All AI Models Use Google Search in 2026

ChatGPT uses SerpAPI (Google is suing them for it). Perplexity uses Google search results. Claude uses Brave Search, which is largely a Google index clone. Every major AI model's web search feature ultimately depends on Google's index. This means optimizing for Google is optimizing for all AI models simultaneously. There is no separate "AI SEO" to do.

The search chain for each model

• ChatGPT: user query to internal search to SerpAPI to Google results to response synthesis
• Perplexity: user query to search to Google/Bing results to response with citations
• Claude: user query to Brave Search (Google-derived index) to response
• Gemini: user query to Google Search directly to AI Overview

Every chain starts with a search engine query and ends with Google's index. The models rewrite your prompt into multiple search queries, retrieve results, and synthesize. If your content does not rank in Google, it does not enter any of these pipelines.

Why this simplifies your strategy

The AEO industry implies you need different optimization for each AI model. In reality, the retrieval layer is shared. A page that ranks #3 on Google for "best CRM for startups" will be retrieved by ChatGPT, Perplexity, and Claude when their users ask about CRMs for startups. Your job is to rank in Google. Full stop.

Tracking your visibility across AI surfaces

import requests, os

H = {"x-api-key": os.environ["SCAVIO_API_KEY"]}

def cross_model_visibility(keyword: str, domain: str):
    """Since all models use Google, check Google ranking + AI Overview."""
    resp = requests.post("https://api.scavio.dev/api/v1/search",
        headers=H,
        json={"query": keyword, "include_ai_overview": True})
    data = resp.json()

    # Organic ranking
    organic_pos = None
    for i, r in enumerate(data.get("organic_results", [])):
        if domain in r.get("link", ""):
            organic_pos = i + 1
            break

    # AI Overview citation
    ai_sources = data.get("ai_overview", {}).get("sources", [])
    ai_cited = any(domain in s.get("link", "") for s in ai_sources)

    return {
        "keyword": keyword,
        "google_rank": organic_pos,
        "ai_overview_cited": ai_cited,
        "implication": "visible to all AI models" if organic_pos and organic_pos <= 10
            else "unlikely to appear in AI responses"
    }

result = cross_model_visibility("best project management tool", "yoursite.com")
print(f"Google rank: #{result['google_rank']}")
print(f"AI Overview cited: {result['ai_overview_cited']}")
print(f"AI model visibility: {result['implication']}")

The one exception

Perplexity and ChatGPT have growing content partnerships and direct crawling programs. If a model has a direct content agreement with a publisher, that content may appear in responses regardless of Google ranking. But for the vast majority of websites, Google ranking remains the gatekeeper. Do not optimize for the exception.

Simple SEO wins that compound across all AI models

• Direct answers in the first paragraph (AEO-friendly and SEO-friendly)
• Structured comparisons with real numbers (easy for models to extract)
• Frequently updated content with dates (freshness signals)
• Comprehensive coverage of subtopics (matches the multiple sub-queries models generate)