot be used lawfully and under the organization’s policies, choose another input or another use case.

What should happen before you fund implementation?

Ask the proposed owner to assemble a small set of representative examples and define the acceptance criteria. A useful criterion describes the work: a summary must preserve the decision, owner, due date, and unresolved question. “Looks good” cannot support a reliable evaluation.

Run through the workflow without automation first. Find out who supplies the information, who reviews the result, and how corrections travel back to the source. Automating a broken handoff can simply accelerate confusion.

Then fund a bounded experiment with an explicit review point. Include time for integration, review, user support, and failed attempts in the estimate. If nobody has capacity to own those tasks, the pilot is not ready, even when the software is readily available.

Where does executive coaching help with prioritization?

Coaching can help an executive distinguish a business priority from a response to pressure. A vendor may emphasize the tool it sells; a functional leader may emphasize the backlog in their department. The CEO needs to compare those requests against the company’s actual constraints.

Bring two candidate use cases to a coaching conversation along with the evidence for each. Examine what must be true for the expected value to materialize, who bears the implementation cost, and what you would stop doing to make room. The outcome should be a defensible choice, including the option to wait for better evidence.