Nobody can seem to agree on what to call this new online search discipline. Some say Answer Engine Optimization (AEO), while others prefer Generative Engine Optimization (GEO). The terms differ, but the goal is the same: ensuring your brand appears inside AI-generated answers to online searches. For simplicity we’ll stick with AEO in this post.

While marketers may disagree on the term, there’s widespread consensus on the importance of an effective AEO strategy. After all, more than 40% of Gen Z now prefer using AI assistants, like ChatGPT, over conventional search engines for discovery.

From a practitioner’s standpoint, SEO and AEO are two sides of the same coin. Both aim to convince the specific resource people turn to for information that your company is relevant to what they’re seeking. The fundamental difference lies in how those resources serve users.

For two decades, marketers optimized for clicks. The question was: How do I drive traffic from search engines to my site? Today, the question has flipped: How do I get my brand mentioned inside large language model (LLM) answers?

In AEO, the goal isn’t referral traffic—brands get precious little of that from LLMs. It’s representation. “Visibility” is the word most marketers use. You want your brand to appear in the response itself (or on the AI Overview summary directly within search results), as part of the information consumers trust. That means caring about:

• Presence: How often your brand appears in answers
• Prominence: How early it appears in an answer
• Citations: The links LLMs include to back up their responses

AEO tools generally fall into three broad categories. The first are AI-native AEO platforms, a new generation of monitoring tools built specifically for this world. They track prompt and answer visibility, citations, sentiment, and share of voice relative to competitors. Because they’re purpose-built and have no prior-era feature debt, they tend to earn high marks for innovation and feature velocity.

The second group are SEO tools with AEO features. Established SEO platforms haven’t been caught off guard—most are layering in AEO tracking modules. While these features may evolve more slowly than those of AI-native startups (and UI’s can get a little busy) many companies prefer keeping SEO and AEO within the same platform. The tradeoff—less innovation for more stability—can be worth it, especially for larger organizations that value continuity.

And finally, agencies are filling the gap that separates insights from action. They’re combining human testing and strategic guidance with homegrown or third-party tools to provide end-to-end support—reporting on LLM visibility, interpreting data, and executing optimization recommendations. As one marketer put it, “The monitoring tools mostly access the same data—it’s what they do with it that matters.” Agencies actually do something with the data.

“There’s no Matt Cutts for AEO,” one CMO at an AI-native monitoring vendor told me, recalling the previous Google web spam head who acted as the liaison between the search giant and a generation of SEO professionals. Nobody truly knows how LLMs decide which sources to include in their answers. But early evidence points to three consistent factors: recency (fresh content is favored), authority (models value credible sources and subject matter experts), and structure (bot-readable formats and consistent entity names help models connect the dots).

These factors have inspired a variety of techniques to improve visibility. Many marketers describe this phase as feeling like the early days of SEO, when brands begged for backlinks from authoritative sites. Still, certain approaches are emerging as best practices, most centered around structured clarity.

On the on-site side, that means:

• Using Q&A formats and prompt-like subheads
• Answering likely follow-up questions on key pages
• Including a TL;DR section summarizing key points
• Writing long-tail content—the hyper-specific topics that were hard to justify in the SEO era
• Ensuring clean markup (schema, canonical tags)
• Offering bot-readable versions (markdown or JSON)
• Keeping content dates fresh and attributing authorship to subject-matter experts
• Editing press pages to include excerpts mentioning your brand, not just links
• Creating comparison pages
• Prioritizing page load times

As one expert summarized: “Half of this is classic SEO. The other half is new—schema tags, citation management, and off-domain authority.”

Only a small percentage of answer content comes from a brand’s own site. The majority comes from third-party domains, fueling what some see as a resurgence of public relations. Common off-domain tactics include content swaps or paid placements on sites with key citations; expanding PR lists to include citation owners; participating in Reddit discussions and industry communities; publishing a Wikipedia page; and increasing influencer and creator marketing investments for added credibility (and control). One team I’m aware of went so far as to spin up their own online community in part because the concentration of subject matter experts discussing industry topics alongside relevant mentions of the company’s brand is exactly the sort of format that LLMs will value.

Nevertheless, one has to wonder if the rate at which AI learns will accelerate the half-life of today’s AEO practices. A martech entrepreneur friend recently asked, rhetorically, “Why would we need to reformat our webpages for bots? Isn’t AI bound to learn to read human formats anyway?” Marketers spent years collecting backlinks for SEO. How long will content swaps be a necessary tactic in AEO?

Yet for all their similarities, one of the starkest differences between SEO and AEO is measurability. Because few users click citations, most LLM-related traffic shows up as direct. For now, marketing teams will need to rely on correlation—tracking whether improvements in AEO coincide with increases in direct traffic. On the positive side, marketing wisdom says that as volume grows, quality often drops. Yet at least one marketer told me her brand has seen the opposite: a lift in both direct traffic and conversions from that cohort of visitors.

In addition to direct traffic patterns, much of what marketing teams measure aligns to native features in AEO platforms: share of voice in LLM responses, citation frequency, sentiment. If these metrics sound familiar it’s because they map closely to the early days of social-media marketing. Let’s just resist calling them vanity metrics, at least not until a better alternative is available.

Most advanced brands now treat AEO as an extension of SEO, not a replacement. The same fundamentals—technical health, relevance, and content quality—still rule. Just as SEO evolved to include voice search and structured data, AEO is about making your brand understandable and findable by machines that answer instead of link.

Acknowledgment
Huge thanks to everyone who contributed insights to this article—especially Yulia Green Ziv of HiBob*, whose experience and candor helped shape this piece.