AI
Where AI actually creates value in business workflows
AI is useful when it sits inside a real process — not when it is added as a layer of novelty on top of unclear work.
Most businesses do not have an AI problem. They have a work problem: slow handoffs, repeated data entry, decisions waiting on one person, or information that cannot be trusted.
AI creates value when it is applied to a specific workflow with a clear input, a clear output, and a measurable cost of doing that work today. Summarizing a meeting is useful. Replacing an undefined decision process with a chatbot is not.
The practical test is simple. Can you describe the task without mentioning AI? If the answer is “we need something smart,” the need is still unclear. If the answer is “every invoice is typed into two systems,” you have a candidate.
We look for four kinds of leverage: less manual work, higher accuracy, faster decisions, and new capability that was not feasible before. If a proposed AI project cannot name one of these, it is probably a demonstration — not a system.
The other half of the work is people. A well-designed assistant that nobody trusts will sit unused. Training, context, and a clear operating rule — when the human decides — are part of the solution, not an afterthought.