How To Gain Visibility Across AI Search Engines?

It is dominated by AI overviews and zero-click search

Google’s AI Overviews, launched to the public in 2024, mark a foundational shift. That’s because instead of showing ten blue links, the search engine now provides synthesized answers. And it often quotes or summarizes from multiple sources, without requiring you to click through.

According to SEMrush’s AI Overviews Study, the presence of an AI Overview reduces clicks to traditional organic results by up to 65% for some queries.

This means:

• Visibility inside the overview is the new Page One.
• If your brand isn’t being cited as a source within these AI responses, you’re increasingly invisible.
• Even if users don’t click, brand impressions within AI summaries build awareness and trust.

For instance, our client Jeremiah runs Arrowfish Consulting, a leading business valuation and accounting firm. And blogs from his website often get cited at the top of AI overviews. This helps generate awareness about his brand and gain trust as a valuation expert.

You need to look beyond Google, it’s a multi-AI world

Generative search isn’t just about Google. You’re now optimizing for a distributed network of AI interfaces, each with unique behaviors. This includes:

AI searches are conversational and persistent

The new search is conversational, contextual, and ongoing. And with tools like Google’s Project Astra, we’re shifting from one-off queries to multi-turn interactions.

Here’s how it works:

• Users won’t just ask “What is SEO?” They’ll ask follow-ups like “How does it apply to small businesses?” or “Can you show a checklist?”
• Your content must answer layered questions and not just isolated keywords.
• The AI remembers context. So, if your brand is mentioned once, follow-up queries might depend on how well you’re presented initially.

AI trusts authority and users trust AI

When users read a response in an AI Overview or from ChatGPT, they assume the AI knows best. This makes AI citations a powerful trust signal, even more powerful than ranking on Page 1 of Google.

So, for your brand to be chosen and cited, you should:

• Build content that’s easily extractable and clearly answers the query.
• Demonstrate authority, credibility, and consistency across the web.
• Maintain a strong presence on third-party platforms (Google Business, Reddit, LinkedIn, G2, Trustpilot, etc.), which AI tools often scan to validate trustworthiness.

Take Steam and Sauna Experts, for instance. We built them a high converting website and helped boost their online authority and trust by following the above three pointers. And now, they top AI responses as the best steam and sauna company in South Florida.

Content is being commoditized. You’ve got to stand out with unique value

Basic content is no longer a moat as AI can generate it better, faster, and at scale. This has created a “Content Collapse” problem where generic advice, how-tos, and product descriptions are easily summarized and replaced by generative tools.

So, to survive and win in AI search:

• Your content should offer unique insights, real-world experience, data, storytelling, and brand voice.
• You should shift from “How to rank” to “How to be cited,” because the citation is the click in the AI world.

In short, search is no longer about ranking for one keyword in one search engine. Today, you’re optimizing for visibility across an ecosystem of AI-driven platforms that span voice, chat, video, and web.

And to that end, your business will thrive if you:

• Adapt to zero-click environments
• Build a brand AI can trust
• Focus on being the source, not just linking to it
• And treat content as product, not just marketing

In the next section, we’ll explore how this change redefines the core principles of SEO and how to evolve your strategy to match.

1. The foundation layer: Crawlability and extractability

The first layer of our generative engine optimization pyramid addresses one core question: “Can AI find and understand your content?”

This is the non-negotiable baseline. Without it, nothing else matters.

Your key objectives here should be

• Ensure technical SEO hygiene: Mobile-first indexing, fast load times, proper canonical tags.
• Use semantic HTML structure (H1s, H2s, lists, tables) so AI can parse your content easily.
• Create clear, scannable answers to commonly asked questions, one idea per paragraph.
• Add schema markup (e.g., FAQ, HowTo, Organization) to help AI contextualize the content.
• Focus on content modularity and break things into chunks that are easily quotable or summarized.

Why does this matter?

LLMs and AI interfaces like ChatGPT, Bing Copilot, and Perplexity often lift snippets from well-structured HTML, bullet points, and schema-rich sections. Meaning if your content isn’t machine-readable, you won’t get surfaced no matter how good the insight is.

2. The middle layer: Credibility and trustworthiness

The middle layer of our AI search pyramid looks to answer this: “Is your content and brand worthy of citation?”

That’s because once your content is accessible, the next question AI asks is: Should I trust this?

And to gain trust, you should:

• Build E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).
• Include real authorship with bios, credentials, and topical authority.
• Accumulate off-page signals: backlinks from reputable sources, mentions on Reddit, Quora, LinkedIn, industry publications, or directories.
• Maintain a consistent presence across platforms. Align facts about your brand (name, address, founders, product lines) across your site, GMB, LinkedIn, Wikipedia, etc.
• Encourage brand + topic associations (e.g., “Notion for team productivity” or “Dr. Axe for gut health”) in community forums and UGC platforms.

Why does this matter?

AI engines increasingly lean on web consensus. So, when multiple sources validate a claim or brand, it signals trust. In fact, when Gemini or ChatGPT “choose” sources, they prefer brands that demonstrate clarity, credibility, and consistency across the web.

3. The top layer: Unique and valuable

The top layer of our AI search engine optimization pyramid finds the answer to this question: “Is your content worth surfacing over a generic AI summary?”

Here, you should look for what makes your brand undeniably worthy of visibility. It should not just be extractable but irreplaceable.

And to that end, you should:

• Share proprietary data, original research, or unique methodologies.
• Publish use-case-driven content and first-person insights, things AI can’t generate from thin air.
• Offer personal storytelling or thought leadership that adds value beyond what’s already been summarized.
• Integrate multimodal assets: charts, videos, audio clips, tools, content that’s useful and hard to replicate.
• Build a clear brand narrative and voice. Be recognizable even if your name is removed from the content.

Why does this matter?

Most AI-generated responses are bland. They pull from the average. So, the brands that win in AI search are the ones that go beyond the average, offering something that can’t be easily aggregated. You see, AI engines want to give users the best answer, not the most common. That’s your edge.

Real-world example: Why Steam and Sauna Experts get cited

Steam and Sauna Experts are a leading e-commerce website for sauna equipment and accessories. We’ve gone from doing their SEO to AI search optimization, winning them stellar results on both fronts.

Now, their blogs, products, and services get cited across AI overviews and generative results. And this is mainly because the website caters to the above pyramid and adds value that generative tools can’t synthesize elsewhere.

You can also audit your content using the pyramid, here’s how

Go through your top URLs and ask:

• Is this technically clean and extractable?
• Would an AI model trust and cite this?
• Does this content offer something no other article does?

If the answer to any layer is “no,” you’ve just found an optimization opportunity.

1. Structure your content for scannability and extraction

Generative engines love content that’s easily digestible and modular. They often don’t summarize full pages, they extract atomic units of information, like a paragraph, list, or definition.

Here are some best practices you can follow:

• Use clear subheadings (H2, H3, H4) that reflect specific user intents or sub-queries.
• Write short, focused paragraphs (2–4 lines) that answer a single idea per block.
• Use bullet points and numbered lists where applicable as these are more likely to be pulled into AI answers.
• Use callout boxes for definitions, facts, or key takeaways.
• Avoid fluff or stacking multiple ideas into long blocks of text.

For instance

Instead of:

“AI search engines are becoming more popular, and there are many ways to improve visibility such as schema, internal linking, quality writing, and domain authority…”

Use:

How to Improve Visibility in AI Search Engines

• Add schema markup (FAQ, HowTo, Article).
• Improve internal linking for topic clustering.
• Use clean HTML structure with proper headers.
• Build topical authority through depth.

This layout is AI-readable, summarizable, and citation-ready.

2. Align the content with query intent instead of keywords alone

AI search engines excel at interpreting meaning behind a query. Meaning they don’t need exact-match keywords to understand relevance. But that doesn’t mean keywords are dead, they’re just contextualized now.

Here’s how to Adapt:

• Still include primary and secondary keywords, but write naturally.
• Focus on semantic search alignment. Cover the full scope of intent using related concepts, questions, and variations.
• Use question-style headers (e.g., “What Is AI Visibility?” or “Why Is Crawlability Important?”). LLMs love matching these to user queries.
• Include follow-up style answers that anticipate the next user question. This mimics how users talk to AI tools.

For instance, a lot of people search about using a sauna before bedtime. So, when it came to covering this topic for Steam and Sauna Experts, we fulfilled the core intent of the query instead of just stuffing keywords.

The result: Top AI Overview rank and multiple citations across different AI platforms.

Pro tip: Use tools like AlsoAsked, AnswerThePublic, or Perplexity.ai to discover multi-turn user query chains. Then reflect those in your subheadings.

3. Use structured data (schema) strategically

Structured data (schema.org) isn’t just for traditional SERPs. AI models also use it to identify context, roles, and content types.

So, focus on high-impact schema types:

• Article / BlogPosting (always)
• FAQPage / QAPage\
• HowTo / Step-by-Step
• Organization / Author / Product / Review
• Speakable (for voice interfaces)

Also, use FAQ schema not just at the bottom, but throughout the article (in-line Q&A blocks), making each one a stand-alone answer.

4. Optimize for language model (LLM) friendliness

AI systems extract content differently than humans. They often:

• Ingest entire HTML structures
• Ignore complex JavaScript or bloated builders
• Prefer clarity over cleverness

Here are some of my tips to make your content LLM-friendly:

• Use descriptive anchor text (“learn about zero-click search” instead of “click here”).
• Avoid ambiguous references like “as mentioned above” or “read the next section.”
• Remove fluff intros and get straight to the point in each section.
• Provide examples. LLMs tend to surface real-world use cases or “For example…” statements.

5. Add unique multimodal elements

AI tools increasingly index not just text, but images, videos, charts, and tools, especially when embedded with semantic clues (captions, alt text, structured markup).

So, you should include:

• Custom charts or graphics (with proper alt text and captions).
• Embeddable tools (calculators, checklists).
• Transcripts or summaries of embedded videos.
• Infographics that explain core ideas.

Bonus: Tools like Google AI Overviews and Perplexity’s Related Media are starting to cite visual content directly.

6. Internal linking with context

AI tools do track link context. So, don’t just internally link but explain why the link matters. Here’s how.

Instead of:

Learn more [here].

Use:

Learn how to optimize for zero-click AI answers in our detailed guide on AI citations. Your anchor text should reflect the destination’s intent and value, increasing the odds it gets recognized and cited by AI interfaces.

On-page AI search optimization checklist

1. Have digital footprint across the web

LLMs like those used by ChatGPT, Perplexity, or Bing Copilot are trained on vast public data, including:

• News sites
• Educational domains
• Government sources
• Authoritative blogs and wikis
• Forums and UGC platforms
• Social signals

So, your goal should be to ensure your brand or personal entity has a well-distributed and semantically connected presence across multiple platforms. This is how you become known to the AI layer.

Here’s what you can do:

1. Secure profiles on platforms that AI models crawl and index:
   • LinkedIn (thought leadership content)
   • Reddit, Quora, Stack Overflow (contributions, answers)
   • YouTube (indexed transcripts + authority via presence)
   • Medium, Substack, DEV.to, or niche publications
2. Get mentioned or cited by third-party websites in your niche (guest posts, PR).
3. Create a Google Knowledge Panel if possible (or optimize your business’s visibility in Google Maps/local listings).

Why does this matter?

Tools like Perplexity and You.com often cite sources with a cross-platform presence. If you’re not visible across the web, your content may not be selected, even if your site is optimized.

2. Build E-E-A-T signals (experience, expertise, authoritativeness, trust)

AI search engines increasingly rely on E-E-A-T principles. And they do so not just from Google, but from how LLMs are fine-tuned to prioritize credible and expert-backed information.

You can boost E-E-A-T by:

• Having named authors with detailed bios (linked to platforms like LinkedIn).
• Publishing firsthand content (case studies, personal insights, examples).
• Including author credentials, awards, or affiliations in schema and visible page text.
• Earning citations from expert-level domains like niche blogs, academic sources, or reputable news.
• Highlighting trust badges (certifications, BBB, ISO) where applicable.

Tip: Tools like ChatGPT now offer web citations. The more credible signals your brand has online, the higher the likelihood your domain will be cited in AI summaries or footnotes.

3. Get digital PR, mentions, and brand citations

Backlinks still help, but in AI search, brand mentions (with or without a link) carry weight too.

You can build mentions via:

• Guest blogging on niche or high-authority sites.
• Collaborations or interviews with known influencers.
• Submitting expert quotes to services like Help a Reporter Out (HARO) or Qwoted.
• Getting featured in industry roundups, podcast guest spots, or webinars.

Bonus: Use tools like Brand24, Ahrefs Alerts, or Google Alerts to monitor where your brand or domain is being mentioned and track where authority is building.

4. AI-friendly link building

Classic link-building rules still apply. But now, context-rich citations matter more than just anchor text.

Here’s what you can do:

• Secure backlinks from pages that clearly explain context around your contribution.
• Favor placements in educational, technical, and evergreen resources (LLMs favor stable data).
• Prioritize high-authority topical relevance over just domain authority (e.g., health links from WebMD > random newspaper site).
• Leverage “linked unstructured data” like datasets, case study stats, or tools as these get embedded into AI’s training more deeply than promo pages.

Note: Even non-clickable citations (like brand names, quotes, tool mentions) in trusted sources can earn you visibility in tools like Perplexity or AI Overviews.

5. Optimize your platform for AI citability

AI search platforms extract answers from platform-native content too and not just websites.

Here are some key channels you can leverage:

• LinkedIn Articles (rank well in ChatGPT and Bing)
• Reddit AMA threads or in-depth answers
• Quora Spaces or curated answer collections
• YouTube with detailed descriptions and transcript optimization
• GitHub (for dev tools, SaaS, and data-related brands)

These sources are often trusted by AI engines for crowd wisdom or domain-specific commentary.

6. Align with citable content formats

Certain content formats are more likely to be extracted and cited by AI engines.

You can focus on:

• Definitional content (What is…, How does…, Why does…)
• Data-driven content (surveys, reports, benchmark stats)
• Step-by-step guides (especially HowTo Schema-optimized)
• Curated lists (tools, examples, frameworks, templates)
• Case studies with results

LLMs love to cite clear declarative content with attribution value. If your page contains an original framework or benchmark, it’s far more likely to be reused.

Off-page AI search optimization checklist

In short

Today’s AI engines assess trust not by quantity of backlinks alone but by your digital credibility fabric. For instance:

• Are you mentioned in places humans trust?
• Does your content reflect depth and original insight?
• Do others in your industry talk about or cite your work?
• Are your authors real, experienced, and visible?

Answer yes to those questions consistently and you won’t just win in Google, you’ll dominate across AI tools hungry for credible content.

1. Have structured data & schema markup

Schema markup helps machines understand what your content is about beyond just keywords. Google’s AI Overviews and other engines often rely on structured data to identify answer-ready content.

Here’s how you can implement these schema types:

• Article + author, datePublished, headline, publisher
• FAQPage for common questions and AI-ready snippets
• HowTo for step-by-step content
• Breadcrumb to help engines understand site structure
• Product, Review, or Event if relevant to your business
• Organization and Person schema for E-E-A-T signals

Pro Tip: Use Google’s Rich Results Test or Schema.org validator to validate your structured data.

2. Use semantic HTML and logical hierarchy

Large language models parse your content using HTML tags. Here, clean semantic HTML helps them extract and understand what’s important.

This is why I suggest you use tags in an order like this:

• <h1> only once per page to clearly signal the main topic.
• Use <h2>, <h3>, etc. to build a logical hierarchy of subtopics.
• Use <ul> / <ol> for lists — these are often turned into bullet point summaries or answer blocks by AI.
• Include <strong>, <em>, <blockquote>, and <code> to provide semantic signals.
• Avoid excessive <div> soup or JavaScript-heavy content blocks that don’t degrade well for crawlers.

Why does this matter?

AI search tools extract and repurpose content at scale. Proper markup ensures your content can be safely reused, cited, or summarized.

3. Maintain crawlability and indexing hygiene

AI platforms often piggyback on the same crawl infrastructure used by traditional search engines. Meaning, if your content isn’t crawlable, it won’t be seen by anyone.

Here’s a technical health checklist you can follow to avoid that:

• Ensure robots.txt does not block essential content.
• Check noindex or canonical tags that may prevent indexing.
• Submit updated sitemaps regularly to Google Search Console & Bing Webmaster Tools.
• Use clean, descriptive URLs (avoid long query strings or hashbangs).
• Prioritize fast page speed, especially for mobile.

Note: Some platforms like Perplexity AI specifically honor noindex/nocache headers. So, if you want to be cited, make sure you’re not unintentionally blocking crawling.

4. Optimize for vectorized search and embeddings

Generative engines like ChatGPT or Perplexity often rely on embedding models rather than traditional keyword matching. This means they’re looking for semantic meaning, not just matching terms.

Here’s what can help you:

• Topical coherence: Use natural language consistently within a page.
• Clear entity linking: Mention brand names, locations, people, etc., clearly and consistently.
• Contextual repetition: Don’t be afraid to reiterate key ideas with variation — it helps reinforce meaning in embedding space.
• Glossaries or internal definitions: Help disambiguate terminology for AI agents.

Bonus: If your brand produces tools, calculators, datasets, or technical documentation, clearly describe their functions. These assets are highly valued by AI systems.

5. Create structured knowledge assets (for LLM use)

While AI Overviews use real-time data, some models are trained on static content snapshots.

You can future-proof your visibility by building content that is:

• Easily scraped and reused
• Stored in knowledge bases
• Linked from public, trusted directories

Also, you should consider creating:

• Glossary pages (high-value for LLM ingestion)
• Public datasets or open-access reports
• Developer docs or open APIs (especially if you’re SaaS or product-based)
• GitHub repos or public code snippets
• Long-form evergreen guides that become source material

These resources can enter LLM datasets (e.g., OpenWebText, Common Crawl), increasing the chance of long-term AI citation.

6. Avoid AI-invisible formats during access control

If your content is locked behind elements that AI can’t parse, it becomes invisible.

So, you should avoid:

• JavaScript rendering without server-side fallback
• Content hidden behind login or paywalls (unless via structured summaries)
• PDFs and image-heavy content with no OCR or alt text
• Dynamic SPAs without SSR (Server-Side Rendering)

Tip: AI agents also struggle with bloated cookie banners, intrusive pop-ups, or auto-play videos. So, keep the UX clean and content-forward.

We followed the above five technical readiness steps for Steam and Sauna Experts, helping them gain top visibility on Google AI Overviews, among others.

Checklist for technical readiness

Let’s start with monitoring

LLM-based search engines don’t yet offer robust analytics. But there are still several manual and semi-automated ways to track where your brand or content is showing up.

You can:

Next up comes tracking (manual + API-based)

Because traditional SEO tools don’t track AI visibility well (yet), many teams are building their own custom dashboards and alert systems.

You can:

Metrics to track (manually or in dashboards)

A. Ecommerce

Product pages are now AI-indexed entities
AI search engines increasingly treat product content as discrete, structured knowledge objects and not just pages with keywords. This means proper schema markup, customer engagement data, and brand context can turn your product pages into AI-citable resources.

Here are some optimization tips for you:

• Product Schema: Add Product schema to include name, brand, SKU, availability, price, etc.
• Review Markup: Use AggregateRating and Review for social proof.
• Customer Q&A: Incorporate a section for commonly asked questions — this fuels “answer-ready” material for generative search.
• Breadcrumb Schema: Helps LLMs understand page hierarchy and product categorization.

For instance, Perplexity AI has been known to cite boutique DTC brands when product content is cleanly structured, includes genuine customer reviews, and answers common buyer questions. So, a skincare brand that includes usage instructions, before-after galleries, and dermatologist quotes in a structured format is more likely to be featured.

B. B2B SaaS

Original insights = Generative engine gold
In the B2B SaaS space, trust and authority are built through unique data, expert positioning, and solution-oriented content. AI engines prioritize pages that demonstrate expertise and provide factual, reusable material.

Here are some optimization tips you can follow:

• Original Research & Data Reports: Publish proprietary studies or usage benchmarks. LLMs love citing unique stats.
• Use Cases & ROI Stories: Structure these with bullet points and subheadings to be answer-extractable.
• Feature Documentation: Include explainer glossaries, API references, and technical FAQs.
• FAQ & HowTo Schema: Wrap your documentation and knowledge base in structured data for deeper AI integration.
• Plugin Potential: ChatGPT and Claude offer plugin/app integrations — if you’re SaaS, consider building AI-compatible tools.

For instance, a CRM platform that publishes annual sales performance benchmarks may find its data quoted inside ChatGPT responses to queries like “What’s the average B2B sales cycle length?” More so if those benchmarks are labeled clearly and accessible to bots like GPTBot or Common Crawl.

C. Healthcare, finance, legal

Regulatory content must be high-trust and expert-led Sectors with high stakes require AI engines to prioritize safety, accuracy, and authority. Google’s AI Overviews are especially cautious in surfacing content in YMYL (Your Money, Your Life) categories. And generative systems tend to follow suit.

Here’s how you can optimize for this sector:

• Author Attribution: Use schema to identify authors’ names, titles, and credentials. Include bios that cite medical, legal, or financial certifications.
• Structured Citations: Back up claims with peer-reviewed sources or government/association data (PubMed, NIH, IRS, SEC, etc.).
• Medical/Legal/Financial Schema: Use MedicalWebPage, LegalService, and FinancialProduct where applicable.
• Compliance Markers: Ensure disclaimers, privacy policies, and terms of service are machine-readable and visibly linked.

For instance, a health clinic blog post written by a licensed physician, properly marked with medical schema, and citing the Mayo Clinic or PubMed, is more likely to be cited. This is particularly true for Google’s AI Overviews and in Perplexity’s sourced answers.

AI search optimization strategy for different sectors

A. Think of AI assistants as the new browsers

From ChatGPT to Siri, and more, AI-powered agents are fast becoming the primary interface between users and the internet. These agents rely on large language models to parse, summarize, and deliver results in natural language

For instance:

• ChatGPT Voice Mode (GPT-4o): Reads summaries of web pages aloud to users, paraphrased in a conversational tone.
• Perplexity on Mobile: Reads out results, citing sources, and allows interactive follow-ups.
• Siri + ChatGPT Integration (iOS 18+): Lets users ask complex queries, with answers generated via OpenAI’s LLMs.

So, the better your content is structured, semantically rich, and factually clear, the higher the chance it will be selected, paraphrased, and spoken by an AI assistant.

B. Know how content is selected, summarized, and voiced

AI agents don’t just list results like Google Search, they synthesize multiple sources and generate a cohesive answer. This answer is often:

• Condensed into ~2–3 key points
• Paraphrased in friendly and neutral tone
• Stripped of sales language or excessive fluff
• Voiced or displayed with citations (depending on platform)

Here’s how you can optimize:

• Use Answer-First Formatting: Begin with a clear, concise answer or summary at the top of your content.
• Use Plain Language: Write in a tone that’s easily understandable when spoken aloud.
• Break Up Long Paragraphs: Short blocks and bullet points are easier for LLMs to convert to audio.
• Avoid Jargon & Legalese (unless required): If you’re in a complex industry (like finance or healthcare), provide plain-language explanations alongside technical terms.
• Incorporate Pronunciation Cues: When relevant, spell out how a term is pronounced (especially for brand names or niche topics).

C. Optimize for zero UI interfaces

Zero UI refers to interfaces where users don’t interact with a screen at all. Instead, they rely on voice, gesture, or background automation.

Think smart speakers, wearable AI assistants, in-car systems, and even embedded agents in operating systems.

These interfaces demand content that is machine-readable, concise, and intent-optimized.

Here are some zero UI optimization strategies:

• Build for Answers, Not Just Pages: Frame content to directly address high-intent queries (“How do I…” “What’s the best way to…”).
• Structured FAQs: Add FAQPage schema and short Q&A blocks throughout your content.
• Embed Micro-Definitions: Define terms clearly inline — don’t assume prior knowledge.
• Create Audio-Friendly CTAs: Instead of “Click here,” use “Visit our website at…” or “Ask us on [platform]…”
• Improve Contextual Redundancy: Repeat key concepts naturally to improve extractability without keyword stuffing.
• Ensure Fast Load & Readability: For mobile-first AI agents, speed and clarity are everything — no bloated scripts or long load times.

Future-proof your content with this checklist

Pro tip: Start creating voice snippets

I suggest you consider creating concise audio versions or voice snippet summaries of your key content. This not only preps your brand for the rise of smart assistants but also increases accessibility and engagement on platforms like YouTube, Spotify, or even ChatGPT with voice enabled.

What is AI search optimization (AIO)?

AIO is the practice of structuring your content so it ranks, appears, or is cited in AI-generated answers across platforms like Google AI Overviews, ChatGPT, Perplexity, and more. It builds upon traditional SEO but focuses on semantic clarity, structured data, and machine-readability.

How do AI engines decide what to cite?

AI platforms prioritize content that is:

• Factually accurate and well-sourced
• Structurally organized with semantic HTML and schema
• Authored by credible sources with expertise
• Easy to extract, summarize, and reuse

Is traditional SEO still relevant?

Absolutely.

Technical SEO, backlink authority, content quality, and user experience still matter. But AIO adds a new dimension, i.e., optimizing for machines that generate answers, not just link listings.

Can ChatGPT or Perplexity read my website?

Yes, if you allow their bots (like GPTBot, ClaudeBot, PerplexityBot) to crawl your content. They extract and process public content for use in answering queries.

Do I need to allow GPTBot to gain visibility?

If you want your content to be cited in ChatGPT or included in LLM training, yes.

You should not block GPTBot. But you can control access via robots.txt and meta tags. Many brands opt to allow crawling but block training, depending on their goals.