AI in SEO

I tested dozens of AI SEO tactics and found 7 that actually work. Implemented on a client site, these strategies drove 2300% more AI traffic… And got them appearing in 90 keywords in AI Overviews (from 0): #1: TARGET CONVERSATIONAL QUERIES Traditional keywords don't trigger AI Overviews like conversational queries do. Traditional: "15-minute home workout" (no AI Overview) Conversational: "What's a quick 15-minute workout I can do at home without equipment?" (triggers AI Overview) Use Google's "People Also Ask" section to find these conversational queries. Add these exact questions as H2s, then answer them directly. #2: STRUCTURE WITH CLEAR HEADINGS AI loves content it can easily scan and understand. Use this exact heading hierarchy: - ONE H1 that states the topic clearly - H2s for major sections/questions - H3s for sub-points within sections #3: BE DIRECT & CONCISE AI will ignore #1 ranking sites in favor of lower-ranking pages with clearer writing. Vague, metaphorical language entertains humans but confuses AI. Direct, factual statements get featured in AI Overviews. #4: ADD SUMMARY SECTIONS FOR EASY EXTRACTION AI loves content that summarizes key points upfront. Add either: - A brief TL;DR summary (2-3 sentences) - A bullet-point "Key Takeaways" section Place them at the beginning of articles. This makes it easy for AI to extract your main points without crawling the entire page. #5: MONITOR YOUR BRAND ACROSS AI PLATFORMS AI often describes your brand differently than you'd expect. Use these exact prompts in ChatGPT, Gemini, and Microsoft Copilot: "What can you tell me about [your brand]?" "What does [your brand] do?" Check if the descriptions are accurate. If you find discrepancies, fix them by: - Updating your About Us and FAQ pages - Claiming and updating Google Business Profile, Yelp, LinkedIn and Trustpilot listings - Making your brand description consistent across all platforms AI pulls from these sources directly to form its opinion of you. #6: DEMONSTRATE AUTHORITY WITH REAL EXPERTISE AI prioritizes content from trusted sources. Add these specific trust signals: - Expert author bios with credentials - Case studies with real data - Industry certifications displayed prominently - Citations from reputable sources #7: COLLECT AND SHOWCASE REVIEWS We did a single-variable test on a law firm site stuck in rankings for months. The ONLY change we made was adding Google Reviews. Result: Immediate ranking improvements in both traditional AND AI search. Display reviews prominently on your site. Then actively engage with all user content: - Respond to comments (even negative ones) - Answer questions on forums - Engage with social mentions AI sees this as proof of legitimacy.

Recently Google dropped Gemini Flash 2.0, its latest AI model, and it’s clear that the search giant isn’t going gently into that good OpenAI-led night. The headliner? Native image generation. If your feed is suddenly flooded with people freaking out over AI-edited images, this is why. Google just launched the first-ever omni-modal image gen in an experimental release. Fast, high-quality, and dangerously close to making stock photo sites obsolete. Gemini 2.0 can generate visuals within seconds, seamlessly embedding text (yes, actual readable text) into images - a feat that’s been historically tough for AI. It’s a direct shot at OpenAI’s DALL·E 3, and early reports suggest it’s faster and more accurate. Want to tweak an image? You don’t need to start over, just tell Gemini to “make the sky more dramatic” or “add a golden retriever by the door,” and it gets it. The difference is night and day (pun intended, refer to image below). But the most interesting part of the Google AI Studio is its deep integration - a strategic move that suggests this is just the beginning of something much bigger. Gemini isn’t just generating content; it’s absorbing context by weaving itself into the very fabric of Google’s ecosystem. Personalized, context-aware AI responses using your search history, Maps data, and soon, Google Photos. Need a restaurant recommendation? Gemini won’t just give you a list - it’ll pull from your past preferences, factor in traffic, and even suggest what time you should leave. This is Google finally playing to its strengths: data, distribution, and dominance. Search gives Google unmatched insight into what users want, and every service - Gmail, Maps, YouTube, Chrome - funnels more context into that engine. The brilliance of Gemini isn’t just that it generates high-quality images or responds with multi-step reasoning; it’s that it does so inside Google’s walled garden. AI integration isn’t a standalone experience; it’s baked into the ecosystem that billions of users already live in. And that’s where Google’s real advantage lies. OpenAI and Midjourney built powerful standalone models, but Google owns the internet’s intent layer. Every search query, every navigation request, every email sent through Gmail is a potential point of entry and input data for AI. If you believe, as I do, that the real future of AI is less about individual chatbots and more about pervasive intelligence, then Google’s approach looks like an inevitability. Which brings us to the bigger question: if Google nails this, does it even matter who has the better model?

AI search is already deciding which early stage tech companies get seen and most are completely invisible inside it (even with solid SEO) I've been testing AI visibility strategies with B2B SaaS startups over the past year. What I've learned: Traditional SEO metrics tell you very little about whether ChatGPT, Perplexity, or Google's AI Overviews will surface your brand. The gap between what founders think works and what actually gets cited is massive. Here's the framework I've found that consistently moves the needle: 𝟭. 𝗕𝘂𝗶𝗹𝗱 𝗔𝘂𝘁𝗵𝗼𝗿𝗶𝘁𝘆 𝗔𝗜 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗥𝗲𝗰𝗼𝗴𝗻𝗶𝘇𝗲 AI evaluates content using E-E-A-T: Experience, Expertise, Authority, and Trust. Of these four, trust matters most. What this looks like in practice: → Include detailed author bios with specific credentials → Share first-hand experience with real outcomes → Support every claim with verifiable sources → Update content regularly (53% of ChatGPT citations come from content updated in the last 6 months) 𝟮. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗳𝗼𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗣𝗮𝗿𝘀𝗶𝗻𝗴 Over 72% of first-page results use schema markup. AI systems need structured data to understand your content. The tactical approach: → Implement JSON-LD schema markup → Use logical heading hierarchies (H1/H2/H3) → Break content into short, scannable paragraphs → Create standalone quotable statements with specific data 𝟯. 𝗠𝗮𝘁𝗰𝗵 𝗡𝗮𝘁𝘂𝗿𝗮𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗤𝘂𝗲𝗿𝗶𝗲𝘀 Searches containing 5+ words grew 1.5× faster than shorter queries in 2023-2024. AI chat interactions last 66% longer than traditional searches because users are asking complete, conversational questions. How to adapt: → Research "People Also Ask" questions in your space → Target long-tail, question-based queries → Structure answers as standalone responses → Use conversational, clear language 𝟰. 𝗨𝘀𝗲 𝗛𝗶𝗴𝗵-𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗙𝗼𝗿𝗺𝗮𝘁𝘀 Content over 3,000 words generates 3× more traffic than shorter pieces. Featured snippets have a 42.9% clickthrough rate, and 40.7% of voice search answers come from them. The formats that work: → Comparison articles with modular sections → Detailed listicles (2,300+ words for voice search) → FAQ sections with direct answers → Data-rich content with clear statistics 𝟱. 𝗧𝗿𝗮𝗰𝗸 𝗪𝗶𝘁𝗵 𝗚𝗘𝗢 𝗧𝗼𝗼𝗹𝘀, 𝗡𝗼𝘁 𝗦𝗘𝗢 𝗧𝗼𝗼𝗹𝘀 Traditional SEO metrics show weak correlation with AI citations. You need specialized Generative Engine Optimization (GEO) tools. What to track: → Brand mentions across AI platforms → Citation rates in ChatGPT, Perplexity, AI Overviews → Share of voice for key queries → Sentiment in AI-generated responses This isn't about abandoning SEO. It's about expanding your visibility strategy to include the platforms where your buyers are already searching. Repost this ♻️ if you found it helpful! P.S. If you're a technical founder trying to get visible in AI search, start with this 5-st

Google’s AI Overviews are reshaping where visibility comes from. Most AIOs sit on top of informational searches: “how to,” “what is,” “why does.” These queries now trigger AI answers far more often than they show traditional organic results. Long queries see the highest takeover rates, and some categories (Health, Science, YMYL) are seeing AI responses on nearly half of all searches. Branded and commercial intent searches remain more stable. People looking for a company, a tool, or a transaction still see traditional blue links in most cases. That gap is where marketers still have room to grow, defend, and influence. The big shift is that informational SEO is becoming an AI-first environment. You can still rank, but the click patterns change. High-ranking pages in certain categories will see fewer visits simply because AI answers sit above them. Marketers should know which of your queries fall into high-AIO territory. ↳ Strengthen commercial intent content. ↳ Build authority that AI can reference. ↳ And shape visibility in the parts of search that still drive traffic. Which category of your content is most exposed today?

Google faces one of the most intriguing strategic dilemmas in its history: The AI-powered search paradox. Traditional search has been Google's cash cow, driven by neatly aligned ad placements among multiple organic results. With AI-powered search and conversational interfaces, the playing field fundamentally shifts. Instead of numerous listings, AI gives a single synthesized answer. Look at how the search landscape has evolved in just six months. AI Overviews now appear in 85% of results, up from 77% in January. Traditional ad placements? They've stayed flat while AI-driven features dominate more screen real estate. This leaves Google in a classic Prisoner's Dilemma: ↗️ Move too soon: Introduce AI-powered chat aggressively, and risk cannibalizing the current lucrative search ad business without a proven ad revenue alternative. ↘️ Move too slowly: Hold back to protect current revenues, but potentially allow competitors (like Microsoft and OpenAI) to seize market share and redefine user expectations. The core challenge? Monetizing AI-driven results without disrupting user trust and the streamlined experience. Possible paths I can see Google taking: 1. Native, highly relevant "sponsored" insights or embedded recommendations. 2. Subscription or premium models for advanced AI-driven assistance. 3. Hybrid models blending conversational AI with targeted advertising at key conversational touchpoints. Google's decision here could reshape digital marketing, media buying, and the entire online ad ecosystem for decades. How do you think Google should navigate this dilemma?

Google is doubling down on AI-powered search. During yesterday’s earnings call, CEO Sundar Pichai outlined Google’s plans to transform Search into an AI-driven assistant, expanding beyond traditional query-based results. The shift began with AI Overviews—Google’s attempt to synthesize information rather than simply providing links. Despite a rocky rollout, including widely publicized inaccuracies, Google is moving forward with deeper AI integration. Pichai highlighted Project Astra, DeepMind’s multimodal AI system that processes live video and provides real-time responses. He hinted that Astra could power future AR smart glasses, reinforcing Google’s broader AI ambitions. Another key initiative is Gemini Deep Research, an AI agent that generates long-form research reports—effectively automating tasks that traditionally required multiple searches. Additionally, Project Mariner aims to interact with websites on behalf of users, potentially eliminating the need to visit them at all. Pichai also suggested making Search more conversational, enabling follow-ups and real-time interaction. Will these AI-driven changes disrupt the digital ecosystem? It’s clear that websites that rely on Google’s traffic will see reduced human traffic. It’s also clear that advertisers will need to rethink their SEO and SEM strategies. Google is on a mission. Facing competition from practically every foundational model builder and hyperscaler, our friends in Mountain View have to aggressively evolve Search – failure is not an option. -s

𝗛𝗼𝘄 𝘄𝗲 𝗮𝗿𝗲 𝘂𝘀𝗶𝗻𝗴 𝗔𝗜 𝗮𝘁 𝗚𝗼𝗼𝗴𝗹𝗲 𝘁𝗼 𝘄𝗼𝗿𝗸 𝘀𝗺𝗮𝗿𝘁𝗲𝗿 AI isn't just something Google is building for the world - it's also completely changing how we work internally every single day. And I'm seeing it first hand: From my colleagues to my own tasks to many tools and processes, AI is everywhere. 🚀 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝟭𝟬 𝘄𝗮𝘆𝘀 𝗚𝗼𝗼𝗴𝗹𝗲𝗿𝘀 𝗮𝗿𝗲 𝗽𝘂𝘁𝘁𝗶𝗻𝗴 𝗔𝗜 𝘁𝗼 𝘄𝗼𝗿𝗸: 1️⃣ Generating code: ↳ AI helps write 30% of Google's new code, significantly accelerating development. 2️⃣ Writing meeting notes: ↳ Gemini in Google Meet summarizes discussions and action items, replacing "manual" note keeping. 3️⃣ Prioritizing & fixing bugs: ↳ AI quickly identifies and resolves issues, even handling duplicate bugs automatically. 4️⃣ Sparking creativity: ↳ Marketing teams use Gemini to brainstorm campaigns and YouTube creatives 5️⃣ Understanding employee feedback: ↳ NotebookLM quickly summarizes themes from thousands of responses for internal events and surveys. 6️⃣ Creating visual assets: ↳ Generative AI crafts visuals for events like keynotes and videos. 7️⃣ Testing new ideas: ↳ Google DeepMind uses AI to mock up and animate creative concepts and pitch ideas. 8️⃣ Keeping our platforms safe: ↳ Trust & Safety uses AI to detect and flag policy-violating content efficiently. 9️⃣ Improving sales lead quality: ↳ AI filters help sales identify promising customers, increasing conversions and making sales cycles shorter. 🔟 Reducing food waste: ↳ Even our on-campus chefs use AI-driven insights to refine menus and cut food waste by over 30%. And it isn't just about faster output. It's about being creative, tackling bigger challenges, and making our work more impactful. 💥 What are your favorite AI use cases? 🤔 Let me know in the comments below. 💬 -- 🔔 Follow me for more posts on digital marketing, careers in tech, and life at Google. ♻️ Share this post with your network if you enjoyed it.

The Ultimate AI SEO Blog Structure: 1/ Start with the main question Focus on the actual questions people type into ChatGPT. Your H1 should reflect that question directly, since it becomes the “primary query” the rest of the page supports. Example: “What is the best AI visibility platform?” 2/ Add credibility signals at the top AI models prefer up-to-date information, reviews, and expert signals. Add things like: • Reviewed by • Last updated • Recent insights or case studies It increases your odds of being cited. 3/ Give a direct answer immediately AI models look for quick clarity. Start the page with a 1–2 sentence solution to the main question. This helps you win featured snippets, Perplexity pulls, and ChatGPT short responses. 4/ Use a TL;DR to frame the page Summarize the key points in a quick, skimmable block. Use short sentences or simple bullets. This gives AI engines and readers a concise version of the entire page. 5/ Use visuals that explain the idea Add diagrams, step-by-step visuals, or small charts to illustrate concepts. AI models read alt text and use visuals to interpret structure and meaning more accurately. 6/ Provide citable content Link to reliable and relevant sources. LLMs use citations to validate information and expand on answers. Give them material AI can rely on: • Data • Definitions • Clear explanations 7/ Format for AI readability Give each section one idea, use clean H2 and H3 headings, and keep the structure simple. Think like a user asking variations of the same prompt: • How does this work • Why is it important • What steps should I follow This matches conversational search patterns. 8/ Finish with a clear CTA Invite users to take the next step. Ask them to try a tool, read a related guide, or leave feedback. A CTA helps define the intent of your page. Final takeaway: Brands that win in 2026 will optimize for the places people ask questions, not just where they type keywords.

AI Search Is Rewriting the Rules - Here’s How Your Business Can Get Found The shift from traditional SEO to AI search is accelerating and the data is clear: Different AI platforms use radically different sources to answer user questions. If you want your brand to be visible in the age of AI, you’ll need new strategies tailored to each platform. 🔍 What the Latest Research Shows Profound’s analysis of 30 million citations across ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot (Aug 2024–present) reveals: ChatGPT is Wikipedia-heavy (47.9% of citations), with Reddit a distant second (11.3%). Google AI Overviews spreads citations across Reddit, YouTube, and Quora reflecting its ecosystem. Perplexity has a unique pattern, with a recent surge in Reddit citations, now accounting for over 4.5% of all references. Microsoft Copilot grounds its answers in your organisation’s internal data (documents, emails, SharePoint) and trusted web sources, so the most-cited sources vary by company and configuration. Takeaway: There’s no one-size-fits-all approach. If you’re focusing on AEO/GEO (AI/Google Engine Optimisation), you must adapt your strategy for each platform. 💡 James Cadwallader’s Perspective (CEO, Profound): “The user doesn’t care where content comes from as long as they get viable answers... the new environment basically requires that we consider bots as a primary consumer because the bots are the interpreters of information for the end user.” 🛠 How to Boost Your Brand’s AI Visibility ✅ Publish on Crawl-Indexed Platforms: Use platforms like Medium, PR Newswire, and others regularly scraped by Common Crawl and AI engines. ✅ Optimise for AI and Search Engines: Make sure your pages are crawlable, indexable, and use structured data (FAQ, How-To, Article schema). ✅ Monitor Your Inclusion: Tools like Profound’s Conversation Explorer let you see how often your brand appears in AI search results across ChatGPT, Perplexity, and Copilot. ✅ Engage With AI Tools: Reference your own content in conversational AI to build authority and visibility. ✅ Structure for Clarity: AI tools like Perplexity value clear headings, direct answers, and up-to-date knowledge over backlinks. 📈 Why This Matters AI search is quickly becoming a dominant discovery channel. Gen Z and Millennials are already using AI tools over Google for research and recommendations. AI conversations span the entire marketing funnel, from awareness to conversion, all within a single session. Key Takeaway: To stay visible and influential in an AI-driven world, publish high-quality, crawlable content on domains included in major training datasets, and optimize for both human and machine readers. The future of search is agentic - make sure your brand is ready. Sources: Insights and data from Profound, James Cadwallader, Perplexity Deep Research, and the latest industry report

You don’t need another SEO vs AEO debate. You need a strategy that makes you visible. In AI search, visibility depends on 3 things: → whether AI can find you, → whether it trusts you, and → whether it can understand and cite your content. This 6-pillar checklist combines proven SEO fundamentals with the steps that actually matter for AI search 👇 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 1. Brand Presence & Mentions → If AI can’t find you, it can’t recommend you. ☐ Check visibility in ChatGPT, Perplexity, Claude etc. ☐ Secure mentions in directories and roundups ☐ Build a strong off-site footprint (PR, Reddit, forums) 2. Entity & Authority Signals → AI recommends what it trusts. ☐ Wikipedia/Wikidata, Knowledge Panel ☐ Author signals, reviews, credentials ☐ Original data and credible backlinks 3. Content & Passage Optimization → Be easy to extract and quote. ☐ Lead with answers ☐ Use Q&A blocks, lists, schema ☐ Keep content clear and current 4. Conversation & Community Coverage → Visibility starts where people talk. ☐ Forums, Reddit, niche communities ☐ Real language over keyword stuffing ☐ Consistency matters 5. Technical Foundations → If crawlers can’t access you, AI can’t either. ☐ Open crawler access ☐ Optimize Core Web Vitals, structure, sitemaps 6. Visibility Tracking & Adaptation → You can’t grow what you don’t track. ☐ Monitor mentions and share of voice across LLMs ☐ Spot trends and shifts early ☐ Learn from competitors fast - - - - - - - - - - - - - - - - - - - - - - - - - - - - - This isn’t a “future” SEO checklist. This is SEO, just in a new environment. The brands showing up now are the ones AI will keep recommending. Don’t wait to “catch up” later. Build visibility where it actually matters today. ♻️ Repost it to share with your network. Follow me Emilia Möller for insights on AI visibility.