If you search Google for your business, you probably show up somewhere. But if you ask ChatGPT, Gemini, or Google's AI Overview the same question, chances are you don't exist.
That's not a hypothetical. We ran our own site — TechBuild.me — through Semrush's AI visibility checker and scored a flat zero. No mentions across ChatGPT, Google AI Overview, AI Mode, or Gemini. And we're a technology company that builds websites for a living.
The reality is that most small and medium businesses are completely invisible to AI search engines right now. And with millions of people switching from traditional Google searches to AI-powered answers every month, that invisibility is becoming a real business problem.
This guide covers exactly what we're doing to fix that — and what any business can do to start showing up when AI answers questions in their industry.
What Is AEO and Why Does It Matter?
Answer Engine Optimisation (AEO) is the practice of structuring your online presence so that AI-powered search engines can find, understand, and cite your business when answering user questions.
Traditional SEO focuses on ranking web pages in search results. AEO focuses on becoming a recognised entity that AI models reference in their answers. The distinction matters because the two systems work differently.
When someone types a query into Google, the search engine returns a list of pages ranked by relevance and authority. The user clicks through to read those pages. When someone asks the same question to ChatGPT or Gemini, the AI synthesises an answer from its training data and (increasingly) from real-time web sources. It doesn't return a list of ten blue links — it gives a direct answer and may cite one or two sources.
That means the old game of competing for position seven or eight on page one is becoming less relevant. The new game is being one of the two or three sources the AI actually names.
How AI Search Engines Decide What to Cite
AI models don't rank pages the way Google does. They recognise entities — companies, products, people, and concepts — and associate those entities with topics. When a user asks a question, the model looks for the most authoritative entity associated with that topic and pulls information from sources connected to it.
Three signals determine whether an AI will cite your business.
Entity recognition is the first and most fundamental. The AI needs to know your business exists as a distinct, identifiable thing. That means your company name, product names, and what you do need to appear consistently across multiple sources in a way machines can parse — not just in marketing copy designed for human readers.
Topical authority is the second signal. The AI needs to associate your entity with a specific domain of expertise. A business that publishes deep, factual content on a narrow topic builds stronger topical authority than one that publishes surface-level content across many topics. If you build websites for small businesses, the AI needs to see enough evidence to connect your name with that specific category.
Cross-source corroboration is the third signal and often the most overlooked. AI models trust information that appears consistently across multiple independent sources. If your business is described the same way on your own website, in a Medium article, on a directory listing, and in a Chrome Web Store description, the model has much more confidence that its understanding of your business is accurate. A single website, no matter how well optimised, isn't enough.
The AEO Foundation: Making Your Business Machine-Readable
Before worrying about content strategy or backlinks, the foundation needs to be right. AI crawlers need to be able to extract structured, factual information about your business quickly and unambiguously.
Dedicated Product and Service Pages
Most small business websites have a homepage, an about page, a services page that lists everything in brief, and a contact page. That structure works for human visitors but makes it difficult for AI models to understand what you actually offer.
Each distinct product or service needs its own page, and each page needs to open with a clear, factual definition — not a marketing tagline. AI models heavily weight the first paragraph of a page when deciding what it's about.
Consider the difference between these two approaches:
Marketing-focused opening: "Transform your business with our revolutionary all-in-one platform that empowers entrepreneurs to achieve their dreams."
Entity-focused opening: "TechBOS is an all-in-one business operating system that combines website management, CRM, appointment booking, e-commerce, and email marketing into a single platform. It is designed for small and medium businesses as an affordable alternative to platforms like HubSpot."
The second version contains specific, extractable facts: what the product is, what it includes, who it's for, and how it's positioned. An AI reading that paragraph can immediately categorise the entity and associate it with relevant queries.
Structured Data (JSON-LD Schema)
Structured data is markup you add to your website's code that explicitly tells search engines and AI crawlers what your content represents. It's the single most impactful technical change for AI visibility.
For a business offering products or services, the key schema types are:
Organisation schema on your homepage should include your business name, any trading names, your URL, a description, founding date, founder information, physical address, and links to your profiles on other platforms (social media, GitHub, directories, app stores). The sameAs property is particularly important because it helps AI models connect your presence across different platforms into a single entity.
SoftwareApplication or Product schema on each product or service page should describe what each offering is, its category, pricing, features, and who created it.
FAQPage schema on relevant pages provides question-and-answer pairs that AI models can extract directly. When someone asks an AI a question that matches one of your FAQ entries, your content becomes a natural source for the answer.
If you're using a platform like Next.js, these can be added as JSON-LD script tags in your page components. If you're using WordPress, plugins like Yoast or RankMath can generate much of this automatically.
The llms.txt File
A relatively new convention, llms.txt is a plain text file placed at the root of your website (like robots.txt) that provides AI crawlers with a structured summary of your business. Not all AI crawlers read it yet, but adoption is growing, and it takes minimal effort to implement.
The file should be comprehensive: who you are, what you offer, descriptions of each product or service, your technology stack if relevant, and links to key pages. Think of it as a briefing document for an AI that's learning about your business for the first time.
Comparison Pages
This is a high-leverage tactic that most small businesses overlook. When people ask AI search engines for recommendations, they frequently phrase their queries as comparisons: "What's a cheaper alternative to HubSpot?" or "Salon software better than Fresha for multi-location."
If you create a page that directly addresses that comparison — structured as a fair, factual analysis rather than a one-sided sales pitch — you become a potential source for exactly those queries. The key word is "fair." AI models are sophisticated enough to discount heavily biased content, so including honest assessments of what your competitor does better actually increases your credibility as a source.
Building Topical Authority Through Content
With the technical foundation in place, the next step is creating content that establishes your business as an authority on specific topics. This is where AEO diverges most sharply from traditional content marketing.
Write Reference Material, Not Blog Posts
Traditional blog posts are often optimised for engagement — catchy headlines, personal anecdotes, calls to action. AEO content is optimised for citation — factual, comprehensive, and structured as a definitive resource.
The distinction shows up in how you approach a topic. A traditional blog post about small business websites might be titled "5 Reasons Your Business Needs a Website in 2026" and run 800 words. An AEO-focused guide on the same topic might be titled "What Does a Small Business Website Actually Cost in 2026?" and run 2,500 words with specific pricing data, feature comparisons, and platform breakdowns.
The blog post gets shared on social media. The guide gets cited by AI.
Good AEO content targets the exact questions people ask AI search engines. These tend to be specific, factual, and comparison-oriented:
"What is the best all-in-one business platform for small businesses?"
"How much does salon management software cost?"
"What's the difference between building a website on WordPress vs Next.js?"
"How do sales commission structures work?"
Each of these is a query someone might type into ChatGPT. If your content provides the most comprehensive, factual answer, you're in the citation pool.
Writing Rules for AI Citation
Several patterns consistently correlate with content that gets cited by AI models:
The first paragraph should contain a clear, direct answer to the question the content addresses. AI models often extract opening paragraphs as summary answers.
Use specific numbers, dates, and facts rather than vague claims. "Plans start at $49/month" is extractable. "Affordable pricing" is not.
Include properly marked-up FAQ sections. Questions that mirror how people phrase AI queries, with concise factual answers, are among the most frequently cited content types.
Aim for 2,000 words minimum on authoritative guides. AI models associate depth with authority.
Keep content updated with visible "last updated" dates. AI models prefer recent sources over older ones.
Include author information with credentials. A bylined article by someone with demonstrated expertise carries more weight than anonymous content.
Cross-Source Corroboration: Getting Mentioned Elsewhere
Creating excellent content on your own website is necessary but not sufficient. AI models give significantly more weight to entities that appear consistently across multiple independent sources. This is where the effort multiplies.
External Publishing Platforms
Republishing your expertise on platforms like Medium, Dev.to, LinkedIn Articles, Hashnode, and IndieHackers creates independent instances of your entity in the AI's training and retrieval data. Each article should mention your business and products by name, link back to your website, and use consistent descriptions.
The key word is "consistent." If your website describes your product as "an all-in-one business platform" but your Medium article calls it "a website builder," the AI has weaker confidence in what your product actually is. Use the same language everywhere — ideally the same language as your llms.txt file and your schema markup.
Directory and Review Platform Listings
Software directories and review platforms are heavily crawled by AI models because they aggregate structured information about many products in consistent formats. Getting listed on platforms like Product Hunt, G2, Capterra, AlternativeTo, SaaSHub, and Crunchbase creates multiple independent data points that confirm your entity.
For local or service-based businesses, the equivalent would be Google Business Profile, Yelp, industry-specific directories, and professional association listings.
Earned Mentions and Media
The highest-value cross-source signal is being mentioned by someone else without your direct involvement. This includes journalist quotes, podcast appearances, guest posts, case studies featuring real clients, and reviews from independent users.
Platforms like Connectively (formerly HARO) and Qwoted connect journalists with expert sources. Responding to queries in your area of expertise can result in being quoted as "Jane Smith, founder of [Your Company]" in a published article — exactly the kind of independent entity mention that AI models use to build confidence.
Even small podcast appearances create transcripts that get indexed. A 30-minute conversation where you discuss your industry and mention your business by name several times generates a substantial independent source.
YouTube and Video Content
Video platforms are increasingly important for AEO because transcripts get indexed by AI models. A YouTube video titled "I Built a HubSpot Alternative — Here's How It Compares" generates a transcript that contains your product name, feature descriptions, and competitive positioning, all attributed to a specific creator on a high-authority platform.
Every video should mention your business and key products by name within the first 30 seconds, include a detailed description with product links, and use chapters with timestamps (which become structured data that AI can parse).
Technical AEO Checklist
Beyond content and cross-source strategy, several technical elements should be in place:
Your robots.txt file should allow all major AI crawlers. Some businesses have inadvertently blocked GPTBot, Google-Extended, or Anthropic's crawler, making themselves invisible to those platforms.
Your sitemap should be current and submitted to Google Search Console. While AI models don't all read sitemaps directly, Google's AI features rely on Google's index, which relies on your sitemap.
If you're using a framework that supports it, implement IndexNow — a protocol that notifies search engines immediately when you publish or update content, rather than waiting for them to discover changes on their next crawl.
Your about page should include a founder or team bio with links to social profiles and external platforms. This helps AI models connect your personal entity with your business entity, strengthening both.
Consistent NAP (Name, Address, Phone) data across all listings reinforces entity recognition. If your business name appears differently on your website, your Google Business Profile, and your Crunchbase page, the AI may treat these as separate entities.
Open Graph and Twitter Card meta tags on all pages ensure that when your content is shared or referenced, it carries consistent structured information about what it represents.
How to Measure Progress
AEO results take longer to appear than traditional SEO improvements, but they're measurable:
AI visibility tools like Semrush's AI search visibility checker provide a baseline score and track changes over time. Moving from N/A to any score at all is the first meaningful milestone.
Manual AI spot checks are the most direct measure. Monthly, ask ChatGPT, Gemini, and Perplexity the questions your target customers would ask: "What are the best alternatives to [competitor]?" or "What is [your product name]?" Track when you first appear in responses.
Brand search volume in Google Trends shows whether awareness of your business is growing. Increasing brand searches correlate with increasing entity recognition by AI models.
Search Console impressions for comparison-style queries ("your product vs competitor," "your product alternative") indicate that your comparison content is being indexed and shown.
Backlink growth tracked through free tools like Semrush or Ahrefs shows the accumulation of independent references that feed cross-source corroboration.
The Timeline
Expect to invest 30–60 days of consistent effort before seeing measurable changes in AI visibility. The technical foundation (structured data, llms.txt, product pages) can be completed in the first two weeks. Content creation and external publishing should be ongoing, with a target of one substantial piece per week. Directory listings and platform profiles can be set up over a few days.
The first sign of progress is usually appearing in responses to very specific, low-competition queries — "What is [your exact product name]?" rather than "What are the best business platforms?" Broader visibility follows as cross-source signals accumulate.
This isn't a quick fix, and it doesn't replace traditional SEO. It's an additional layer of visibility that's becoming increasingly important as more consumers shift from searching Google to asking AI. The businesses that invest in AEO now, while most competitors haven't heard the term, are the ones that will own those AI-generated recommendations in 12 months.
What We're Doing at TechBuild.me
We're following this exact playbook ourselves. We started from zero AI visibility, with 2,370 Google impressions over three months and zero AI mentions. We're building dedicated product pages for TechBOS, CloserOS, and Coterie with entity-focused opening paragraphs. We're expanding our structured data and llms.txt. We're publishing definitive guides (like this one) that target the exact questions our potential clients ask AI. And we're building cross-source signals through our Chrome extension SiteCheck, our Medium presence, and our YouTube channel.
We'll report back on what works and what doesn't. Because the best way to help our clients get found in AI search is to figure it out ourselves first.
Published by TechBuild.me — your website, CRM, and business tools in one platform. Built in Bradenton, FL.
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