For more than two decades, digital discovery has operated on a simple model: search, scan, click, decide.
This worked when there were people searching the web; but with the emergence of artificial intelligence agents, the main consumer of information is no longer always human.
This gives rise to a new paradigm: Response engine optimization (AEO), also called generative engine optimization (GEO). Because agents view data very differently than humans, success is no longer determined by rankings and clicks, but by whether content is understood, selected, and referenced by AI systems.
The SEO model the web was built on is no longer going to cut it, and businesses need to prepare now.
How LLMs interpret web content
Traditional SEO is built around keywords, rankings, page-level optimization, and click-through rates. Users manually search multiple sources and click to get what they need. Simple but sometimes frustrating and time consuming.
But AEO operates on a completely different level. Agents are increasingly taking over user workflows: Claude Code, OpenClaw, CrewAI, Microsoft Copilot, AutoGen, LangChain, Agent Bricks, Agentforce, Google Vertex, Perplexity’s web interface, and more.
These agents do not “browse” the web like humans. They analyze user intent based on persistent memory and context from past sessions (rather than simple autocomplete) rather than just expressions. They require short, structured and to-the-point materials.
Moreover, agents go beyond looking after the delegation, they deal with lower tasks. What starts as “search, read, decide” evolves into “agent buys, agent summarizes, human decides” (and further “agent actions → human approves”).
“In practice, AEO starts where SEO stops,” said Dustin Engel, founder of the consulting firm Elegant disruption. “AEO is the next layer of discovery” or “zero-click discovery.”
In this new world where agents synthesize responses, users may never see a business’s website, click-through rates decrease, and attribution and relevance (instead of pure visibility or appearing at the top of a list of blue links) can become critical.
“The new standard is closer to a citation map: where the model is drawn from, how often you appear and how you are described,” Engel said.
Some, like Adam Yang from the Q&A platform QuoraArgues that AEO has already defaulted over SEO.
Yang notes that this is for “a certain class of requests.” Any question the user wants a synthetic answer to — "What is the best approach to X," "compare these two options" "What should I know about Y?" – solved by AI without a single click as you go.
Many analysts note that Google’s own AI Insights is already accelerating this on the consumer side. “SEO is not dead,” Yang said. “However, the optimization goal has changed from ‘rank on page 1’ to ‘get cited in an answer’.”
How practitioners are already using AI agents
Are there scenarios where constant search/Google is still the best option?
“Absolutely,” analyst Wyatt Mayham said Northwest AI Consulting. Especially for personal tasks like finding nearby restaurants or local service providers. The interface is “better” in these cases because it combines maps, reviews and photos. “That experience is hard to beat right now,” he said.
For job research, he says he “barely” uses traditional search and “gets close to zero” every month.
“When I need to understand a company or person professionally, agents do it faster and give me a more useful result than a page of blue links,” he said.
His firm uses autonomous agents “heavily” and built a Claude Skills function that powers the sales operation. Before a discovery call with a prospect, team members can run a skill that pulls up a contact’s LinkedIn profile, scrapes the company website, pulls relevant data from sources like ZoomInfo, and creates a clear picture of their revenue, team size, tech stack, and pain points.
“I have a custom research brief that’s ready to go without spending 30 to 45 minutes by hand until I call,” Mayham said.
He noted that the big advantage is that these tools work in the background. You don’t have to sit around clicking browser tabs: You just tell the agent what you need, it does it, and you get a structured result that’s actually useful.
“What used to be a full hour of sales preparation collapsed into minutes,” Mayham said.
Carlos Dutra, data science manager at a fintech company With confidencesaid Claude Code “really changed” his daily workflow. He uses it for most of his coding work, and what surprised him wasn’t the speed, but the fact that he didn’t have to open browser tabs and keep track. “Not because I’m lazy, but because the answers are better,” he said. He still uses Google for some tasks: Rating pages, breaking news, anything that needs to be current. “But for technical reasoning? Agents basically replaced the search for me in person,” he said. Quora’s Yang had a similar experience. He’s been using Claude Code daily for the past few months, mostly for content strategy, knowledge management, and competitive research. A workflow that used to take him half a day now takes 30 minutes. But the best thing is that he can now perform the research and synthesis tasks in parallel that he should have done sequentially. Also useful is that agents retain context across sessions “significantly better” than web-based tools. When you need to understand a concept, map the competitive landscape, or synthesize industry trends, Claude or Confusion is the go-to choice before opening a browser tab. “I started looking at agent search as my first stop, not Google. Traditional search is now where I validate, not where I discover.” Although the folds are real. Mayham noted that LinkedIn in particular has been “aggressive” in blocking automated logins, and that many other sites have (or are implementing) similar protections. Users will hit walls if agents can’t get through, so a backup plan is important for those who rely on agents. “Reliability isn’t 100% yet, and that’s probably the biggest thing holding back wider adoption,” he said. Mayham’s advice to other developers: Stop chasing shiny objects. A new AI tool is launched “practically every day” and many (including experienced developers) jump from platform to platform without ever delving into any of them. “Pick a model, dig in, build a real workflow on it,” he said. “You’ll get more value out of mastering one platform than surface-level experience across five.”
How businesses can compete in an AEO-driven world
The rules change when AI agents search. The question is no longer whether your content is on the first page, but whether the model selects you as a source when generating an answer.
Structure matters more than ever. The content should:
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Organize around conversational intent, provide direct answers, and reflect real user questions and follow-ups;
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Be authoritative and reflect a strong track record;
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Be fresh (and regularly refreshed as needed);
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Have clear headings and an established FAQ layout.
Another important point is to maintain a strong brand presence in forums and platforms where models are trained – Wikipedia, Reddit, LinkedIn, industry publications. Businesses may also consider investing in original data, such as research.
In Mayham’s experience, when a business is recommended by LLM during a search-style query, the conversion rate is “dramatically higher” than traditional channels. For his company, traffic referred to LLM converts between 30-40%, which “destroys what we see from SEO or paid social.”
“When someone is talking to an AI and it recommends you by name, the intent signal is just different.”
Mayham said that discoverability within LLMs will be as important as Google rankings, “maybe more so.” “It’s a whole new surface for customer acquisition that most businesses haven’t even considered yet.”
Trustly’s Dutra agreed that the “uncomfortable truth” is that most corporate content is “largely invisible” in agent-driven queries. “AEO is about whether your content survives fragmentation, embedding, and semantic retrieval,” he said.
Companies that thrive don’t do anything ‘exotic’,” he noted. They have clean, declarative content that doesn’t require context to understand. Those who still write keyword-stuffed copy will be left behind, because LLMs care about semantic clarity.
A quick test for clients: Ask LLM the question your page should answer without specifying a URL. “If it can’t generate a response from your content, you have a problem.”
Jeff Oxford of SEO Agency Vision Labs offers valuable step-by-step advice:
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Engage in conversations on Reddit, one of the most referenced domains in AI search. Businesses should build a positive reputation on Reddit and engage in any relevant topics that customers ask for recommendations.
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Create a strong YouTube presence. According to Internet behavior tracker Ahrefs, YouTube has the “strongest correlation” with AI visibility among ChatGPT, AI mode, and AI Views. Oxford said: “This makes sense because both Google and OpenAI train their models on YouTube transcripts, and YouTube is the most referenced domain in Google’s AI products.”
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Invest in digital PR and brand awareness; the latter is the second highest factor associated with AI vision. “Brands need to improve their digital presence by being in as many places as possible,” Oxford said.
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Create tailored content with AI citation examples. Businesses should examine the leads and topics that AI search engines encounter with competitors, then create authoritative content on those topics.
“The goal is to become a resource that AI models find worth referencing,” he said.
Still, there can be a lot of unnecessary hype about how drastically businesses need to change. said Shashi Bellamkonda, principal research director at the consulting firm Info-Tech Research Group. Those who follow the best practices of producing content that their audience really needs, written by experts and demonstrating expert opinion, are in a good position to be cited in AI-powered search. He noted that Google has developed the EEAT (Experience, Experience, Authority and Trust) framework to evaluate the quality and usefulness of content and help algorithms identify reliable, high-quality information. To differentiate, businesses must use structured information and schema to communicate context: Is this an article, research study, product review? “Original long-form content will be evaluated by AI-powered response engines,” Bellamkonda said. “Trying to copy strategies or game the system is taboo in this era.” Experts should also share their views on several channels and "About us" pages should be “robust” and include bios that highlight the experience of thought leaders.
“Ultimately, the reputation of AI-powered search is making sure that the user likes the search more than you think they should read,” Bellamkonda said. “So having a good focus on the end user is a great way to be successful.”
