Your Guide to Answer Engine Optimization
On the go? Here is your rapid-fire reference for getting content right for answer engines. These eight steps distill the essentials of creating content AI search systems can trust and quote.
- Lead with the answer in sentence one
- Prove it next: stats, examples, and expert quotes
- Cover variants: address different ways people ask the same question.
- Link out to credible sources and cite
- Keep pages fresh with a visible “last updated”
- Use the right schema: Article, FAQPage, HowTo, Product, Org, Person
- Make it scannable: logical H1-H3 hierarchy, bullets, tables, and summary boxes
- Measure mentions in AI citations wins and AI referrals, not just blue links
The New Game: Generative Search
With so many new approaches and acronyms (AEO, GEO, GSO, and AIO) floating around, it can be confusing to keep up with all these shifting changes. Mostly Serious is here to help you cut through the noise and evolve your content strategy to be compatible with LLMs. In short:
For small and medium businesses, this is good news: high-quality, well-structured content can now outperform sheer domain size. AI-powered search engines draw from a much wider range of sources than traditional search, creating far more variation in results—up to 91 percent in some cases.
Unlike legacy search, which tends to favor large, established brands and remains relatively consistent, AI search opens the door for smaller players to be discovered when their content delivers real value.
AI Search Glossary (Because Acronyms)
At this time, there isn’t much agreement on what the acronyms for AI search are. You might see any of the following terms below, but they all refer to the process of achieving brand visibility in AI tools by designing pages that generative search engines can easily quote:
- AEO: Answer Engine Optimization
- GEO: Generative Engine optimization
- GSO: Generative Search Optimization
- AIO: AI Optimization
- AI Overviews: AI-generated answers that appear in traditional SERPs.
Here are a few other words to help keep things straight as we delve into the wild world of web content optimization:
- Keyword: A word or phrase used in a search engine query.
- Entity: A uniquely identifiable thing (brand, person, concept)search engines map to queries.
- Schema/structured data: code that helps search engines understand what content is on a page.
- Pillar page: High‑level guide linking to cluster content.
- Variant: Alternate phrasing of the same user intent.
Why Being the Source Beats Ranking #1
Search used to be a race to place in the top ten links. Now it’s a contest of quotability and continuity where the challenge is to get your content retrieved, rather than a numerical position. This poses an important question…
How is content retrieved in AI search engines?
Generative engines synthesize answers, and then selectively cite sources they trust. If your content is clear, verifiable, and structured, you’re more likely to earn a mention and the possibility of a click, whether or not you rank first in traditional SERPs.
Does content originality matter for AI search?
This modifies and narrows prior advice on creating quality content. Is bringing something new to the conversation important? Absolutely. However, it is now more important to frame these insights within the context of other sources, lest AI write your one-off assessment as potential hallucination fodder (Note: please don’t substitute pizza sauce with glue no matter what the robots tell you.). Rollouts of new models have reduced these incidents, at least in part, by looking for consensus across sources.
Do keywords still matter for AI search?
These changes also bring fresh heat to the keyword v. entity debate. While targeting low competition high volume keywords lost some weight across iterations of Google’s Helpful Content Update, current research suggests a return to exact match words as AI systems currently parse content to mirror searchers’ specific phrases. This tendency is a contributing factor for why framing information as questions and answers currently proves successful in AI search and overviews.
While AI search engines continue advancing toward entity-based indexing— where meaning and relationships matter more than exact keywords— the most effective tactic right now is to keep things simple. Frame your headings in natural, question-based language that reflects how people actually search. This helps AI systems quickly match your content to searcher intent.
Auditing Content for AI Search: How to Get Started
It can be difficult to decide where to apply content changes to prepare for AI search. Use this section as a litmus test for deciding what to prioritize first. While informational content often performs better in AI search, do not neglect core pages that are more likely to convert or serve as critical final stages in the user journey once prospects are aware of your brand and ready to move forward. Use these guidelines to understand which pages to optimize for AI search first.
- If service/product pages are thin: Fix those first. Add definitions, pricing/tiers, FAQs, and proof (case bullets, outcomes, quotes).
- If service/product pages are solid: Expand informational content—how-tos, pillar guides, comparisons—to capture broader queries and build topical authority.
Once you’ve sorted where your website lands in content maturity, you can move on to implementing updates. We recommend that you map your gaps to match customer problems. Then, create a mini brief for each issue containing a one-sentence answer, at least 2 or 3 arguments supported by evidence, 5 common questions around the topic, and a schema that corresponds to your content. Once you have your outline, you can move on to fleshing out your writing.
Writing for AI Systems (Without Sounding Robotic)
Before diving into the tactics, remember that writing for AI search doesn’t mean stripping away personality or human connection. These next points outline a proven approach to ensure your content is both machine-friendly and engaging for real people.
Content Patterns that work for AI Search:
- Use relevant web schema markup for SEO to make your content structure explicit to search engines and AI crawlers.
- Answer immediately with clear language that captures each page’s core takeaway.
- Support with internal evidence such as data, quotes from subject matter experts, and concrete examples.
- Address question variants: by using subheads like “How…,” “What…,” “Why…,” this structure captures long-tail keyword phrases that are likely to appear in voice or AI search engines.
- Link to authoritative external references and cite your sources in-text.
- Add a “Last updated” line to informational content and maintain it. Try to update each page at least once per year.
This isn’t so different from traditional SEO, but it does provide more focus for content decisions. As always, your best guide is to create content that’s genuinely helpful to the user and offers a clean, clear navigational experience on the page.
Structure That Gets Quoted Reusable, Quotable Content Blocks
You can take these content patterns even further by going beyond words to add features that make it easier for AI crawlers to understand the content on the page. Luckily, these enhancements help human readers too! Here are some effective options:
- Definition box: one-sentence definition or recommendation
- Comparison tables: features, limits, pricing, fit
- How-to steps: numbered, outcome-focused, each step with a success check
- FAQ sections: 5–8 direct Q&As written in short paragraph answers paired with FAQPage schema
- Clear heading hierarchy: H1 (one per page) → H2 → H3
- Scannable formatting: bullets, lists, short paragraphs
- Summaries: key takeaways at the top; checklist at the bottom
- Data visualization: tables, simple charts
- Internal link hubs: connect related pages
Technical Non-Negotiables
For traditional SEO, schema, a type of structured data, is a “nice to have” but isn’t a direct ranking factor. It often is used in an effort to more readily appear in SERP features like Job Postings, Featured Snippets, and People Also Ask. You can still appear in these features and LLMs without structured data, but adding this code provides that extra clarity that AI systems love to eat up.
Ultimately, we recommend applying as many schema types as are relevant to your specific webpages, but the following types tend to help with mentions in informational content while establishing trust and expertise.
Schema: FAQPage, Article, HowTo, Product, Organization, Person.
If you aren’t savvy with building out schema structures, not to worry. Numerous free schema builders exist online that allow a plug-and-play method of generating code. You can use dentsu to select and fill in context for your schema types then head over to Schema.org’s validator to confirm that your structured data is ready to be dropped into your header code to quickly create structured data like the examples below.
Example Schema Types for LLM Mentions
Important Metadata for AI Search:
At least a few traditional technical SEO elements fall into the “more things change, the more they stay the same” bucket. Be sure to continue including the following metadata and markup hygiene:
- Custom title/meta description
- Descriptive alt text
- Proper heading hierarchy
- Author name and publication/last-updated dates
- Language/location attributes
How to Prove Authority & Originality to AI Crawlers
You don’t need a research department to create content that earns trust—you just need a repeatable process that capitalizes on the expertise you already have at your disposal. AI engines reward clear, verifiable information with identifiable sources, and you can deliver that without deep pockets or a team of analysts.
Here’s how:
- SME interviews: Schedule short, focused 20-minute calls with your subject matter experts. Ask questions like “What’s the shortest correct answer to this?” and “What do people usually misunderstand?” This produces authoritative, quotable insights that no competitor can replicate word-for-word.
- Primary sources: Dig into your own operational data for fresh, original proof points. Use ticket logs to spot recurring issues, CRM exports to track buyer trends, customer polls to reveal preferences, or internal metrics that demonstrate performance.
- Attribution: Always credit the human source behind the information. Include their name, role, and—when possible—a headshot. Date the interview or dataset so readers (and AI systems) know the information is current.
- Editorial standard: Treat sourcing as non-negotiable. Every major claim, statistic, or assertion should be backed by a cited reference—either from your own data or a trusted external source.
By combining consistent processes with a culture of attribution, you position your business as a credible, original voice worth citing. In short: answer first. Prove second. Keep it fresh, but document your claims.
Measurement Beyond Blue Links
Generative engines surface, synthesize, and selectively cite content—so the true wins happen when your brand becomes a trusted source worth quoting. To track progress, you need to expand your analytics lens beyond traditional metrics such as keyword position or click-through rate.
The following signals give a clearer picture of your AI visibility and influence. They help you understand not just if people are finding your content, but how AI systems are representing and driving traffic to your site—and whether that traffic is actually engaging and converting.
What Metrics to Watch for AI Engine Optimization:
We’re still in the early stages of tracking metrics for KPI in AI search mentions, but you can use a combination of existing Google tools, manual checks in SERPs, and generative engines, as well as automated GEO software that illuminates how your brand is featured in results.
- Calculating the percentage of AI referral traffic in GA4
- Manually tracking brand mentions in AI Overviews and Search Engines
- Engagement quality in GA4 to better understand pages receiving mentions
- Search Console query data to identify topics, questions, and queries sparking user interest
- Heatmap validation for insight into points of user interest or confusion
Which Automated Tools Track GEO Success in LLMs
SEO software is still catching up to categorizing AI results. A few good options have recently entered the market that provide a little more granularity into your content’s success in AI search. Semrush’s AI Toolkit will identify how your brand is being featured in AI results, spotting gaps with competitors and providing a hit list of content ideas you can use to shore up gaps.
Ahrefs’ Brand Radar gets a little more into the numbers, identifying how your brand has been featured in AI results and providing examples of which pages appear, as well as how you’ve been featured in AI responses.
As SEO increasingly shifts to a brave new AI model, tracking metrics is sure to become more sophisticated (and hopefully a little less expensive!) with time.
What Patterns to Avoid for AI Search
While the following elements might seem harmless or even helpful in some contexts, they work against you in AI search. They reduce clarity for algorithms, make it harder for AI systems to extract accurate answers, and can diminish user trust—all of which lower your chances of being cited.
Generative engines favor content that is concise, verifiable, and easy to parse. These pitfalls make it harder for AI to trust, quote, or even surface your page.
- Keyword stuffing → write naturally
- Walls of text → use bullets, tables, FAQs
- Organization-centric copy → lead with user needs
- Outdated stats → keep data current
- Missing bylines/last-updated → add them
- No citations → link to authoritative sources
In a nutshell: structure ruthlessly, write for humans, stay factual, and signal authority to grab the attention of LLMs
AI Search Optimization Implementation Checklist
These elements ensure each page you publish is not only optimized for traditional SEO, but also structured, credible, and easy for generative engines to quote. Run through this list before hitting publish to maximize both human usability and AI visibility.
FAQ: Answer Engine Optimization & Generative Search Strategy
1. What is Answer Engine Optimization (AEO)?
AEO is the practice of structuring content so generative AI search engines can easily quote it with confidence. It’s less about ranking first and more about being cited as the trusted source.
2. How do I optimize my content to appear in AI Overviews?
Lead with a clear answer in sentence one, back it up with stats or expert quotes, and format content with headings, bullets, and schema markup. AI systems prefer concise, evidence-backed structures they can lift directly.
3. Do keywords still matter for AI search?
Yes—AI currently favors exact-match phrasing because it mirrors how users ask questions. Use clear, question-style headings (“What is…,” “How do…”) to align with how people query.
4. How is AI-driven search different from traditional SEO rankings?
Instead of listing top links, generative engines synthesize answers and selectively cite sources. That means quotability and clarity now matter as much as authority and backlinks.
5. How can small or mid-sized businesses compete in AI search results?
Generative engines surface a wider variety of sources—91% more than traditional SERPs. High-quality, well-structured content from smaller domains has a real shot at being cited.
6. What kind of content performs best in AI search?
Informational content with definitions, how-tos, comparison tables, and FAQs tends to perform well. But don’t neglect product or service pages—enrich them with proof points, pricing, and FAQs to stay competitive.
7. How do I prove originality and authority to AI crawlers?
Use SME interviews, internal data, and clear attribution with names, roles, and dates. Fresh, human-sourced insights make your content trustworthy and harder to replicate.
8. What metrics should I track to measure AEO success?
Look beyond rankings—track AI referral traffic, brand mentions in AI Overviews, GA4 engagement quality, and competitor gap reports from tools like Semrush or Ahrefs.
9. What mistakes should I avoid when writing for AI search?
Avoid walls of text, keyword stuffing, outdated stats, or missing citations. These weaken clarity and make AI engines less likely to quote your content.
10. How often should I update my content for AI visibility?
Add a visible “last updated” date and refresh content at least annually. Current, verifiable content signals credibility to both AI systems and human readers.
11. Will AI-focused search strategies hurt classic SEO?
Not at all. AI-optimization complements traditional SEO by demanding clearer structure and credible sourcing—elements that boost both AI visibility and organic rankings. Traditional SEO remains essential.
12. Is web schema really necessary to rank in AI search and overviews?
Yes. While schema isn’t a direct ranking lever, it makes your content machine-readable and AI-friendly—boosting chances for being picked up in AI-generated summaries.