Do backlinks matter for AEO (answer engine optimization)?

Roughly 58% of consumers now use AI answer engines in their product research each week — and that number is rising fast. As AI-powered answer engines like ChatGPT, Perplexity, and Google AI Overviews become primary discovery surfaces, content and SEO teams are asking the right question: is there a relationship between backlinks and AEO, or is it time to rethink the entire authority playbook?

The short answer is that contextually relevant backlinks carry more value than high-volume, low-relevance links for AEO. But they no longer tell the whole story.

This post breaks down exactly how backlinks and AEO interact, where the differences between AEO and SEO show up in practice, and what a balanced authority strategy looks like right now.

Before diving in, keep in mind that tools like HubSpot AEO are built specifically to help marketing teams track and improve their brand’s visibility across AEO — more on that as we go.

Table of Contents

Traditional search engines use backlinks as a primary authority signal. A link from a trusted domain to your page is, at its core, a vote of confidence — one that gets weighted by the linking domain’s own authority, the relevance of the context, and the anchor text used. Answer engines don’t abandon the traditional logic of off-page SEO. But they layer a great deal more on top of it.

When an AI answer engine like ChatGPT or Google’s AI Overviews assembles a response, it isn’t simply ranking pages by backlink count. It is identifying sources that can reliably ground the answer. Those sources are:

• Current content
• Content that is clearly structured
• Content consistently associated with the right entities and topics

What this means for content and SEO teams is that a high-authority backlink profile is a necessary but no longer sufficient condition for AI visibility. That’s exactly the gap HubSpot AEO was built to close. The tool gives marketing teams a single place to monitor how often their brand appears in AI answers — and what content is driving (or missing from) that visibility.

Nathaniel Miller, Head of Marketing at Ashbrook Technologies, said in a recorded interview for the Found in AI podcast: “The companies ranking highest across AI platforms tend to be the ones with both strong authority and strong backlink profiles.” He added that “if you’re not getting qualified traffic from that link, it’s basically a logo slap. The real value is in relevance and authority — not just size.”

In traditional SEO, strong domain authority and link volume influence rankings. But in AEO, relevance and semantic alignment between the linking source and your brand’s topic cluster matter much more. Here’s how different link types map to their influence in AEO versus classic SEO:

Alongside backlinks, mentions and co-citations are equally important. A brand mention — even one without a hyperlink — tells an AI system that a source is referencing your brand in a given topical context. When that happens repeatedly across credible sources, it builds the kind of authority that influences the likelihood of citation in AI-generated answers.

While brands with a strong backlink profile tend to be cited often, that doesn’t mean the AI-generated answer will link to the brand. As Charlie Graham, founder of RivalSee, shared on the Found in AI podcast, roughly 85% of brands mentioned in ChatGPT responses have no citation link at all. Users see the name, remember it, and search for it afterward.

That downstream effect is a real authority signal. It just does not show up in traditional analytics.

Pro tip: HubSpot AEO can help you identify which of your pages are earning citations and which link types are actually moving the needle in AI-generated answers.

Need help keeping up with all the acronyms and definitions? Check out the SEO Glossary.

This means when an AI answer engine like ChatGPT, Perplexity, or Google AI Overviews puts together a response, it doesn’t necessarily lean on Google’s traditional ranking factors. Instead, it attempts to ground its answer in trustworthy source material from content or brands that reliably represent accurate information on the topic at hand. Here’s how it works.

1. Source Parsing

AI systems read and index content from across the web, training on or retrieving from large corpora that include news sites, blogs, publications, and structured data sources. What gets parsed is determined not just by backlinks, but by crawlability, recency, and the semantic structure of the page itself.

2. Authority Weighting

Authority weighting works differently from PageRank. An answer engine is not counting links to determine a score. It is assessing whether a piece of content — or a brand — appears consistently and credibly in contexts relevant to the query.

A brand that is cited in 10 authoritative industry publications, mentioned in expert roundups, and consistently associated with a specific topic area will carry more AI authority than one with a strong backlink profile built primarily through directories and generic outreach.

3. Signal Merging

Answer engines do not evaluate links, mentions, and page structure in isolation. They merge these signals into an overall assessment of source reliability for a given topic.

A page can have strong backlinks and still not be cited if its content is ambiguous, outdated, or poorly structured. Conversely, a page with modest link authority but exceptional clarity — clear headings, direct answers, supporting data, consistent entity signals — can earn citation ahead of technically stronger competitors.

Backlinks build trust, but structure and freshness determine whether a page actually gets cited. HubSpot AEO maps these merged signals so marketing teams can see where they’re strong and where gaps are costing them citations.

An entity in AI search is a clearly defined, consistently described thing — a brand, a person, or a concept. As Lars Lofgren, SEO consultant for enterprise brands including Automattic and Perplexity, said on the Found in AI podcast, what matters isn’t just a brand’s domain but the business’s primary entity — and AI engines are essentially mapping the relationships among everything they can crawl.

Answer engines are far more likely to cite brands with strong entity clarity, meaning these brands have:

• Consistent naming conventions across all channels
• Structured data (Organization, Person, and sameAs schema)
• A clear, recognizable area of expertise

If an AI system cannot confidently determine who a brand is, what they stand for, and verify that information across channels, it won’t risk citing them. Entity confusion is a silent AEO killer. HubSpot AEO helps marketing teams catch these gaps early. It shows which pages are earning citations and surfacing prioritized recommendations for where to create, update, or strengthen content.

4. Interplay With Backlinks

A strong entity with a high mention share but no backlink profile will be harder to verify. A strong backlink profile without entity clarity or mention frequency will still underperform in AI citation environments.

The brands earning the most AI citations tend to have all four signals firing at the same time: authoritative links, consistent mentions, strong co-citation associations, and a clearly defined entity. Let’s not forget quality content, too. As Miller put it: “If your content isn’t great, no number of backlinks will help.”

When an answer engine crawls your content, a dense internal linking structure around a topic cluster signals topical depth — the “A” in the FSA framework (Freshness, Structure, Authority).

3. Add schema and consistent terminology.

Schema markup clarifies page purpose and content structure. It is machine-readable metadata that clarifies the purpose and structure of a page to search and AI systems alike. For AEO, the most valuable schema types include:

• FAQPage — marks up question-and-answer blocks for easy extraction
• HowTo — structures procedural content in a format AI systems can follow and cite
• Article — signals content type, author, and publication date
• Organization / Person — establishes entity identity and links to authoritative profiles (sameAs)

Consistent terminology matters as much as schema. If a brand alternates between calling a concept by three different names across its site, AI systems will have a harder time building a clear entity association.

Pick the canonical term for each concept and use it consistently across all pages, social profiles, and external mentions.

Pro tip: Once your schema is in place, HubSpot AEO helps you monitor whether your pages are earning citations in AI answers. This gives teams a signal that content is being recognized and surfaced by AI engines.

Link building and mention building are not separate programs. The most effective AEO strategies treat them as a single integrated effort, where every outreach action is designed to produce both a structural link signal and a brand mention that AI systems can index. Here’s what to do.

1. Prioritize formats AI engines love.

Certain content formats earn disproportionately more AI citations than others. These include:

• Original research and data reports — AI systems gravitate toward primary sources with verifiable statistics
• Expert roundups and attributed quotes — position brand voice in a credible company
• FAQ and How-To content — directly matches the question-answer structure AI systems are designed to extract
• Comparison and versus content — captures decision-stage queries where AI-driven discovery is especially common

Pro tip: When publishing original research, include a standalone “Key Findings” section at the top with three to five clearly labeled statistics. This format is highly extractable and dramatically increases the likelihood of citation.

2. Earn relevant links and co-citations with original research.

Original research is the single most efficient way to earn both backlinks and co-citations simultaneously. A well-designed study or data report gives other publishers a reason to link to a brand as a primary source, and the publications that cover it will often mention the brand alongside other respected voices in the category. This creates the co-citation signals that strengthen AEO authority.

Beyond research, digital PR — earned media placements, expert commentary in industry publications, and podcast appearances — is an excellent backlink strategy that provides both link authority and authentic mentions.

As Miller put it: “Digital PR is the fastest way to start building momentum.” A single well-placed expert quote in an industry publication can generate a backlink, a brand mention, and a co-citation with other recognized experts in a single placement.

Best for: Brands in competitive categories where link volume alone hasn’t moved AEO visibility — original research and digital PR create differentiated authority signals that generic content cannot.

3. Participate where answers form.

AI systems don’t only index brand-owned content. They pull from the places where authoritative conversations happen, such as:

• LinkedIn
• Reddit
• Quora
• Niche forums
• Media outlets with structured metadata
• Wikipedia
• Crunchbase

Participating in these channels — contributing expert commentary, publishing thought leadership, appearing as a guest on podcasts — expands a brand’s footprint across the sources AI systems are trained to trust.

Once a brand has established credibility in the space and built relationships with the people behind the usernames, others are more likely to ask for its input to support their own work — generating another mention on a third-party site.

“It’s a lot of relationship building,” Miller said. “Once you get in with a company or you get a LinkedIn connection, they’re a lot more likely to reach out and say, ‘Hey, I’m working on this article, would love your insight.’”

Pro tip: Qwoted and HARO are particularly valuable here. Use HubSpot AEO’s citation analysis to monitor whether third-party placements are showing up as sources in AI answers and which external domains are contributing most to your brand’s visibility.

A useful lens for structuring this is Loop Marketing, HubSpot’s framework built on the principle that every content and outreach action should feed data back into the next iteration. The same logic applies to AEO measurement, which breaks into three stages: benchmark, tie changes to activity, and report what to scale.

1. Benchmark AI visibility and citations.

Before optimizing for AEO, establish a baseline. This means:

• Testing a brand in AI engines directly — prompt ChatGPT, Perplexity, and Google AI Overviews with the questions a brand’s buyers are most likely to ask and document whether and how the brand appears
• Tracking branded search volume in Google Search Console — rising branded impressions without proportional backlink growth is a proxy signal for AI-driven mention activity
• Monitoring citation frequency with dedicated tools — platforms designed for AI visibility tracking can measure how often and in what contexts a brand appears in AI-generated answers

Pro tip: HubSpot AEO is built specifically to help marketing teams benchmark and track AI visibility alongside traditional search performance. Rather than maintaining separate dashboards for SEO and AEO metrics, marketing teams can monitor citation frequency, grounding query coverage, and page-level citation activity in one place — making it far easier to identify what’s working and where gaps exist.

2. Tie changes to content and outreach activity.

Measurement for AEO requires tracking AI visibility, cited pages, and changes tied to content and outreach work. Measurement only becomes useful when changes in visibility can be tied to specific content or outreach actions. This requires disciplined activity logging of when a brand:

• Publishes a new piece
• Updates an existing page
• Earns a major placement,
• Adds schema.

Make a note of the date and the nature of the change. Over time, patterns will emerge, like:

• Certain content types drive citation pickup faster than others
• Certain publication placements produce measurable spikes in branded search
• Entity clarity improvements lift citation frequency across multiple pages simultaneously

3. Report what to scale and what to stop.

The final step in the loop is translation, particularly turning measurement into prioritization decisions. The questions to answer on a monthly cadence are:

• Which pages are being cited most frequently, and what do they have in common?
• Which outreach placements produced measurable visibility changes?
• Where are there content gaps — topics where competitors are being cited and the brand isn’t?
• What should be sunset, refreshed, or doubled down on?

This cadence transforms AEO from a one-time project into a compounding strategy. Each measurement cycle produces cleaner inputs for the next.