Business AI field guide

What does an AI opportunity audit cover?

An AI opportunity audit reviews a recurring task before proposing technology. It maps the workflow and tools, identifies priorities and dependencies, and proposes a next step with checks for the output. The free audit is delivered within one week after completed intake and required access.

By Michael Berger

Bring a workflow, not a shopping list.

Describe what triggers the task, who handles it, which tools are involved, and what a finished output should contain. Identify where information is copied, delayed, or corrected. A process owner should explain the exceptions as well as the usual path. The intake accepts this context without confidential customer records or credentials.

Review inputs, access, and handoffs.

The audit asks where the information comes from, whether it is current, and which system receives the result. It distinguishes a rule-based integration from a task requiring interpretation. Missing access, inconsistent records, or an undefined decision owner become prerequisites, rather than assumptions hidden in a proposal.

Receive a map and a practical next step.

The deliverables describe the workflow and systems reviewed, prioritize opportunities with their dependencies, and outline a proposed implementation scope. The next step includes a way to check outputs before launch. This is a planning exercise; it does not install production integrations or promise a financial return.

Decide whether to commission implementation.

Implementation is a separate decision with a written scope. Review the deliverables, required access, approval points, software costs, and acceptance checks before proceeding. If the task can be handled by a simpler rule or a process change, that belongs in the recommendation too.

Compare the next step.

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