AIM AI Search Practice · DFW Market Study
The State of AI Visibility in DFW
We assessed a dozen Dallas–Fort Worth businesses in depth and scanned hundreds more for one thing: whether AI assistants can find, understand, trust, and recommend them. Most can’t — yet. Here’s what we found, and why it’s the most fixable advantage in your market right now.
The core finding
Your customers already trust you.
AI doesn’t know that yet.
Across every business we evaluated, one pattern repeated: real-world trust that AI systems simply cannot see. Decades in business, hundreds of reviews, BBB accreditation, local press — paired with a nearly empty machine-readable identity.
The reviews exist, but there’s no rating markup. The business is 50 years old, but there’s no structured “founded” date or local-business schema. It has five social profiles, but nothing in the code connecting them. To a human, the business is obviously trustworthy. To an AI assistant reading the page, it’s an unverified stranger — so it doesn’t get named, cited, or recommended.
“Readable, but neither understandable, trustworthy, nor citable” — the one-line diagnosis that fit almost every site we scored.
How we measure it
A deterministic score, not a gut read.
Every business is scored against the same rubric on eight weighted categories — the same inputs always produce the same score, so the number is defensible and repeatable. We run it two ways:
The full AI Visibility Assessment scores all eight categories, including off-site signals like how often AI engines actually cite you and how you stack up against competitors. It’s the fee-based, client-facing deliverable.
The Teaser scores the six on-site categories in seconds — the quick snapshot we use to open a conversation. Both run the same core rubric, so the story they tell is the same.
The pattern everyone shares
The foundations are fine.
The identity layer is empty.
Stack the category scores and the same shape appears business after business. The sites load fast and read cleanly — AI crawlers can reach the pages. But the moment an engine tries to decide who this business is and whether to trust it, the signals run out.
The site is readable
Technical AI Readiness and AI Readability typically score 80–90. Crawlers reach the pages, the content parses, nothing blocks the door. This is table stakes — and most businesses clear it.
The site isn’t citable
Trust & E-E-A-T, Entity Recognition, and Structured Data are the lowest categories almost every time — frequently under 40. This is exactly the layer AI reads to decide whom to recommend.
Two findings worth sitting up for
Invisible to AI — not by choice
In one prospect batch, a dozen sites returned zero crawlable pages because they hard-block bots — including the four major AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended). A customer’s AI assistant hits the exact same wall. These businesses aren’t scoring low; they’re not in the conversation at all.
Entity confusion is quietly costing wins
One franchise location presented three different cities across its brand name, its schema address, and its page title. The result: it appeared on the “best of” list for one city but was absent from the list for the city in its own name — so an AI asked to recommend the best there never named it. Ambiguity an AI can’t resolve becomes a recommendation it won’t make.
The good news
Almost all of it is fixable — and fast.
The recurring defects behind these scores aren’t redesigns. They’re administrative — the kind of work that can move a score meaningfully in weeks, not quarters.
- No
LocalBusiness/Organizationschema, or only a stub - No
sameAslinks tying the business to its verified profiles - No
aggregateRatingmarkup, despite strong real reviews - NAP inconsistencies between the site and Google, Yelp & BBB
llms.txtmissing or corrupted — in one case pointing at a dead domain- Multiple
<h1>tags per page from page-builder artifacts - Missing meta descriptions across large shares of pages
- AI crawlers blocked at robots.txt or the firewall
How AIM closes the gap
Measure. Remediate. Track.
The same rigor that produced this study is the process we run for every client — a measurable before, defensible work in the middle, and proof it moved.
Measure
We score your site against the full eight-category rubric — a reproducible baseline that shows exactly where AI can and can’t see you, and why.
Remediate
We build the identity layer: connected schema, sameAs
and rating markup, clean NAP, llms.txt, and the E-E-A-T signals that make an AI confident enough
to recommend you by name.
Track
We monitor whether ChatGPT, Gemini, Perplexity and Google’s AI actually cite you — and grow your share of those answers month over month.
Questions we hear
AI visibility, answered.
What is “AI visibility”?
How is the score measured — and is it reliable?
Why isn’t my business showing up in AI answers?
How long does it take to fix?
What’s the difference between the free teaser and the full assessment?
Is this only for Dallas–Fort Worth businesses?
See where you stand
Find out what AI sees when it looks for you.
Get a free teaser score in seconds — or book a working session and we’ll walk your full assessment together. Either way, you’ll know exactly where the gap is and what it takes to close it.
Advanced Integrated Marketing, Inc. · Arlington, TX · (817) 592-5586
About this study: findings are drawn from AIM’s own AI Visibility Assessments and Teasers run across Dallas–Fort Worth businesses (clients and prospects). Individual businesses are referred to by industry only. Full-assessment and teaser scores use different category sets and are reported separately. AI-answer appearance rates reflect our testing on a defined set of buyer-intent prompts.
