An AI audit should turn a broad ambition into a ranked set of opportunities, risks and next decisions. It is valuable before selecting a model or committing to implementation.
Start with the business process
Map the trigger, inputs, decisions, handoffs, exceptions and outcome of the current workflow. Record where time is lost, where quality varies and which errors matter to the user or business.
Check whether AI is appropriate
- Is the task probabilistic, language-heavy or pattern-based?
- Are representative examples and lawful data access available?
- Can the output be evaluated before it causes harm?
- Is a deterministic rule or normal software workflow a better fit?
Produce decision-ready outputs
The audit should document the priority workflow, baseline evidence, data and integration constraints, risk classification, evaluation method, human-review boundary and a recommended build, discovery or stop decision.
Reject theatre
A generic maturity score, impressive demo or savings estimate is not an audit result. The result must be traceable to the organisation’s own workflow and evidence.
Turn the decision into a scoped plan
Bring the workflow, affected users, available data, constraints and desired outcome to a needs-assessment call. PilotProof will recommend a proportionate next step and prepare a proposal only after the scope and assumptions are clear.