Conductor has published a 31-page Enterprise AEO Handbook, and it is worth reading even if you will never buy an enterprise platform. It is also a vendor document: every section closes with a panel headed “How to do this with Conductor”, and the five stage maturity model and four pillar structure in it are Conductor’s own frameworks rather than industry standards.
That does not make it wrong. Most of the tactical advice is sound and transfers to a company with four people in marketing and no platform budget. What does not transfer is the operating model around it. This post separates the two, because a smaller team reading a document written for a company with a C-suite sponsor and a BI stack can easily conclude the whole discipline is out of reach, which is not the case.
What transfers, and you should copy
The content advice is the strongest part of the document, and almost none of it needs software.
- Write for chunkability. The handbook’s framing is that a reader or a model should be able to drop into the middle of your article, read one section, and leave with a complete answer. That means real topic sentences, paragraphs that stand on their own and headings that honestly preview what sits under them. This is the single most useful editing instruction in the document.
- Put FAQ sections where they genuinely fit, paired with FAQ schema, on pricing pages, product pages and buying guides. Five to ten real questions, not a padded list. Not every page needs one.
- Think in entities and topics rather than keywords. A connected cluster covering a subject properly signals depth; two pages chasing two phrasings of the same thing does not.
- Treat titles and meta descriptions as content. They are often the first thing a model reads about a page, and they are doing double duty for traditional search at the same time.
- Audit for formats models cannot read. Information baked into an image rather than coded as text, content that only appears after a click in an accordion or tab, anything rendered only in JavaScript, and video without a transcript. We have written about the same failure patterns in SEO and GEO for B2B SaaS companies.
- Keep the good pages fresh on a cadence, and update the published date only when you have actually updated the content.
None of that requires a licence. It requires an editor with a checklist.
The best idea in it is the one most marketing teams will resist
The handbook states the gated content problem plainly: if a piece needs to drive pipeline through gated downloads, it will not drive AI visibility, and if it needs to drive AI visibility, it has to be crawlable. You cannot have both from the same file.
Its recommended compromise is to gate the full asset but publish an HTML version carrying the unique data points and key insights, so that the substance is crawlable and the download still exists for lead capture.
What makes this worth pointing out is that the handbook follows its own advice. The public handbook page is a substantial HTML summary that any model can read, and the 31 page PDF sits behind a form. The crawlable page is the part that will get cited. The PDF is the part that captures the email address. Both jobs get done, by two different artefacts.
That is the practical answer for anyone sitting on a gated report, a webinar recording or a case study PDF. Publish the findings as a page. Keep the form on the file. Most teams do the opposite and then wonder why their best research never appears in an AI answer.
A vendor telling you not to trust a metric
Conductor’s measurement section argues that prompt volume and conversation volume are not reliable metrics, because AI search is personalised enough that you cannot meaningfully tally how often a given prompt is asked. It recommends citations, brand mentions, share of voice, sentiment, persona and intent coverage, AI bot crawl activity, and traditional search performance alongside them.
A platform company arguing against a number that platform companies sell is worth noticing. If a tool quotes you monthly search volume for prompts, ask how it was derived before you report it to anyone.
One finding worth knowing about AI crawlers
The handbook reports research on Conductor’s own content in which ChatGPT crawled a newly published page eight times more often than Google in five days, and Perplexity crawled it three times more often. That is a single case, measured by the company publishing it, so treat it as an indication rather than a benchmark.
The implication still holds and is useful. New or freshly updated content can start influencing AI answers quickly, and there is no equivalent of the “request re-indexing” button for AI bots. If a page goes live broken, slow or missing its schema, you do not get to ask for a second look. Publishing correct the first time matters more than it used to. If you are still deciding which of these crawlers to admit in the first place, we covered that in the GPTBot decision guide.
What does not transfer without the budget
Four things in the document describe a company most readers do not work at.
The maturity stages. The later stages assume executive sponsorship, brand, PR, product, web development and analytics teams all engaged, a platform integrated with the CMS, CRM and BI tools, and finally AI agents running routine work under human governance. For a team of four, those stages do not describe a destination so much as a different company. The useful part of the model is only the first instruction: be honest about where you actually are rather than where you would like to be.
Always-on monitoring. The need is real. A broken schema tag or a key page returning a 404 does quietly cost visibility. The enterprise answer is 24/7 monitoring with real-time alerting and intelligent prioritisation. The smaller answer is an uptime monitor, a structured data validation run after every deployment, and a human opening your ten most important pages once a week. That covers most of the risk for almost none of the cost.
Agentic AEO. The handbook’s own pro tip is the honest one: build your own agents only if you have the engineering resources, the expertise and the time to maintain them as things change. For most teams in 2026 this is a thing to watch rather than a thing to buy.
A unified data engine. For the first six months, a spreadsheet holding your question set and what each assistant said is enough. The reason to graduate from it is volume, not capability.
What we would actually do first
This sequence is Brilad’s framing rather than anything from the handbook, and it is ordered so that the cheapest work that produces evidence comes first.
- Write the question set. Fifteen to twenty questions a real buyer would ask, in their words, not yours. Run them against ChatGPT, Google AI Overviews, Gemini, Perplexity and Copilot. Record whether you are named, what is cited, and whether the description of you is accurate.
- Fix what cannot be read. Take your twenty most important pages and find the content locked in images, tabs, accordions and JavaScript. Move it into plain HTML.
- Add schema to content that already exists. Organization sitewide, Article on posts, FAQPage wherever you already have questions and answers, Product where relevant. This is markup work on content you have already paid to produce.
- Free your best gated asset. Publish its substance as a page and keep the form on the file.
- Correct your third-party profiles. Review platforms, directories and listing sites, with the business details matching your own site exactly.
- Re-run the question set after 30 days, unchanged, and compare.
Five of those six cost time rather than money, and the one that costs money is schema implementation, which is a one-off.
The honest summary
The handbook’s closing argument is that the fundamentals of AEO are strong content, technical soundness, real authority and accurate measurement, and that these are not going anywhere. That is correct, and it is also the part of the document that has nothing to do with buying anything.
Read it for the content and technical chapters, which are good. Read the maturity model as a description of enterprise reality rather than a ladder you are obliged to climb. And take the gated content point seriously, because it is the one recommendation in the whole document that costs nothing, that most teams will refuse on principle, and that would change what an assistant can say about you within weeks.
If you want the longer argument about why having something of your own to say matters more than formatting it correctly, that is in AI search needs more than optimised content.
Source: Conductor, The Enterprise AEO Handbook. Figures and frameworks described above are Conductor’s, and the research cited on crawler frequency is the company’s own. This post is an independent commentary and Brilad has no commercial relationship with Conductor.