What is AI search optimization? (& why marketers should care)
Resources and ideas to put modern marketers ahead of the curve Insights and strategies for managing contacts, pipelines, and customer relationships at scale Guidance on automations that personalize campaigns, nurture leads, and drive growth Tactics to align marketing and sales, close deals faster, and support modern selling teams Ideas and best practices for delivering seamless support and memorable customer experiences Tips for building high-performing websites and content that attract, convert, and educate Resources for measuring performance, reporting results, and turning data into action Practical perspectives on using AI to streamline work and scale smarter marketing efforts Strategies for selling online, managing payments, and optimizing the digital buying experience Original research, data-backed insights and industry analyses All of HubSpot's marketing, sales, and customer service software on one agentic platform. Marketing Hub Marketing automation software Free and premium plans Service Hub Customer service software Free and premium plans Content Hub Content marketing software Free and premium plans Revenue Hub CPQ, billing, and payments software Free and premium plans Agent Hub Your central home for building and managing AI agents across the platform Learn more AEO (Beta) Answer engine optimization tools that track and improve your brand's visibility in AI results Learn more Home Marketing What is AI search optimization? (& why marketers should care) What is AI search optimization? (& why marketers should care) Written by: HubSpot Staff HUBSPOT AEO TOOL See exactly where your brand shows up in answer engines and take action to close AI visibility gaps. AI search optimization is the practice of improving brands’ odds of being cited and mentioned by answer engines like ChatGPT, Gemini, and AI Overviews. The traffic it earns is small but high-intent. Across more than 1,200 publisher and news sites, visitors referred by AI tools signed up at roughly 11 times the rate of search visitors, according to a Microsoft Clarity study. In this article, I’ll walk you through how to define, evaluate, and implement AI search optimization. I’ll even clearly outline how it differs from, but does not replace, SEO. AI search optimization is the practice of making a brand and its content more likely to be mentioned and cited by answer engines like ChatGPT, Perplexity, AI Overviews, and Gemini. AI search optimization is known by many names, including generative engine optimization (GEO), AI SEO, and LLM optimization (LLMO), but at HubSpot, we call it answer engine optimization (AEO). AEO builds upon SEO and does not replace it; they remain distinct but complementary practices, which I’ll detail in a section below. To be clear, AI search traffic is still small compared to traditional search. However, it has an outsized impact on conversions. AI traffic grew 66.02% in 2025 (faster than every channel except paid search), while accounting for only 0.14% of visits, according to Semrush. The latest data I could find shows that AI search is still less than 1% of the total share, according to Ahrefs May 2026 data. But again, that doesn’t tell the whole story when AI answers are influencing purchases without buyers clicking links. People are increasingly using AI answer engines to get recommendations. AI search optimization puts you in control of the narrative that answer engines put out. See exactly where your brand shows up in answer engines and take action to close AI visibility gaps. AI search is powered by large language models (LLMs), a type of artificial intelligence that can read, understand, and respond in natural language. They are trained on massive amounts of data and can respond to prompts in seemingly novel, human-like ways. When it comes to AI search optimization, there are three ways an answer engine can surface your content, and each works differently: An answer engine can pull from properties you own or from third-party platforms where your brand shows up. Content types it may cite include: Getting cited isn’t the only way to show up. A brand can surface in an AI answer in a few different forms. A linked reference attached to a specific claim inside the answer, usually a small chip or number right after the sentence it supports. It tells the reader exactly which statement came from your page, and clicking it sends them straight to that source. Your brand is named directly in the answer text with no hyperlink attached. An engine can recommend you this way without sending a click, which is why these mentions are worth tracking even though they don’t show up as referral traffic. An AI-generated table that lines up several tools or brands across shared criteria like best use case, strengths, and drawbacks. Being included as a row puts you in the engine’s consideration set for that query, and the cells become the engine’s summary of how you stack up against competitors, accurate or not. A rail or panel listing every page the engine pulled from to build its answer, shown alongside or below the response. A page can land here even when it isn’t tied to any single sentence, so a brand can appear in the source list without earning an inline citation. Product results with details like images and pricing, surfaced for shopping queries. ChatGPT, for example, shows products through its merchant program. There’s been much debate about whether AEO is actually a thing, or whether it’s just traditional SEO masquerading as something new and exciting. AEO is definitely distinct from SEO. And here’s where they differ: For deeper reading, check out our article on how SEO has evolved over the years.
Source: HubSpot
This article has been carefully curated and reformatted for educational and informational purposes. Full credit goes to the original publisher.
📚 Visit more helpful articles on Joab Peters Blog
No comments