AI Search vs Traditional SEO: What Actually Changed

Traditional SEO has dominated digital marketing for 20 years.

Keywords. Backlinks. Page speed. Meta tags.

It worked because Google's algorithm rewarded these signals.

But AI search engines like ChatGPT, Perplexity, Claude, and Gemini don't work like Google.

They don't rank pages. They cite sources.

And the rules for getting cited are fundamentally different.

The Core Difference

How Google Works (Traditional SEO)

Google crawls your site, indexes pages, and ranks them based on:

1. Relevance — Does the page match the query?
2. Authority — Do other sites link to it?
3. Experience — Is the page fast, mobile-friendly, and safe?

You optimize by:

• Targeting keywords with search volume
• Building backlinks
• Improving Core Web Vitals
• Writing long-form content

Success = ranking higher than competitors for target keywords.

How AI Search Works

AI assistants don't return a list of links. They generate answers.

When a user asks ChatGPT "What's the best CRM for startups?", it:

1. Retrieves relevant content (from training data or live search)
2. Extracts factual claims from that content
3. Synthesizes a response
4. Optionally cites sources

Your content either gets pulled into that synthesis, or it doesn't.

There's no page 2. No gradual ranking improvement. You're either cited or invisible.

What AI Looks For (That Google Doesn't)

1. Extractable Claims

Google can rank a page with fluffy marketing copy if it has good backlinks.

AI can't cite fluff. It needs statements it can extract and repeat.

❌ "We help companies achieve their full potential."

✅ "Reduces customer onboarding time by 40% based on 200+ deployments."

The second one can be cited. The first cannot.

→ Read more: Your Website Says Nothing AI Can Use

2. Semantic Completeness

Google doesn't care if you mention "SOC 2 compliance" or "GDPR" on your homepage.

AI does. When evaluating whether to cite you, AI looks for the concepts it expects in your category. Missing expected concepts = lower trust = no citation.

→ How we measure this: Semantic Coverage

3. Entity Signals

Google trusts backlinks as authority signals.

AI trusts entity signals: customer logos, analyst mentions, certifications, case studies with real names.

If AI can't verify your claims through recognized entities, it's less likely to cite you.

4. Content Clarity

Google can rank pages with buried information if the overall SEO is strong.

AI struggles with ambiguity. If your pricing is hidden, your features are vague, or your value prop requires interpretation, AI will cite a competitor who was clearer.

What Still Matters for Both

Not everything changed. These factors help in both paradigms:

What to Do About It

If you're starting from zero

Focus on AI search first. The requirements are stricter, and meeting them will also improve your traditional SEO.

1. Make every key claim specific and extractable
2. Cover the semantic concepts your category requires
3. Add entity signals (customers, certifications, integrations)
4. Structure content with clear headings and schema markup

If you already have strong SEO

Audit your content for AI extractability. Ask:

• Can AI quote specific facts from your pages?
• Do you cover the concepts AI expects?
• Are your claims backed by verifiable signals?

Use the AI Search Check to see how AI currently perceives your content.

The Bottom Line

Traditional SEO optimizes for algorithms.

AI search requires content that can be understood, extracted, and cited.

Both matter. But the skills are different.

Companies that adapt early will own the AI search results in their category. Everyone else will wonder why their traffic dropped despite "good SEO."

See How Real Companies Score

We analyze AI visibility for leading SaaS companies:

• Gong: 86.4 AI Visibility Score
• Loom: 76.9 AI Visibility Score
• Basecamp: 71.2 AI Visibility Score

Want your site analyzed? Request an AI Visibility Analysis.