Know which workflow deserves AI funding before you spend on a pilot.
Score the cost of manual work, rework, customer delay, data readiness, compliance risk, urgency, and sponsorship so the first AI build has a real business case.
Stop guessing where AI should start.
The audit turns business pain into a ranked decision. It is built for leaders who need to defend budget, reduce waste, and choose the workflow with the clearest path to measurable value.
Manual effort and queue volume
Find the work that consumes the most team hours, slows customers, and repeats often enough to justify automation.
Error, rework, and exception cost
Estimate where mistakes, duplicate checks, and unresolved exceptions are quietly eating margin.
Data and integration readiness
Check whether the workflow has usable data, stable systems, APIs, ownership, and access controls.
Risk, governance, and approval paths
Identify where humans must review, where logs are required, and where AI should never act alone.
Know whether to build, prepare, or pause.
Some workflows are ready for an AI pilot. Others need cleaner data, clearer ownership, better exception handling, or a simpler product workflow first. The audit helps separate signal from excitement.
Opportunity score
A directional score that compares value, readiness, urgency, and risk.
Pilot recommendation
Whether to audit deeper, build a controlled pilot, prepare data first, or avoid automation.
Delivery map
The people, systems, integrations, safeguards, and success measures needed for the next stage.
Answer once. Get a practical readiness signal.
The form is submittable and connected to the AI audit backend. With analytics consent, public field progress is also visible in the admin activity panel so your team can recover serious abandoned inquiries.
When the audit is strong, AI Loop can move from score to system.
We can take the highest-priority workflow into discovery, prototype, secure pilot, production build, or managed operation with the same value map.