---
title: "We Audited 18 GEO/AEO Companies' Own Sites. Most Skip Their Own Advice."
description: "Original study: we checked the websites of 18 GEO, AEO and AI-search companies for six AI-readiness signals. 82% carry JSON-LD (which barely moves citations), but 0% expose an MCP manifest, only 6% declare a Content-Signal, and fewer than half have the llms.txt they often recommend."
canonical: https://aiovsseo.com/articles/geo-industry-audit-study.html
date: 2026-06-07
---
# We audited 18 GEO/AEO companies' own sites. Most skip their own advice.

Key finding

We checked the websites of **18** GEO, AEO and AI-search companies for six AI-readiness signals. The pattern is stark: **~82% carry JSON-LD** (the cosmetic signal that [barely moves AI citations](/articles/metadata-llms-read.html)), but **0% expose an MCP manifest**, only **6% declare a Content-Signal**, fewer than half (**41%**) serve a real `llms.txt`, and just **24%** return markdown to agents. The industry selling AI visibility mostly optimizes the part that photographs well.

## Method

On June 7, 2026 we requested the homepage of 18 well-known GEO/AEO/AI-search vendors and tools, then probed six signals with simple HTTP requests:

- **Crawlable homepage** — did it return HTTP 200 to a plain crawler?
- **JSON-LD** — is `application/ld+json` present in the homepage HTML?
- **llms.txt** — does `/llms.txt` return 200?
- **Content-Signal** — does `robots.txt` declare `Content-Signal` / `ai-input` / `ai-train`?
- **MCP manifest** — does `/.well-known/mcp.json` return 200?
- **Markdown negotiation** — does the homepage return `text/markdown` when asked with `Accept: text/markdown`?

This is a point-in-time snapshot of a small sample, not a census — treat it as directional. One site (BrightEdge) returned **403** to our crawler, so signal rates below are computed over the 17 that served a homepage.

**A note on rigor:** for `llms.txt` and markdown we didn't trust the HTTP status code alone — many sites return `200` for any path (a soft-404 serving the homepage). We required the response to be real plain-text/markdown, not HTML. That distinction matters: one site (GenOptima) returned `200` on `/llms.txt` but served its HTML homepage, so we counted it as *no real file*. Status-only checks would have over-reported llms.txt adoption.

## Results

| Signal | Adoption (of 17) |
| --- | --- |
| JSON-LD structured data | **82%** (14) |
| llms.txt present (real file) | **41%** (7) |
| Markdown to agents | **24%** (4) |
| Content-Signal in robots.txt | **6%** (1) |
| MCP manifest (/.well-known/mcp.json) | **0%** (0) |
| Crawler hard-blocked (403) | 1 of 18 (BrightEdge) |

Sample: Ahrefs, Semrush, Conductor, Profound, Otterly, Peec, Jasper, Writesonic, Surfer SEO, Clearscope, seoClarity, BrightEdge, First Page Sage, Evertune, LLMrefs, RankScope, GenOptima, Goodie.

## What it means

### 1. The industry over-invests in the signal that doesn't move citations

JSON-LD is the most-adopted signal (82%) — yet controlled testing shows schema has [near-zero effect on AI citations](/articles/metadata-llms-read.html). It's valuable for Google rich results, but its dominance here suggests the field is optimizing for the checkbox that's easy to ship and easy to demonstrate, not the one that earns citations.

### 2. The machine layer is almost entirely unbuilt

Not one site exposed an [MCP manifest](/articles/machine-to-machine-mcp-layer.html), and only one declared a [Content-Signal](/glossary/content-signal.html). These are the forward-looking, machine-actionable signals — and adoption among the very companies selling AI readiness is effectively zero. The future they describe in their blog posts isn't reflected in their own DNS yet.

### 3. Even llms.txt — which many of them recommend — is a coin flip

Under half serve the file the category evangelizes. (For what it's worth, that's defensible: [llms.txt adoption is ~6% web-wide](/glossary/llms-txt.html) and its impact is unproven — but it's striking that the advocates themselves are split.)

### 4. Markdown negotiation is the quiet early mover

About a quarter return clean [markdown](/articles/markdown-for-agents.html) to agents — higher than we expected, partly because Cloudflare can enable it automatically. It may be the first machine-layer signal to cross the chasm.

> The companies selling AI visibility have mostly shipped the cosmetic signal (schema) and skipped the structural ones (Content-Signal, MCP). The gap between what the industry preaches and what it deploys is the story.

## Caveats

Small sample (18), single snapshot, homepage-only probes, and HTTP-level signals can't capture everything (a site may serve markdown or govern crawlers by means our probe missed). We publish the method so it can be reproduced and challenged — which is rather the point of [honest data](/articles/geo-aeo-statistics-2026.html) in this field.

## Frequently asked questions

**Do GEO and AEO companies follow their own AI-optimization advice?**

Mostly only the easy parts. In our June 2026 audit of 18 such company sites, ~82% carried JSON-LD (which barely affects AI citations), but 0% exposed an MCP manifest, 6% declared a Content-Signal, 41% served a real llms.txt, and 24% returned markdown to agents. The field over-invests in the cosmetic signal and skips the machine-layer ones.

**What is the most neglected AI-readiness signal among GEO vendors?**

The machine-actionable layer. None of the 18 sites exposed an MCP manifest at /.well-known/mcp.json, and only one declared a Content-Signal in robots.txt. These forward-looking signals see near-zero adoption among the companies selling AI visibility.