AEO, GEO, and What Happens as AEM Enters the Chat

Marketing Prepares for When AI Answer Engines Take On Main Character Energy

The Road From SEO to AEO

The world of technology loves a good hero story. Experts map maturity curves to illustrate how long it took for radio, television, computers, or the internet to gain mainstream adoption, comparing it to the meteoric rise of ChatGPT’s generative artificial intelligence (GenAI) explosion into consumer awareness. Search engine optimization (SEO) versus answer engine optimization (AEO) is getting the same curvy treatment.

SEO began in earnest in 1998 when Google first introduced PageRank as a new framework for search engine results. It would take SEO, as a practice and investment, another five years to hit the mainstream of marketing strategies and budgets. The “Golden Era” of SEO hit its peak when COVID-19 shutdowns sparked a massive shift to online shopping and a hunt for information. Demand for SEO soared to record highs in a race to grab homebound digital attention.

By the end of the global pandemic, the age of authenticity was in full swing. Brands that flourished were those that bid farewell to brochureware websites and instead invested in thoughtful digital content strategies and intentional acts of online engagement. By the time Google doubled down on EEAT (experience, expertise, authoritativeness, and trustworthiness) as the core of its quality rater guidelines (QRGs), a monster industry full of back-linking, crawlability experts, content optimizers, and keyword authorities was in play.

That is, until GenAI and the rise of generative engine optimization (GEO).

Understanding AEO and GEO

In less than a year, the market has welcomed AEO and GEO to the marketing lexicon. The industry has begrudgingly had to admit that something had shifted so much so that organizations have needed to move quickly to stop that sensation of free-falling. SEO campaigns have become harder to optimize under the traditional metrics and measures of value and success. Customer campaigns, across demand and brand, B2B or B2C, need more content to execute while delivering declining results. Demand generation campaigns aren’t driving as much as they used to. Search, as a whole, has shifted as algorithms rebalance and favor new factors and sources.

It’s time to better understand what this new alphabet soup is, what it isn’t, and how leaders are establishing new strategies and new platforms to better spell success.

What Is Generative Engine Optimization?

• GEO is a marketing strategy that works to optimize content that is available to be referenced and cited in AI-generated summaries delivered via AI applications.

Be it OpenAI’s ChatGPT, Google’s Gemini, or the in-search generative answer summaries via Google’s AI Overviews, GEO pushes marketers to optimize the broad content made available by a brand, ensuring that content is available and included in the model-generated synthesis or summary. GEO strategies focus on the broad conversation. The win for brands is how a company’s brand or product appears in that broad dialogue, especially when AI is asked to compare multiple solutions or scenarios. GEO is the big picture.

What Is Answer Engine Optimization?

• AEO is the action and practice of structuring and creating content that can be picked up to answer user prompts and queries.

AEO is where GEO strategy gets to work. The goal is to ensure visibility when AI model-driven search tools such as AI Overviews on Google Chrome or AI apps such as ChatGPT analyze sources to generate answers, snippets, or summaries. All of these chatbots, voice assistants, and AI snippets rely on primary source information. AEO engineers content so that brands appear in these answers. The goal of AEO is to offer concise, structured answers to appear in the generated response, including citations in the all-important links included in deeper “AI mode” insights.

What Is the Difference?

• GEO is strategic. AEO is tactical. Both are required in the age of authority.

Whereas GEO answers the question “Why are we not showing up in that answer” by addressing how content is used as an authoritative source for summaries generated, AEO is the work focused on the structure of the content being cited. GEO looks at the entire chain of establishing trust, authenticity, and authority and puts intention behind the content being created. AEO will pressure teams to write, format, and place content in slightly different (and possibly uncomfortable) ways. GEO demands that teams rethink where content and conversations happen, to amplify authority. AEO demands that teams construct answers in semantic triple.

Does That Mean SEO Is Dead? Do I Just Divert My Spend?

• No, AEO does not replace or kill off SEO. Some in the industry actually still see SEO as the larger master category.

In reality, this alphabet soup is a bit more like a set of nesting dolls that addresses the biggest issue of them all: being in the right place at the right time, with answers for and engagement with a customer. SEO is the foundation, driving visibility, availability, and discoverability—all based on the currency of authenticity. Without that foundation, you can’t build those AEO moments to reach your GEO goals.

Enter Answer Engine Marketing

What Is Answer Engine Marketing (AEM), and Is It Really ‘Real’ Yet?

• In theory, AEM is the integration of advertising inventory in line with or on-screen with generated responses to queries in AI applications. It is, at best, in its earliest stages today.

No, AEM isn’t technically a huge “thing” yet, but based on recent announcements from OpenAI, the emphasis is on the not yet. OpenAI began testing ads in ChatGPT as a pilot in February 2026, focusing on limited, more premium placements that are not disruptive to the user experience and appear after generated results. OpenAI has also struck deals with AdTech platforms, specifically Criteo, to open this premium inventory to ad buyers. For its part, Google has not ruled out ads in Gemini but has also been quick to deny any immediate plans, emphasizing the need for trust in AI’s output.

Then there is the reality of AEM in its early incarnation. The initial trials of ads in ChatGPT have been rocky, to put it kindly. Advertisers have noted poor performance and a lack of measurability—the tools marketers have relied on that track digital ad performance just don’t work for this yet. (And no, that em dash was not generated by AI: This author put it there on purpose!) Cost has also been a factor, with Criteo recommending spending upwards of $100,000 for what already feels like an experiment. Then there was the Super Bowl, where Anthropic took a big swing at models integrating ads in responses, comically demonstrating just how horrible that customer experience could become.

Meet the GEO Players

Aside from understanding these new entrants into the alphabet soup buzzword bingo marathon, there are new questions about how to manage any or all of them. New agencies are popping up daily; many of them recast marketing, advertising, or SEO shops now taking on the new demands of GEO and AEO. Marketing technology vendors familiar with SEO tracking and analytics are adding modules to track and gain visibility into AEO outcomes. There are also some early leaders in platforms that are focusing on the demands of large language models (LLMs), GEO strategies, and AEO tactics.

Adobe: Adobe LLM Optimizer does exactly what the name suggests but takes it a step further with direct actions for content improvements along with deep analytics, visualizations, and dashboards into brand visibility that are focused on making a real impact. The Agentic Traffic dashboard easily visualizes how AI agents are interacting with a brand’s website, and the solution delivers a GEO score that tracks how AI sees a brand. LLM Optimizer makes recommendations for content optimization but can also take optimization to a new level aimed at focusing on AI agent traffic. The Optimize at Edge capability delivers a faster path to making AI-specific updates by delivering optimizations at the content delivery network (CDN) layer, meaning existing publishing workflows stay the same but agentic traffic is met with optimized HTML served only to AI agents without impacting human users or traditional SEO bots.

Conductor: Billed as the enterprise AEO platform, Conductor is looking to connect the dots between AEO and SEO analytics, understandings, and workflows. Initially launched as a marketing services firm in the early 2000s, Conductor has grown into a significant player across multiple fronts of marketing optimization. With its enterprise focus, it understands the intelligence that drives impact and the work required to stay visible and durable.

HubSpot: HubSpot has just announced the availability of HubSpot AEO, now in public beta. The solution identifies how a brand appears in answer engines such as ChatGPT, Gemini, and Perplexity; provides CRM-powered prompt suggestions based on what HubSpot AEO knows about a business and its buyers; identifies content gaps; and shifts to seamless execution of recommendations by publishing social posts or updating content pages. A robust brand visibility dashboard includes sentiment analysis, a competitor share-of-voice tracker, and citation analysis that includes sources. More autonomous features will be available throughout 2026. HubSpot has also developed a framework for marketing in this new age of AI and AEO dubbed Loop Marketing that includes a four-stage process, with stage 3 focused on how to diversify content for both human and AI/bot consumption. Expect to see more from HubSpot specific to GEO strategies and AEO capabilities, thanks in part to their October 2025–announced intent to acquire XFunnel, a standout startup focused on monitoring, analyzing, and optimizing brand visibility across generative AI platforms.

Jasper: An early leader in GenAI applications, specifically for content generation, Jasper has introduced solutions that focus on establishing GEO strategies with insights, knowledge, and a comprehensive understanding of both content intent and engine behaviors. The solution offering includes purpose-built SEO, AEO, and GEO AI agents that are connected to often-cited marketing key performance indicators (KPIs), so marketing teams have an agent that deploys quickly and ties to actual marketing outcomes.

Profound: From how content appears in AI summaries to how prompts and searches are driving engagement, the Profound platform aims to be an end-to-end brand content solution based on visibility to push content to valuable customers. Users point to how many AI engines and models are tracked and understood by Profound, breaking free of the “basics” of OpenAI, Google, and Perplexity and expanding understanding to a reported 10 major engines, including DeepSeek, Meta, and Grok.

Semrush: Arguably one of the leaders in SEO and search engine marketing (SEM), Semrush has introduced a suite of tools to address brand visibility in the Age of AI, along with an impressive portfolio of tools focused on content optimization, generation, and repurposing. The key here is AEO integration with a full swath of paid, earned, and owned optimization plays.

This list is the shortest of the shortest lists and by no means a definitive guide. The market is already seeing how the larger marketing and engagement platforms could start to tackle AEO and content for the AI era. For example, Salesforce has built-in tools in Marketing Cloud that actively recommend optimizations for search and AI. The company also has a significant partnership with Semrush to pull analytics and visibility right into the Salesforce platform. On the content management front, solutions such as Optimizely have already launched AEO functionalities that focus on content structure and offerings from WordPress VIP, the company that already powers 43% of the web, already have capabilities that lean heavily into knowledge-centric, FAQ-forward structures and schemas that LLMs love to search and scrape, so enterprises should experience less heavy content lifting by leaning into best practices there.

The Bottom Line: Welcome to the Age of Authority

The old tactics driving linked connections and establishing authenticity won’t cut it here. Complicating matters more is that in this age of authority, authenticity is needed to prove authority, but in different formats and different destinations. This isn’t just a conversation about web destinations but about how we fundamentally shift thinking. Sure, these models are scraping and crawling publicly available websites, but they can also ingest PDFs in an instant. So how does that shift our thinking for demand generation campaigns that rely on gates, forms, and hidden PDFs to capture leads? Should our press releases be structured differently before they cross the wire? How do we leverage earned and paid media to influence prompts before a single model sets out to crawl for answers? And if FAQ structure drives impact in AEO, should we be having different conversations about content management that bring our friends in enterprise content management and languages such as Darwin Information Typing Architecture (DITA) and sometimes ignored component content management systems (CCMSs) back to the strategy tables?

In discussions about AI’s changing the world, it might be time to admit that the workflows and processes we have held dear across marketing, communications, and advertising are too old to automate for authenticity but are ideally suited to modernize for authority. No matter how many maturity curve slides we share, we will create even more “iceberg” graphics to demonstrate just how much change will be required to shift the thinking of what’s lurking under the water. We need to combine the thoughts to get to the reality: The heat of white-hot hype and the massive scale of the underwater iceberg view mean a shift in the very ecosystem we are trying to change. In the end, the iceberg can and will flip, causing a tsunami as everything hidden rushes into view thanks to AI. How we prepare will matter. Starting with visibility into and understanding of AEO to inform a durable GEO strategy is an important step.