The best AI opportunity is rarely the most impressive demo. It is the workflow where a recurring problem, usable data, clear ownership, measurable value, and an appropriate review model come together. Prioritization should make those conditions visible before a team chooses a product.
Start with the workflow, not the tool
Describe the work from trigger to final decision. Identify the inputs, handoffs, exceptions, approvals, and evidence that people rely on today. A vague idea such as “use AI for reporting” is not ready to evaluate. “Draft monthly variance commentary from approved actuals and budget data for FP&A review” is specific enough to test.
This step also exposes whether the real problem is missing ownership, inconsistent data, or a broken process. AI will not remove those constraints. In many cases, fixing the operating model creates value before automation begins.
Compare candidates on four dimensions
Business value
Estimate current effort, delay, rework, decision impact, and the number of people affected. Use a baseline the team can measure again after the pilot.
Feasibility
Assess process consistency, data availability, integration effort, and whether the desired output can be evaluated objectively.
Consequence of error
Consider financial, customer, legal, employment, security, and reputational effects. High-risk work may still be valuable, but it needs stronger controls.
Human review
Name the reviewer, the evidence they need, the acceptance criteria, and the conditions that require escalation or rejection.
Choose a pilot that teaches you something useful
A strong first pilot is bounded enough to control and meaningful enough to reveal how the workflow behaves. It should include normal cases, exceptions, and known failure conditions. Define the baseline, test set, approval path, and stop conditions before the first live output.
The goal is not to prove that a model can produce an answer. The goal is to determine whether the redesigned workflow produces a reliable business outcome with acceptable risk, effort, and adoption.
Treat “not yet” as a useful result
Some candidates should move directly into a pilot. Others need cleaner data, a documented policy, or a more stable process. A transparent opportunity map prevents teams from forcing every idea into implementation and gives leaders a defensible sequence for investment.