AI-First Search: The NEW SEO Strategy for Google

AI-First Search: SEO Strategy For Google’s Search Generative Experience

AI-first search is rewriting the rules of SEO. Google’s Search Generative Experience (SGE), AI overviews, ChatGPT search, Perplexity, and other AI search engines are shifting clicks away from classic “10 blue links” to AI-generated answers, summaries, and conversational results.

If we keep optimizing only for traditional rankings, we’ll simply feed content into other people’s answers. To win in the age of AI-powered search, we need an AI-first SEO strategy that deliberately targets SGE, AI overviews, and answer engines.

In this guide we wrote in Divramis SEO Agency, we’ll break down what AI-first search and AI-first SEO actually are, how Google AI search changes user behavior and ranking factors, and how we can prepare our websites for AI search engines, today, not “someday.”

Understanding AI-First Search And Search Generative Experience (SGE)

What Is AI-First Search?

AI-first search is a search experience where large language models (LLMs) and generative AI sit at the center of how results are generated, ordered, and presented.

Instead of only matching keywords to documents, AI-first search:

• Interprets intent and context behind the query.
• Synthesizes information from multiple sources.
• Produces AI-generated answers, overviews, and conversations.

Google AI search is moving in this direction with AI overviews and SGE-like experiences, while tools like ChatGPT search and Perplexity AI search are born as AI-first search engines. For us as SEOs, this means our goal isn’t just “rank a URL” but be cited, summarized, and surfaced inside AI-driven search results.

What Is Google’s Search Generative Experience (SGE)?

Google’s Search Generative Experience (SGE) is Google’s term for integrating generative AI into search results. Instead of just showing a list of links, SGE can:

• Display an AI-generated overview at the top of the SERP.
• Pull in key facts, lists, and comparisons.
• Cite a small set of source pages as cards or links.
• Invite users to continue the search as a conversation.

Even as branding shifts (“AI overviews” and experiments inside Search Labs), the underlying idea remains: Google AI search uses generative models to answer first and list second.

For SEO, this creates a new battlefield:

• We still want strong organic rankings.
• But we also want our site to be one of the few sources chosen inside SGE and AI-generated results.

How Large Language Models (LLMs) Understand And Use Your Content

LLMs (like the ones powering Google AI, ChatGPT, and other AI search engines) don’t “index keywords” the way classic search engines do. They:

• Convert text into vectors that encode meaning and relationships.
• Learn patterns, concepts, and entities (brands, people, products, places).
• Generate new text by predicting what’s most likely to be useful and coherent.

In practice, that means:

• Clear semantic structure (headings, lists, tables) helps them segment and reuse your content.
• Strong entity-based SEO (consistent naming, context, schema) helps them associate your brand with topics.
• High-quality, unambiguous explanations are more likely to be quoted in AI-generated answers.

AI-first SEO, then, is about feeding LLMs content that’s:

1. Accurate and trustworthy.
2. Easy to parse and summarize.
3. Clearly associated with specific entities, topics, and intents.

From Traditional SEO To AI-First SEO

Traditional Ranking vs. Answer Generation And Zero-Click Experiences

Traditional SEO revolved around:

• Keyword research and on-page optimization.
• Backlinks as the primary off-page signal.
• Tracking blue-link rankings and organic sessions.

AI-first search adds a new layer:

• Answer generation: the AI composes summaries and answers from multiple pages.
• Zero-click searches: users often get what they need directly in the SERP or AI chat.
• SERP participation vs. ownership: a single answer may represent dozens of sources, but only a handful get visible attribution.

So we’re no longer fighting purely for position #1. We’re fighting to participate in the answer and to remain visible when results become zero-click.

AI Search Engines Beyond Google: ChatGPT, Perplexity, And Others

Google isn’t alone. AI search engines like:

• ChatGPT search (with browsing and plugins).
• Perplexity AI search.
• You.com and others.

…are building interfaces where the primary output is a generated answer, not a list of links. These tools still cite sources, but usually just a few.

For us, that means an AI search visibility strategy has to look beyond Google:

• Are we being cited in ChatGPT or Perplexity answers?
• Do those answers mention our brand and link back?
• Is our content structured so LLMs can easily reuse it?

How AI Changes The Role Of Keywords, Links, And Rankings

AI-first search doesn’t kill keywords and links, but it does change how they work:

• Keywords shift from exact-match phrases to intent signals and long-tail, conversational queries.
• Links remain important as trust and authority signals, but content can influence AI-generated answers even if it’s not ranking #1.
• Rankings become one of several layers: classic rankings, AI overviews, People Also Ask, video carousels, etc.

In AI vs traditional SEO, we’re not abandoning old fundamentals. We’re layering on AI search optimization, making sure content is:

• Mapped to search intent.
• Structured for machine understanding.
• Positioned as a credible source for AI-generated results.

How AI-Driven Search Changes Google’s Results And User Behavior

E-E-A-T And Trust Signals In The Age Of AI

As AI-generated results spread, the risk of hallucinations and misinformation grows. Google’s response has been to double down on E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).

In practical terms, Google AI ranking factors increasingly include:

• Clear author identity and credentials.
• Brand reputation signals (mentions, reviews, authority links).
• Transparent sources, citations, and external references.
• Safe, compliant content (especially for YMYL topics).

AI-first SEO means we don’t just write “helpful content”, we prove why we’re trusted. Agencies like Divramis SEO Agency Greece, for example, lean on long-term case studies, client results, and years of specialization as strong E-E-A-T signals.

Semantic Search, Entities, And Topic Authority

AI-powered search is deeply semantic and entity-based. Google AI search and other LLMs rely on knowledge graphs and entity embeddings to understand:

• Who you are (brand, organization, person).
• What you offer (products, services, topics).
• How you relate to other entities in your niche.

To build topic authority in an AI-first world, we need to:

• Cover key topics in depth, not with one shallow page.
• Connect related content via internal links and hub pages.
• Use schema markup to explicitly describe entities, relationships, and attributes.

This is where SEO beyond traditional rankings starts: we’re optimizing not only for pages, but for how the entire site is represented in the AI’s internal knowledge graph.

Core Principles Of AI-First SEO

User-First, Intent-Driven Content As The New Baseline

In SEO in the age of AI, “write for users, not for search engines” finally becomes literal. AI models are trained on what users find valuable, not just on keyword-stuffed pages.

Core principles of an AI-first SEO strategy for Google and other AI search engines:

Intent over keywords

Every page should be built around a clearly defined search intent: informational, commercial, transactional, or navigational. We then support that intent with semantic variants and natural language questions.

Depth over breadth

AI prefers rich, complete explanations it can quote. Thin content rarely makes it into AI overviews.

Clarity over cleverness

Simple language, clear headings, and modular sections make it easier for LLMs to extract precise answers.

Evidence over claims

Case studies, data, screenshots, and real examples signal reliability, crucial for being chosen in AI-generated answers.

Design for humans, structure for machines

We design experiences users love, but we structure HTML, headings, schema, and internal links so that AI systems can fully understand and reuse our content.

Optimizing Content For AI Search, SGE, And Answer Engines

Designing Content For AI Summaries, Overviews, And Conversations

To optimize content for AI search engines and Google SGE, we should assume our pages will be partially read by users and heavily read by machines.

Content patterns that work extremely well for AI summaries:

• Concise definitions at the top of sections (

“What is…”, “How does… work?”).

• Step-by-step lists and frameworks.
• Pros/cons, comparison tables, and FAQs.

When we write, we should imagine a user will ask follow-up questions in a chat. A good AI-first SEO content piece anticipates those questions in:

• Subheadings (H2/H3) mirroring natural language queries.
• Short Q&A blocks.
• Clear transitions between related subtopics.

Answer Engine Optimization (AEO) And Generative Engine Optimization (GEO)

Answer Engine Optimization (AEO) focuses on earning visibility inside answer boxes, featured snippets, People Also Ask, and now AI overviews and SGE.

Generative Engine Optimization (GEO) is the broader discipline of optimizing for generative AI outputs across Google, ChatGPT, Perplexity, and similar systems.

Key AEO / GEO tactics:

• Target question-style queries (who, what, why, how, when) and provide direct, concise answers.
• Use schema markup (FAQPage, HowTo, Product, Organization, Article) to make Q&A and steps machine-readable.
• Provide original insights (unique data, methodology, local expertise) that make your answers more “quotable.”

Structuring Pages For Scannability And Snippet-Worthy Answers

SGE and AI overviews often pull text from blocks that look like ready-made snippets. We can help them by structuring pages like this:

• One clear H1 matching the primary intent (e.g., “AI-First Search SEO Strategy For Google AI Search”).
• Logical H2/H3 hierarchy reflecting user questions.
• Short paragraphs (2–4 lines) and frequent bulleted or numbered lists.
• Highlighted key takeaways or “In short” sections.

From a human perspective, this boosts readability. From an AI perspective, it creates bite-sized, self-contained chunks that are perfect for ranking in AI-generated answers.

Technical Foundations For AI Search Optimization

Using Schema Markup And Structured Data To Feed AI

If AI models are the new “readers,” schema markup is our way of speaking their native language. Structured data helps both Google’s traditional ranking systems and AI layers:

• Clarify entities (Organization, Person, Product, Service, LocalBusiness).
• Mark up content types (Article, BlogPosting, FAQPage, HowTo, Event, Course).
• Provide attributes (price, rating, availability, address, operating hours).

For AI-first SEO, we consistently:

• Carry out and validate schema across key templates.
• Use Organization markup to reinforce brand identity and NAP consistency.
• Mark up FAQs, how-tos, and product data to maximize visibility in SGE and rich results.

Site Architecture, Internal Linking, And Crawlability For AI Discovery

AI can’t use what it can’t discover or crawl. A solid technical base still matters:

• Clean architecture: logical categories, no deep or orphaned pages.
• Meaningful internal links: connecting related topics with descriptive anchor text, strengthening topic clusters and entity associations.
• XML sitemaps and correct robots.txt directives: ensuring important content is easily discoverable.

In an AI-first search world, strong internal linking also shapes how your domain appears in semantic search and knowledge graphs. It tells Google AI which topics you’re genuinely authoritative on.

Speed, UX, And Engagement Signals As Reinforcing Ranking Factors

AI doesn’t ignore classic user experience signals. Google’s systems still rely on:

• Core Web Vitals and mobile performance.
• Mobile-first design (something agencies like Divramis SEO Agency Greece have adopted for years).
• On-page engagement signals: dwell time, pogo-sticking, interaction.

Faster, smoother sites tend to:

• Rank better in traditional SERPs.
• Be perceived as higher quality sources by AI layers.
• Generate more positive user signals that reinforce your authority over time.

Strategies To Earn Visibility In AI-Generated Answers And Overviews

Practical Tactics To Appear In SGE And AI Overviews

To deliberately appear in Google AI search overviews and SGE-style results, we can:

Target “overview-friendly” topics

Comprehensive guides, comparisons, and explainers are more likely to be used as sources.

Own subtopics completely

Build topic clusters around key entities (e.g., “AI-first SEO,” “Google AI search,” “search generative experience”). Cover definitions, how-tos, tools, and FAQs.

Optimize for featured snippets and People Also Ask

Pages that already win these surfaces are natural candidates for SGE citations.

Use clear attributions within content

Phrases like “According to our 2024 data…” or “In our experience optimizing Greek eCommerce sites…” help AI recognize source-specific insights.

Long-Tail, Conversational, And Context-Rich Queries

AI-first search massively expands the importance of long-tail queries and conversational language:

• Users phrase queries as full questions or multi-part prompts.
• Follow-up questions in chat keep refining context.

Our keyword research and content planning should hence focus on:

• Question clusters around a core topic (“how AI-first search changes SEO”, “how to optimize for Google AI search”).
• Modifiers like “for small businesses,” “in Greece,” “for eCommerce,” “in 2025” to catch context-rich queries.
• Natural language phrasing directly reflected in headings and FAQs.

Entity-Based SEO For Brand And Topic Visibility

In AI-first SEO, brand visibility isn’t just about branded keywords. It’s about being recognized as a relevant entity whenever AI discusses your niche.

Entity-based tactics include:

• Ensuring consistent brand name, address, and descriptions across the web.
• Building high-quality mentions and links from authoritative sites in your vertical.
• Publishing content that repeatedly associates your brand with core topics (e.g., AI-first search, technical SEO, WordPress SEO, mobile-first design).

For example, when Divramis SEO Agency Greece appears across Greek and international SEO discussions as a specialist in WordPress and mobile-first SEO, AI systems start to connect that brand entity with those specific competencies. That increases the chance of being cited when AI-generated results talk about those subjects.

Measuring Performance In An AI-First Search World

Tracking Visibility In AI Overviews, Chatbots, And Zero-Click SERPs

Classic rank trackers won’t tell us whether we show up in AI overviews, SGE, or ChatGPT-style answers. We need new methods:

• Manual SERP sampling: regularly testing priority queries in Google and noting when our pages are cited in AI overviews.
• Using SEO tools that detect SGE or generative results and track when a domain appears as a cited source.
• Monitoring referral traffic from AI search engines where possible (e.g., Perplexity links).

We should also watch for an increase in brand queries and direct traffic. As more users discover us via AI-generated answers, they may search our brand directly next time.

New KPIs: Beyond Sessions And “Blue Link” Rankings

In an AI-first search environment, our KPI mix needs to evolve. Alongside classic metrics, we track:

• Share of voice on key topics (how often we appear vs. competitors in SERPs and AI overviews).
• Citation frequency in AI-generated answers (qualitative, but extremely valuable).
• Engagement depth (scroll depth, time on page, conversion rate) from organic traffic we do receive.
• Growth in entity-level signals (mentions, reviews, knowledge panel improvements).

The goal of SEO for AI search engines isn’t only raw traffic, it’s topic ownership and brand inclusion wherever AI explains our space.

Adapting Analytics, Attribution, And Reporting For AI-First Search

Reporting must reflect this new reality. In our dashboards, we:

• Segment organic traffic by query intent (AI-related, informational, commercial, branded).
• Add custom notes when we observe new SGE appearances or AI overview citations.
• Create topic-level reports showing how clusters (like “AI-first SEO” or “semantic search”) perform as a whole.

We also educate stakeholders that zero-click searches and AI-generated answers don’t necessarily mean SEO is “failing.” In many cases, we’re building brand awareness and influence even when the user doesn’t click immediately.

Roadmap: Preparing Your SEO Strategy For The Future Of Google AI Search

Assessing Your Current SEO Through An AI-First Lens

To move toward an AI-first SEO strategy for Google and beyond, we start with a brutally honest assessment:

• Content: Do we have comprehensive, intent-driven content for our core topics, or just thin landing pages?
• Entities: Is our brand clearly defined with schema and consistent external profiles?
• Technical base: Is our site fast, mobile-first, well-structured, and easily crawlable?
• Authority: Do we have credible links, reviews, and case studies that support E-E-A-T?

An AI-first audit looks at all of this, plus:

• How well our content maps to question-based and conversational queries.
• Whether we already appear in featured snippets, People Also Ask, or AI-like features.

Prioritizing Quick Wins vs. Long-Term AI Search Investments

We don’t need to rebuild everything overnight. We can phase changes:

Quick wins (0–3 months)

• Update top-performing pages with clear definitions, FAQs, and snippet-friendly sections.
• Carry out or fix core schema markup (Organization, Article, FAQPage, Product, LocalBusiness).
• Improve internal links for key topic clusters.

Medium term (3–9 months)

• Create or expand pillar pages around strategic topics like “AI-first SEO,” “Google AI search,” or your main services.
• Optimize for long-tail and conversational queries in key markets (e.g., SEO services in Greece, eCommerce SEO, etc.).
• Systematically improve page speed and UX.

Long term (9–24 months)

• Build out full content ecosystems (blog, case studies, tools, glossaries) around your niche.
• Strengthen off-site authority: PR, partnerships, thought leadership.
• Continuously adapt content as AI search engines evolve.

Agencies like Divramis SEO Agency Greece already follow similar phased roadmaps combining web design, technical SEO, and content so sites are “SEO by design” and future-proofed for AI.

Building An Ongoing Testing, Learning, And Optimization Cycle

AI search is changing fast. The only sustainable strategy is to treat AI-first SEO as an ongoing experimentation loop:

Hypothesize

For example: “Adding structured FAQs to our AI-search-focused pages will increase SGE citations.”

Carry out

Roll out changes on a controlled set of priority pages.

Measure

Track rankings, SERP features, SGE/AI overview presence, engagement, and conversions.

Refine

Keep what works, adjust what doesn’t, and roll wins out to more pages.

Instead of guessing how AI-first search will look in five years, we build a system that adapts every quarter. That’s the real future of SEO in the age of AI.

Conclusion

AI-first search isn’t a distant future, it’s already here in Google AI search, SGE-like experiences, ChatGPT, Perplexity, and other AI-powered search tools. The cost of ignoring it is simple: our content will keep fueling someone else’s answer while our brand stays invisible.

If we embrace AI-first SEO, we can:

• Align content with user intent and conversational queries.
• Structure pages and schema so that LLMs can easily understand and reuse our work.
• Strengthen E-E-A-T, entities, and topic authority so Google AI trusts us as a source.
• Measure success not just by rankings, but by our presence inside AI-generated answers and overviews.

Whether we handle this in-house or partner with a specialist agency like Divramis SEO Agency, the key is to start now. Audit our site through an AI-first lens, prioritize quick wins, and commit to a continuous cycle of testing and optimization.

SEO in the age of AI belongs to brands that don’t just chase algorithms, they design content and experiences for the way humans ask questions and the way AI understands answers.

 

AI-First Search & SGE: Frequently Asked Questions

What is AI-first search and how is it different from traditional search?

AI-first search is a search experience where large language models and generative AI sit at the center of how results are created. Instead of only matching keywords to documents, AI-first search interprets intent, synthesizes multiple sources, and returns AI-generated answers, overviews, and conversational results before showing full lists of links.

What is Google’s Search Generative Experience (SGE) in SEO?

Google’s Search Generative Experience (SGE) is the integration of generative AI directly into search results. It can display AI-generated overviews at the top of the SERP, pull key facts and comparisons, cite a small number of source pages, and invite follow-up questions, turning search into an interactive conversation.

How does AI-first SEO change the way I should optimize my content?

AI-first SEO shifts focus from ranking a single URL to being cited inside AI overviews and answer engines. Content must be intent-driven, deeply informative, clearly structured, and supported by strong entity and schema markup so LLMs can easily understand, segment, and reuse your explanations in AI-generated results.

Does AI-first search mean keywords and backlinks no longer matter?

No. In AI-first search, keywords and backlinks still matter but play a different role. Keywords act more as intent and topic signals than exact matches, while links remain crucial trust and authority indicators. These classic signals now support your chances of being selected as a credible source for AI-generated answers.

How can I optimize my site specifically for Google AI search and SGE?

To optimize for Google AI search and SGE, create comprehensive, intent-aligned pages with concise definitions, step-by-step lists, and FAQs. Use schema markup (FAQPage, HowTo, Organization, Article), strengthen internal links around topic clusters, highlight original data or case studies, and aim to win featured snippets and People Also Ask boxes first.

How do I measure SEO performance in an AI-first search environment?

In AI-first SEO, you still track rankings and organic traffic, but add new KPIs: presence in AI overviews and SGE, how often your domain is cited as a source, share of voice on priority topics, engagement depth from organic visitors, and growth in entity-level signals like mentions, reviews, and knowledge panel improvements.

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I am Yannis Divramis, I am a SEO Expert. I have been doing SEO since 2013.

I run the Divramis SEO Agency  and I am very glad that you’ve watched this video and keep watching the other videos, because we are posting every month many videos about SEO.

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