How to choose your first AI workflow

Start with an observable process

Choose a piece of work with a clear trigger and a recognizable end. “Use AI in operations” is too broad to evaluate. “Prepare a first draft of the weekly project summary from approved project notes” is specific enough to discuss inputs, ownership and review. Write down who starts the work, where the information comes from and who receives the result.

Measure the existing work

Record a small sample before changing anything. How often does the task occur? How long does preparation take? How much review is already required? Which handovers cause waiting? Keep observations separate from estimates. A frequent task with a substantial review burden can still be a poor pilot if the information is inconsistent or the consequences of an error are difficult to contain.

Ask four practical questions

First, is the task repeated often enough to justify designing and maintaining a workflow? Second, are the necessary inputs available and suitable for the intended use? Third, can a competent person check the result without redoing the entire task? Fourth, can an incorrect result be detected and corrected before it causes a material problem? A negative answer identifies work to do before implementation.

Choose a small, reversible pilot

Define one intended output and a set of representative examples, including incomplete information and unusual cases. Start with a draft or recommendation that a person reviews. Agree on access, permitted information and a stop condition. An illustrative pilot might assemble a draft internal report while the process owner checks every claim against its source. This example is a design pattern, not a claim about a particular customer result.

Evaluate the whole workflow

Compare preparation time, review time, errors and handover effort with the starting point. Record the cases that need manual intervention. Do not count a faster draft as a gain if reviewing it creates more work downstream. Decide whether to continue, change the scope or stop. Keep a named owner and a review date even when the pilot becomes routine.

General information and practical frameworks. The legal requirements for a particular organization or use case require individual assessment.

The AI Workflow Playbook