The AI audit that watches your team work.
An AI audit usually means a questionnaire. The Shadow Day is different: we spend a day inside your real workflows and end with a ranked map of where AI pays off first.
The premise
Most companies don't need an AI strategy deck. They need to know which three workflows are worth fixing, what each is worth, and which one to start with. That takes specificity, and specificity comes from watching the work, not surveying it. People describe their process the way it's supposed to run. The waste lives in the way it actually runs.
How the day runs
The audit starts before we arrive: a public-data baseline run the week before, covering your stack, your team shape, and the signals your industry leaves in the open. Then the day itself, shadowing either the leader or two to four team members through real work: the meetings, the handoffs, the copy-paste between systems. The day closes with a live debrief, and you get a one-page bottom line the same day. The full report follows within two business days.
Why we call it the Shadow Day
Because that's what it is: an AI shadow day, spent beside the people who do the work. The name keeps us honest about the method. No questionnaire reconstructs the friction a day of observation surfaces, and no vendor demo tells you which workflow your team will actually adopt.
What you walk away with
Three to five specific calls, each framed as buy, build, automate, agent, or delegate, ranked by value and lift, plus the one we'd start with first. The report is specific enough to act on without us. If you do continue, the audit fee credits toward a workshop or sprint within 30 days.
What it is not
The audit doesn't install tools, build automations, write SOPs, or train your team. Those are workshop and sprint scope, and mixing them into a diagnostic is how diagnostics go soft. One day, one job: find where AI pays off first, and say so plainly. Not ready yet? Take the free AI readiness assessment and bring your score to the call.
FAQ
What is an AI audit?
An AI audit is a structured look at where AI would pay off in your business, and where it wouldn't. Most are run by questionnaire. Ours runs by observation, because people describe their workflows the way they're supposed to work, not the way they do.
What's the difference between an AI audit and an AI readiness assessment?
An AI readiness assessment is the free, self-serve version of an AI audit: it scores where you stand in about five minutes. The audit is a paid day inside your real workflows, and it tells you what to do. Take the assessment first and bring your score.
What do we get at the end?
You get a ranked opportunity map: each workflow worth automating, what it's worth, what it would take, and what to do first. Think of it as an AI opportunity assessment with evidence behind every line, specific enough to act on without us.
Who needs to be in the room?
The people doing the work we're shadowing need to be there, plus one decision-maker for the wrap-up. The day splits between team observation and an executive session.
What if the audit says we're not ready?
If the audit says you're not ready, it tells you that directly, along with what to fix first. An honest no after one day costs far less than a pilot that was never going to stick, and it preserves your team's trust in the next attempt.
Specificity before commitment.
One day. A ranked opportunity map. An honest go or no-go. Start there before you commit to anything bigger.