How do you run an AI readiness diagnostic?

The diagnostic exists because most teams can state the outcome they want and cannot state where their process breaks. Ask an owner where leads get stuck today and the honest answer is often silence. That gap is the whole problem: an agent placed on an undiagnosed workflow automates the leak instead of closing it, at machine speed.

Run it on one workflow at a time, and inspect four things. Data: where the records live, who owns them, and how much of it an agent could act on without a human correcting it afterwards. Handoffs: every point where work changes hands between marketing, sales, success, and finance, and which of those handoffs nobody owns. Permissions: read versus write on each API, one-way versus bidirectional syncs, and which systems should stay walled off entirely. Documentation: whether the process exists anywhere other than in one person's head.

Take a company website as the example, since it anchors most go-to-market effort. Marketing drives traffic to it, product marketing uses it for messaging, product uses it for self-serve conversion, sales leans on the pricing and enablement pages, and customer success uses live chat and case studies. If nobody can say which of those handoffs leaks revenue, an agent sitting on top of all of it fixes nothing.

"Not ready" has recognizable symptoms: a small share of data an agent could act on unsupervised, systems that do not talk to each other, a workflow nobody has written down, no named owner for the records, and no baseline number to compare against after launch. Regulated industries hit these walls first because they are forced to; everyone else discovers them after the purchase order.

The order never changes: diagnose, fix, write it down, then hand it to AI. Skip any of the first three and you are not saving time, you are paying to make an existing problem run faster.