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What Actually Happens in an AI Audit

Wondering what an AI consultant actually does? Here's exactly what happens during an AI Audit — the questions, the deliverable, and what most business owners discover.

AI StrategyBusinessAI Consulting

Most business owners who reach out to me have the same question: "What exactly do I get?" Fair question. The AI consulting space is full of vague promises and PowerPoint decks that don't lead anywhere. So let me just tell you what an AI Audit looks like, step by step.

What an AI Audit Is (and Isn't)

It's not a sales call dressed up as a discovery session. It's not a generic report about how AI is going to change your industry. And it's not me telling you to buy ChatGPT Plus.

An AI Audit is a structured 90-minute working session — followed by a written deliverable — that maps your current operations against specific AI opportunities. The goal is to give you a clear picture of where AI can actually help your business, what it would take, and what to do first.

The First 20 Minutes: Understanding How You Work

Before we talk about AI at all, I ask questions about your operations. Things like:

  • What does a typical week look like for you and your team?
  • What are the most time-consuming tasks that happen on a regular schedule?
  • Where do things fall through the cracks?
  • What do your customers or clients ask you most often?

I'm listening for patterns. Repetition. Volume. The stuff that's eating hours but feels too small to hire for — or that you've already hired for, but it's still a bottleneck.

A recent client ran a 30-person home services company. In the first 20 minutes, it came out that her office manager spent 2-3 hours every Monday compiling job reports from three different systems into a spreadsheet that went to exactly one person. Nobody had ever questioned it. It just happened every week.

The Next 40 Minutes: Going Deeper on Specific Workflows

Once I have the lay of the land, we go deeper on 3-5 workflows that looked promising in the first pass. I ask:

  • Who's involved in this process?
  • What tools or software does it touch?
  • What's the input and what's the output?
  • What happens when it breaks or gets delayed?
  • Has anyone tried to improve it before? What happened?

I document this in real time. Not notes I'll clean up later — a working map of the process, inputs and outputs, dependencies, and where judgment calls happen. That last part matters. AI handles routine decisions well. It handles edge cases poorly. Knowing where your humans need to stay in the loop is half the work.

The Last 30 Minutes: Prioritization

Not everything that could be automated should be automated first. We end the session by ranking the opportunities we found against three criteria:

  1. How much time or money is this actually costing you?
  2. How clean is the data or process? (Messy inputs make bad AI outputs.)
  3. How much would your team actually use this?

That last one gets skipped in most AI conversations. I've seen companies spend $40K on tools their teams quietly stopped using within 60 days. Adoption matters as much as capability.

The Deliverable

Within a week of the session, you get a written AI Opportunity Report. It includes:

  • A plain-English summary of each opportunity we identified
  • An honest assessment of complexity and cost to implement
  • A recommended starting point — one thing, not a list of 12
  • Notes on what to watch out for (data quality issues, integration constraints, change management concerns)

The report is yours. You can take it to a developer, a different consultant, or your internal team. There's no gotcha where the audit only makes sense if you hire me for the next phase.

What Clients Usually Discover

The most common finding is that the biggest opportunity isn't the one they came in thinking it was. A marketing agency owner came in convinced he needed AI to write content faster. We spent 90 minutes together and the real opportunity was automating his client onboarding process, which was eating 6+ hours per new client across his team. Content was a distraction.

The second most common finding is that they're further along than they thought. They already have structured data, they already use tools with APIs, their team is already curious about AI. They just needed someone to connect the dots.

Who This Is For

If you're running a business with 10 to 100 people, you probably have more AI opportunity than you realize. You also probably don't need to spend $50K to find it. The Audit is designed to give you a real answer — not a proposal for more consulting — in a contained, low-risk engagement.

If you want to know what's actually possible for your specific business, book an AI Audit.

Want the broader picture?

If the writing is useful, the projects page shows the fuller body of work. And if there's a role, project, or idea worth comparing notes on, email me.