The question “Where can we use AI?” is too broad. A better question is “Which parts of this process benefit from prediction, language, search or automation, and what level of autonomy is appropriate?”
Decompose the workflow
Break the process into tasks. Identify where people gather information, interpret unstructured material, make decisions, communicate, create artifacts or execute actions in software.
Score the task, not the hype
Consider repetition, data availability, tolerance for error, reversibility, sensitivity, decision impact and how easily a person can verify the output. Tasks with high volume and low consequence often make strong starting points.
Choose an autonomy level
AI can assist a human, make a recommendation, execute a bounded action after approval, or act within predefined permissions. Increasing autonomy can increase value, but it should also increase observability and control.
Measure the operating result
Track whether the change actually improves cycle time, quality, cost, customer experience or another business outcome. Adoption is not the objective. Better performance is.
Keep exploring
Turn the idea into an operating move.
Continue with a practical resource, a structured system, or an advisory conversation when context matters.
