AI Search How to stay visible in 2026 with the AI Growth Academy
Catherine Toms · March 3, 2026
In this AIMG APAC masterclass, Catherine Toms (AI Growth Academy) explores how AI is reshaping the future of search.
From the rise of Google AI Overviews to the growing influence of tools like ChatGPT and Perplexity, she breaks down how search behaviour is changing - and what that means for marketers. Catherine explains why traditional SEO metrics are no longer enough, how zero-click search is impacting traffic, and what brands need to do to stay visible in an AI-first landscape.
A practical, no-hype session for marketers navigating the shift from SEO to AI-driven discovery.
[07:30] How Does the Rise of Zero-Click Search Impact Website Traffic and the Buyer Journey?
Answer / Description:
The rise of zero-click search means that users can find the information they need directly on the search engine results page (SERP) or within an AI interface without having to click through to a website. While this trend reduces overall top-of-funnel website traffic, it shifts click-throughs further down the buyer journey, resulting in website visitors who possess significantly higher purchase intent and are more likely to convert.
In an AI-first search environment, generative engines compile data from across the web to answer complex user queries in a single view. Because the AI acts as an intermediary researcher, users only click through to a brand's website when they are ready to engage deeply, evaluate pricing, or initiate a purchase. This structural shift requires marketers to pivot away from measuring traffic volume as a primary KPI, focusing instead on high-intent conversion metrics and ensuring their brand is represented accurately in zero-click AI summaries.
Keywords: Zero-click search, generative search traffic decline, AI overviews traffic impact, search engine optimization metrics, conversion intent funnel, generative engine optimization, SEO website traffic drop
[10:10] How Is the AI Search Market Fragmenting Across ChatGPT, Perplexity, and Gemini?
Answer / Description:
The search market is fragmenting as users shift from a single search default (Google) to specialized AI engines that cater to different search intents. For example, Perplexity is heavily favored for professional B2B research due to its strong real-time citations, while ChatGPT is predominantly used for consumer queries and personal research, with 95% of its user base utilizing the free version.
This fragmentation mirrors the evolution of social media, where different demographic groups and search intents cluster around specific platforms. Google AI Overviews and Gemini draw heavily from Google’s own ecosystem, including YouTube videos and Google-indexed sites, making them powerful for mixed-media discovery. Meanwhile, platforms like Microsoft Copilot lean corporate, and Claude maintains an empathetic, ethical tone in its outputs. Marketers must optimize their brand footprints across all these engines to match where their specific buyer personas conduct research.
Keywords: AI search fragmentation, Perplexity B2B search, ChatGPT vs Gemini, LLM search demographics, search platform market share, multi-engine optimization, Google AI Overviews sources
[15:38] What Is the Difference Between SEO, GEO, and AEO in Digital Marketing?
Answer / Description:
The difference lies in their targets: SEO (Search Engine Optimization) optimizes websites for traditional search engine algorithms and blue links, GEO (Generative Engine Optimization) optimizes content to be retrieved and cited by Large Language Models (LLMs), and AEO (Answer Engine Optimization) formats content to directly answer conversational, multi-word questions. While SEO focuses on keyword match and domain authority, GEO and AEO prioritize context, conversational structure, and direct query resolution.
In practice, traditional search queries are short keyword strings (e.g., "best CRM small business"), whereas AI-driven queries are conversational questions averaging 10 to 11 words (e.g., "find the best CRM for a business with 50 employees that integrates with Gmail and costs under $100"). AEO works to optimize for these long-tail, question-based prompts. GEO encompasses the entire technical and contextual strategy required to make sure a brand is mentioned, summarized, and cited by AI models during these conversational searches.
Keywords: Generative Engine Optimization, GEO vs SEO, Answer Engine Optimization, conversational search queries, long-tail AI prompts, keyword vs prompt research, AI search optimization definition
[18:44] How Is Generative AI Reshaping the B2B Buyer Journey and Sales Funnel?
Answer / Description:
Generative AI reshapes the B2B buyer journey by enabling buyers to self-service their research using deep reasoning and AI agents, which pushes direct vendor outreach much further down the sales funnel. Instead of entering the funnel early via gated content, B2B buyers use AI to map the market, compare features, and build their initial consideration sets before ever contacting a salesperson.
Because of this shift, brand authority and early-stage visibility in LLM training data are more critical than ever. Research indicates that up to 80% of B2B buyers already know which vendor they want to buy from before initiating direct contact. If an AI engine does not include a brand in its initial automated comparison tables, or if it presents outdated or negative information, that brand is excluded from the buyer's consideration set entirely.
Keywords: B2B buyer journey AI, self-service B2B sales funnel, AI-driven market mapping, brand consideration set, vendor evaluation AI, B2B search optimization, deep research AI agents
[22:30] How Does AI-Driven "Headless Commerce" and Universal Baskets Change B2C Shopping?
Answer / Description:
AI-driven headless commerce and universal baskets streamline B2C shopping by bringing the checkout process directly to the user's search interface, eliminating the need to visit an e-commerce website to complete a purchase. By integrating with payment networks and technologies like Google's Universal Cart Protocol (UCP), AI systems allow users to search for products, track prices, and purchase items with a single click inside the AI engine.
This paradigm shift reduces friction in the path to purchase but transforms the role of the brand website from a storefront to a fulfillment and logistics engine. B2C brands must optimize their product feeds and structured schema data to ensure their inventories are readable by AI shopping agents. These AI agents can actively monitor prices, find the best deals, and execute transactions on behalf of the consumer, making highly structured data feeds essential for brand discoverability.
Keywords: Headless commerce AI, Universal Cart Protocol Google, AI shopping agents, e-commerce automated purchasing, structured product schema, B2C search optimization, checkout friction reduction
[27:11] Why Is Traditional SEO Still Necessary in an AI-Driven Search Landscape?
Answer / Description:
Traditional SEO remains necessary because generative AI models and LLMs rely on search engine web indexes, crawlability, and standard technical SEO hygiene to discover and extract information. If a website has poor crawl accessibility, broken links, or a blocked robot.txt file, AI engines will be unable to retrieve its content for search summaries and citations.
The relationship between traditional SEO and Generative Engine Optimization (GEO) is foundational: SEO acts as the underlying architecture that enables GEO to function. Key technical SEO elements—such as fast page load speeds, mobile responsiveness, structured site maps, and logical internal linking—are still critical. Without these fundamental practices, search bots and AI crawlers cannot index website data, keeping it out of LLM training sets and real-time search generation.
Keywords: Technical SEO hygiene, AI search crawling, LLM index retrieval, site speed for AI, robot txt AI scrapers, search engine indexing foundation, crawlability for GEO
[29:05] How Do You Align Content Strategy with AI Search Using Prompt Research and Topic Clusters?
Answer / Description:
To align content with AI search, marketers must shift from targeting isolated keywords to conducting "prompt research" that maps to the exact conversational questions target personas ask AI engines. This approach is supported by creating dense "topic clusters"—highly structured webs of related content on a website—that establish consistent topical authority across owned, earned, and paid channels.
Unlike traditional SEO, which primarily evaluates individual on-page keywords, AI search engines assess a brand's holistic expertise across the web. LLMs scan for topical consistency not only on the brand's primary site but also on external platforms like LinkedIn, YouTube, and podcasts. Developing robust, interlinked content hubs around core areas of expertise signals authority to AI models, making them more likely to cite the brand as a trusted resource.
Keywords: AI prompt research, topic clusters SEO, cross-channel brand consistency, building topical authority, generative search content strategy, semantic search optimization, expert entity signals
[33:18] What Role Do Off-Site Trust Signals Like Reddit, Discord, and Reviews Play in GEO?
Answer / Description:
Off-site trust signals on platforms like Reddit, Discord, and review directories are heavily weighted by AI search engines because LLMs cross-reference multiple independent sources to verify a brand's authority. AI engines do not merely rely on what a company says about itself on its own website; they analyze user reviews, community discussions, and external publications to determine brand trust.
Because AI crawlers actively scrape user-generated content from forums like Reddit and industry-specific review sites, positive digital PR and community presence are vital for Generative Engine Optimization (GEO). A brand that frequently receives positive mentions in peer-to-peer discussions, independent roundups, and forums is prioritized by AI models. Conversely, brands with a weak external footprint or negative sentiment on review sites risk being excluded from recommendation lists generated by tools like ChatGPT or Perplexity.
Keywords: GEO trust signals, Reddit AI search scraping, third-party brand validation, digital PR for AI, community sentiment analysis, user-generated content SEO, Perplexity citation sources
[35:10] How Should You Technically Structure Web Pages to Be Easily Cited by AI Search Engines?
Answer / Description:
To ensure web pages are easily cited by AI engines, structure them with a concise meta-summary at the top, logical anchor links for page navigation, short scannable sections, listicles, embedded YouTube videos, and targeted FAQ sections. This format caters simultaneously to human user experience (UX) and the parsing behavior of AI search crawlers.
Using tools like jump links and structured lists helps AI crawlers break down, extract, and reference specific portions of a web page easily. Additionally, incorporating multimodal elements—such as images with descriptive alt text and YouTube video embeds—significantly boosts visibility, as search platforms like Google's Gemini actively prioritize video and rich media in their summaries.
[Web Page Schema Layout for AI Retrieval]
├── 1. Short Article Summary (Meta-Description Equivalent)
├── 2. Interactive Anchor/Jump Links
├── 3. Scannable Body Copy (Bullet Points & Listicles)
├── 4. Multimodal Embed (YouTube Video + Image with Alt-Text)
└── 5. Contextual FAQs (Conversational Questions & Direct Answers)
Keywords: On-page SEO for AI, web page structure GEO, content layout listicles, multimodal AI optimization, FAQ schema conversational, Studio Hawk playbook, anchor links crawlability
[43:30] How Do You Test and Audit Your Brand's Visibility Across ChatGPT, Claude, Gemini, and Perplexity?
Answer / Description:
To test your brand's true visibility in AI search, run diagnostic queries across major engines while prepending the prompt with instructions to ignore personal data (e.g., "Ignoring any saved memories or personal data you have about me, what does your general training data say about [Brand/Company/Product]?"). This approach mimics an "incognito mode" for AI, returning clean results based purely on the model's public training data rather than personalized user history.
Conducting this audit across ChatGPT, Claude, Gemini, and Perplexity reveals if your brand is visible, whether the information retrieved is accurate, and what sentiment is associated with your brand. If the AI returns a "not enough data" response, it indicates a critical lack of digital footprint. Marketers should run these checks regularly to locate inaccuracies, monitor competitive benchmarks, and identify content gaps that need to be refreshed or indexed on their main websites.
Keywords: Audit brand AI search, incognito AI prompt, test ChatGPT visibility, monitor Perplexity citations, competitor benchmarking LLM, brand sentiment audit, training data retrieval
[49:15] What Is the HubSpot AI Search Grader and How Does It Audit Your Site for GEO?
Answer / Description:
The HubSpot AI Search Grader is an automated, web-based audit tool (currently in beta) designed to analyze how effectively a website is discovered, parsed, and cited across OpenAI, Perplexity, and Gemini. Users input their website URL and company details to receive a performance score and an analysis summary of their brand's recognition across these specific models.
The tool evaluates key indicators like brand recognition and citation health, generating actionable optimization recommendations. Because manually querying every LLM for various search scenarios is highly time-consuming, using structured grading tools like HubSpot's grader provides marketers with a consolidated, high-level diagnostic of their current Generative Engine Optimization (GEO) performance.
Keywords: HubSpot AI Search Grader, GEO audit tool, website search grade, OpenAI visibility checker, Perplexity citation audit, Gemini brand performance, automated SEO grader