Every marketing concept eventually gets wrapped in jargon that makes it sound more complicated than it is. AEO is no exception. This post is a plain-English explanation of what it actually is, why it matters, and what doing it well looks like.

What AEO is

Answer Engine Optimization (AEO) is the practice of getting your business, product, or name mentioned correctly when someone asks an AI product a question. The AI products that matter right now are ChatGPT, Claude, Perplexity, Google’s AI Overviews, and Gemini. A few others are growing.

When someone asks one of these products a question like “what’s the best accounting software for Shopify sellers,” the product generates a written answer. That answer might mention specific products, cite specific sources, and link to specific websites. AEO is the work you do so that your business shows up in those answers when you’d be a legitimate match.

That’s the whole concept. Everything else is detail.

Why it’s different from SEO

SEO is the work you do to rank high in Google’s traditional search results, where the output is a list of blue links. AEO is the work you do to appear in AI-generated answers, where the output is a written response.

The two aren’t opposed. Most of the best SEO practices are also good AEO practices. But some things are different:

SEO is about clicks. You want the user to click your link and come to your site. AEO is partly about clicks (Perplexity and AI Overviews include links) and partly about being mentioned at all, whether or not the user clicks.

SEO ranks pages. AEO doesn’t really “rank” pages. AI products assemble answers from multiple sources, and the question is whether your content gets included in the assembly.

SEO responds to queries. AEO responds to conversational prompts, which are often longer, more specific, and more varied than keyword searches.

SEO cares about keywords. AEO cares about semantic meaning. You don’t need to match keywords exactly; you need to be the right answer to the underlying question.

The overlap is substantial. Most of what makes content good for SEO (clear structure, specific information, authoritative sourcing, technical quality) also makes it good for AEO. But the work you do for AEO goes further in some specific directions.

The four things that matter for AEO

When you strip away the hype, AEO work comes down to four categories.

1. Content that answers specific questions

AI products extract answers from content that directly addresses the question being asked. The content that works is:

The simplest heuristic: could a smart writer summarize this page in two sentences and feel confident the summary is correct? If yes, the page works. If the page is full of fluff and generalities, it doesn’t.

2. Press coverage in publications AI products cite

The highest-impact factor in AEO. When a major publication (Forbes, TechCrunch, Wired, Bloomberg, Reuters) writes about your business, that coverage becomes part of the training data and retrieval systems AI products use to answer questions. AI products cite those publications constantly.

If your category is covered well by a few specific publications, getting mentioned in those publications is often the single most productive AEO investment. It’s also the hardest, because real press coverage requires real newsworthiness and real relationships with reporters.

3. Entity data and knowledge graphs

AI products understand the world through knowledge graphs. A knowledge graph is basically a giant map of entities (people, places, companies, products) and how they relate to each other. If your business isn’t in the knowledge graphs, AI products either can’t talk about you or describe you imprecisely.

The work here:

This is mostly one-time work followed by light maintenance. Done right, it gives AI products a solid foundation for talking about you accurately.

4. Measurement

You can’t improve what you don’t measure. AEO measurement means tracking how your business shows up in AI responses to specific prompts over time.

The basic process: build a list of prompts your customers might ask, run those prompts against the major AI products, and record what the products say. Do this monthly and watch how your visibility, framing, and citation patterns change.

Tools that help: Otterly, Profound, AthenaHQ, or custom trackers built on the APIs. Without measurement, you’re working blind.

What AEO isn’t

A lot of what gets sold as AEO is either SEO with a new name or marketing hype. Some things that aren’t really AEO:

Stuffing pages with keywords AI products might match. AI products don’t work on keyword matching the way old search engines did. Keyword stuffing hurts more than it helps.

Buying backlinks from low-quality sites. Doesn’t work for SEO, doesn’t work for AEO. AI products weight source quality, and low-quality links are noise.

Adding FAQ schema to every page. FAQ schema is useful on pages with genuine Q&A content. Stuffing it onto non-FAQ pages gets penalized and ignored.

Following a “proprietary AEO algorithm” from an agency. There’s no secret formula. The work is content, press, entity data, and measurement. Anyone selling mystery is selling marketing, not results.

Short-term tactics promising fast results. AEO moves slowly because the underlying systems move slowly. Wikipedia updates take time. Press coverage takes time. Knowledge graphs update on their own schedule. Anyone promising fast results is overselling.

How AEO work actually looks in practice

A real AEO program for a small to mid-size business looks like:

Months 1-3: foundation. Audit existing content, create or update entity profiles (Wikipedia, Wikidata, Crunchbase, schema), baseline prompt measurement, identify target publications for press work.

Months 4-6: production and outreach. Publish content targeting specific prompts, begin press outreach with story angles, continue measurement, refine based on early results.

Months 7-12: iteration. Double down on what’s working, cut what’s not, build on early press wins with secondary placements, expand content clusters.

By month 12, a well-run program produces measurable improvements in AI visibility: more prompt mentions, more citations in AI responses, better framing, and more of the right kinds of traffic flowing through AI-driven referrals.

By month 24, the compounding effects are visible: the entity data is solid, the content clusters rank, the press coverage becomes a moat, and the measurement dashboard shows steady improvement across the prompt inventory.

It’s slow work. Most of the value is in the tail of the investment, not the first few months.

Do you actually need to do this?

Not every business needs an aggressive AEO program. A few questions to ask:

Do your customers research purchases before buying? If yes, AI products are increasingly where that research happens, and AEO matters.

Does your category have meaningful competition? If yes, whoever does AEO well will have a lasting advantage. If your category is a monopoly or extremely niche, AEO matters less.

Are you comfortable with a 6-12 month time horizon? AEO work compounds slowly. If you need results in 30 days, AEO isn’t the right investment.

Do you have budget for content, press, and entity work? A real program costs real money. If you can’t commit to at least $2,500-$5,000 per month for a year, start smaller with SEO basics instead.

If the answers are yes, AEO is worth the investment. If they’re no, focus on the fundamentals first and revisit AEO when the business is ready.

The short version

AEO is the work you do so that AI products mention you correctly when people ask relevant questions. It’s a stack of four practices: content that answers questions well, press coverage in publications AI products cite, clean entity data in knowledge graphs, and measurement of prompt-level visibility.

It’s not a trick. It’s not a secret. It’s not a replacement for SEO. It’s marketing work in a new distribution landscape, and it rewards patience, consistency, and quality more than cleverness.

Do the work, measure what matters, ignore the hype. That’s the whole playbook.