Your rankings and traffic can look healthy while AI answers misrepresent your business. Brian Winum walks through the MAXPlaces AI Readiness Audit, from crawler access and connected structured data to entity clarity and the answers customers receive. He explains how his team turns those findings into a prioritized plan.
Key Takeaways
Show notes
A marketing director receives a Sunday text from her CEO: why is ChatGPT saying the company no longer offers commercial work? Brian Winum opens this episode of MAXVolume with that account of an AI answer contradicting a business’s actual services. Rankings, traffic, and the homepage all looked healthy, yet the answer reaching a potential customer was wrong. The story introduces the gap he wants an AI Readiness Audit to investigate.
Brian explains the MAXPlaces audit as an examination of what AI systems can reach, understand, and report about a business. His team scores eight categories on a 100-point scale: Emerging below 40, Developing from 40 to 69, Competitive from 70 to 84, and Leading from 85. These are the MAXPlaces methodology’s assessment bands. Each finding is meant to include evidence and a specific corrective action so the score leads to practical work.
He groups those categories into four questions, beginning with access and comprehension. Can the relevant crawlers retrieve the site, and can they make sense of the content? Brian discusses robots.txt rules, page construction, performance, and structured data. He describes disconnected information about services, reviews, and the company as a recurring audit finding, then connects clearer answer content with Answer Engine Optimization (AEO).
The third question is about entity clarity: can an AI system distinguish this business from another? Brian discusses inconsistent legal names, brand names, and nicknames, along with an example in which an engine confused a client with a similarly named company in another state. In his framing, Generative Engine Optimization (GEO) includes making the business’s identity and expertise easier to recognize and reference.
The fourth question examines what AI answers actually tell prospective customers. Brian describes testing real buying questions across major engines, recording the responses, and comparing them with current business information and competing answers. His examples include discontinued services, old prices presented as current, and competitors named for queries where a business already ranks well. These checks add context that a ranking report alone does not provide.
The episode closes with how Brian turns findings into a ninety-day order of work. He describes prioritizing impact and effort, often starting with access, then structure, then measurement. The goal is an evidenced action plan a team can use without rebuilding everything. He also points listeners toward the MAXPlaces AI Readiness Audit and its free visibility check as ways to begin examining how their business is represented.
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Brian Winum is a partner at MAXPlaces and MAXBURST with more than 20 years in digital marketing. On MAXVolume, he examines AI search, SEO, and what changes in online discovery mean for businesses.
About Brian Winum →Full transcript
1,508 words · Full transcript from supplied captions · Brian WinumTranscript provided from the episode subtitles. Select a timestamp to play from that point.
When healthy reports miss an AI answer problem
A marketing director I know got a text from her CEO on a Sunday. One line: "Why did the plumber we're interviewing say ChatGPT told him we don't do commercial work anymore?" They do commercial work. It's thirty percent of the business.
She checked everything Monday morning. Rankings — fine. Traffic — fine. The website said "commercial services" right there on the homepage. Every dashboard she had was green. And an AI was still, confidently, telling potential customers she'd exited a line of business she was actively trying to grow.
That's the thing that keeps marketing directors up at night now. Not that a number went down. That there's an entire layer of how customers see them that doesn't show up in a single report they own. Today I want to take you inside the thing we built to find it.
What an AI Readiness Audit asks
I'm Brian Winum, this is MAXVolume, and I want to walk you through what we call an AI Readiness Audit — conceptually, like you're sitting across the desk from me.
Here's the first thing to understand. This is not an SEO audit with a new coat of paint. An SEO audit asks "why aren't we ranking." This asks a completely different question: when an AI engine reads your business — ChatGPT, Gemini, Perplexity, Copilot, Google's AI answers — what can it actually reach, what does it understand, and what does it go on to tell people about you?
How the MAXPlaces readiness score works
We score that across eight categories and roll it into one number out of a hundred. Under forty, we call it Emerging. Forty to sixty-nine is Developing. Seventy to eighty-four, Competitive. Eighty-five and up, Leading.
And every point of drag maps to a specific, numbered finding with a fix attached — because a score you can't act on is just anxiety with a decimal point.
Let me group those eight categories into the four questions I'm really asking when I run one.
Question one: can AI crawlers reach your site?
The first question is the most basic, and it's the one that fails most often. Can the AI crawlers physically reach your site? And you would not believe how many can't.
Back in 2024, when everybody got nervous about AI "stealing" their content, a template went around the internet — a little snippet you drop in a file called robots.txt that tells the AI crawlers to go away. Thousands of businesses pasted it in. It felt responsible.
Here's what it actually did. It didn't protect anything — your pages are still public to anyone with a browser. What it did was slam the door on the exact engines your customers now ask for recommendations.
I have opened audits where the single highest-impact finding was one line of text, added years ago by a well-meaning developer, that quietly erased the company from ChatGPT entirely. Not ranked low. Absent. Invisible before the race even started.
That's category one, and I check it first every single time, because every other improvement you make is capped until the door is open.
Question two: can the information be understood?
Say the crawler gets in. Second question — can it actually make sense of what it finds? This is a cluster of categories: how your pages are built, how fast they load for a machine, and how your information is structured.
The big one here is something called schema — the machine-readable labels that tell an AI "this is a service, this is a review, this is who provides it." And what I find, over and over, is schema that exists but sits in disconnected islands. Every page declares a few facts, but nothing points to anything else. The AI reads a hundred and forty little unrelated fragments instead of one connected picture of a business.
Your reviews float free of the company they're reviewing. Your services float free of the company that provides them. The machine is holding a thousand puzzle pieces with no box lid — and when it can't assemble a confident picture, it does the rational thing. It reaches for a competitor it can understand.
That's also where Answer Engine Optimization lives — structuring your content so that when someone asks the question your business exists to answer, the machine can lift your answer cleanly instead of giving up halfway through a wall of marketing copy.
Question three: does AI recognize your business?
Third question, and this is the one that genuinely rattles people. Does the AI know who you are — as a specific, distinct entity in the world? We call this entity clarity, and it's usually the lowest score on the card.
Here's a pattern I see constantly: a company refers to itself three different ways. The legal name, the brand name, the nickname everybody uses. No single canonical declaration of "this is us." No presence in the structured knowledge sources these engines lean on. And so the AI does something terrifying in its ordinariness — it guesses.
I have watched an engine confidently resolve a client to a similarly-named company in a different state. Their reviews, their reputation, their years of work — credited to a stranger, because the machine couldn't tell them apart.
This is Generative Engine Optimization at its core: making your business an entity these systems recognize, trust, and name. Not a link they might list. A source they rely on.
Question four: what are AI answers telling customers?
And the fourth question is the one from that Sunday text message. Forget rankings — what are these engines actually telling people when your name comes up? So we ask them. We run the real buying questions your customers ask, across all the major engines, and we write down what comes back.
And this is where the stomach drops. The discontinued service they're still recommending. The pricing from a blog post three years old being quoted as current. And the one that stings the most — the competitor getting named as the answer on a question you outrank them for in regular Google. You won the old game and you're losing the new one, on the same query, at the same moment.
We score what the AI says about you, and we score how you're doing against the competitors winning those answers — because once you can see why they're winning, it's almost always something structural and fixable, not something magic they have and you don't.
The visibility gap in familiar reports
So pull back and look at all four together, because here's the real answer to the title of this episode. What keeps marketing directors up at night isn't any single one of these findings. It's that none of them show up in the reports they're used to living in.
Your analytics will not tell you a crawler is blocked. Google Search Console will not tell you an AI is quoting a dead price. Your rank tracker will cheerfully show you at number one on the exact query where a machine is handing the customer to your competitor.
It is invisible failure. You are losing deals before you're even in the running, and every dashboard you own is telling you everything's fine. That's the gap. And you cannot close a gap you can't see.
Prioritizing fixes across the next ninety days
Now here's why I actually love running these, and it's not the part you'd expect. The news is almost always better than the client fears walking in. Because when you lay all eight categories out and rank every finding by impact and effort, a pattern shows up nearly every time: the highest-impact fixes are also the fastest and cheapest.
The blocked crawler is one line of text. The dead service is an afternoon of cleanup. Defining who you are is a configuration, not a construction project.
I almost never finish an audit and tell someone they need to tear it all down and start over. I tell them the opposite — you've got a strong foundation, and three specific things are quietly strangling it, and here's the ninety-day order to fix them in.
Access first. Then structure. Then measurement. Sequenced, because the order is the strategy. Most businesses sitting in that "Developing" band are one focused quarter away from "Competitive." They just needed someone to turn the lights on.
What the audit delivers and where to start
That's the whole idea behind the AI Readiness Audit. Eight categories, one honest score, every finding evidenced and paired with the exact fix — a document your team can run with whether you ever hire us or not.
If that Sunday-text feeling landed a little too close to home — if you're not actually sure what the machines are saying about your business right now — that's precisely the thing we look at. You can find the audit over at MAXPlaces, and there's a free visibility check if you just want to see the first crack of light before you commit to anything.
The businesses that win the next few years aren't going to be the ones with the best rankings. They're going to be the ones who bothered to find out what the machine says when a customer asks. I'd rather you find out from me than from a text message on a Sunday.
I'm Brian Winum. Thanks for turning it up. I'll see you next time.




