search
For decades, Google has been the front door to the internet. If you wanted information, you “Googled it.” Marketers built strategies around keywords, backlinks, SERP features, mobile indexing, and content clusters. The playbook was known and kinda predictable.
But now a new search layer is emerging — AI search — driven by tools like ChatGPT, Perplexity, Claude, Bing Chat, and Brave Answers. These tools don’t return a list of ten blue links. They generate answers, compare products, summarize research, and sometimes even include citations. Users get what they need without browsing five tabs or scrolling through ads.
This shift doesn’t kill Google, but it changes how marketers need to think about discovery, visibility, and content intent. If you rely purely on Google SEO, it’s possible you’re already losing impressions in places you can’t even measure yet.
Let’s break down the key differences between AI search and Google search, and what marketers need to take seriously right now.
1. Query Style: Keywords vs. Natural Language
Google Search is keyword-driven. Users often adapt their query to how search engines “think,” like:
- “best crm tools 2025”
- “how to train for marathon”
- “pricing hubspot vs salesforce”
The user optimizes for the machine, weirdly enough.
AI Search is conversational and natural. Users ask like they would ask a person:
- “What CRM tools are best for a 5-person real estate team?”
- “How do I train for a marathon if I only have 10 weeks?”
- “Can you compare HubSpot and Salesforce pricing and tell me which is better for small companies?”
This means intent is clearer, and context matters more. People aren’t adjusting their language to fit the algorithm — the system adapts to the user.
Marketing takeaway: Content optimized for pure keywords is less valuable than content optimized for questions, context, and explanation.
2. Output Format: Links vs. Answers
This is probably the biggest difference.
- Google returns links → you pick one → then read and interpret.
- AI returns answers → already interpreted, summarized, structured.
Example:
Google query:
“Top email marketing tools”
You get blogs, listicles, ads, maybe some Google Shopping boxes.
Perplexity or ChatGPT query:
“What are the best email marketing tools for small ecommerce brands?”
You get a structured response like:
- Klaviyo → best for ecommerce integration
- Mailchimp → beginner friendly
- Drip → automation heavy
- ConvertKit → creator-focused
Sometimes with pricing, pros, cons, and citations.
This is what marketers need to realize: the click happens after the answer, not before. Often the user may not click at all. So visibility means being part of the answer, not necessarily ranking in the top 3 SERPs.
3. Discovery Logic: Ranking vs. Synthesis
Google uses a ranking model based on:
– backlinks
– authority signals
– entity recognition
– mobile speed and UX
– technical SEO
– keyword relevance
AI search doesn’t rank pages the same way, it synthesizes information from multiple sources and creates a combined answer.
It cares about:
– factual clarity
– domain expertise
– structured data
– first-party information
– semantic relationships
– entity definitions (who/what your brand is)
One high-authority PDF or research page can outweigh 50 SEO blogs because the AI model values signal > volume.
4. User Journey: Research vs. Decision Making
Google search (traditional) excels in navigation and research:
- find products
- read reviews
- explore sites
- skim comparisons
Users jump around between results.
AI search compresses the journey into shorter decision cycles:
- asks one question
- gets structured breakdown
- asks follow-up
- gets a comparison chart
- maybe receives recommendations
It removes friction and organizes information automatically.
For marketers, this means:
- You must provide clear, factual, structured content that AI systems can reuse.
- Vague marketing fluff gets ignored because AI can’t extract facts from it.
5. Metrics: Visible vs. Invisible Performance
Google gives measurable visibility:
– impressions
– CTR
– position
– clicks
– traffic
We have dashboards, Search Console, Ahrefs, Semrush, etc.
AI search doesn’t give marketers direct impression data (yet). When someone asks ChatGPT for “alternatives to HubSpot,” HubSpot doesn’t get an impression count or a click report. But the touchpoint happened.
So we have a new type of invisible attribution emerging. People are discovering brands in systems that don’t have analytics pipelines yet.
This is why many marketers underestimate AI search — because they can’t measure it, so they assume it isn’t happening. Big mistake.
6. Business Model: Ads vs. No (or Low) Ads
Google’s business model = ads + traffic.
AI tools are experimenting with different models:
- subscriptions (ChatGPT Plus, Claude Pro)
- premium features
- enterprise licensing
- API usage
- edge ads (Perplexity is testing ads)
- affiliate recommendations (coming soon to many systems)
So monetization logic is shifting, and discovery could soon follow affiliate-style systems similar to YouTube or TikTok.
7. Brand Visibility: SERP Placement vs. Entity Recognition
In Google SEO, you win by:
- ranking top 3
- capturing snippets
- dominating link real estate
In AI search, you win by:
- being recognized as an entity
- having clear product definitions
- being linked in high-authority knowledge sources
- being included in comparisons
- being cited from trustworthy surfaces
If you’re a SaaS brand not listed on:
- G2
- Capterra
- Wikipedia
- Crunchbase
- GitHub (for dev tools)
you’re practically invisible to LLMs.
So Which One “Matters More”?
Trick question. The reality is:
Google search = distribution engine
AI search = decision engine
Google drives the user to content.
AI informs the user before they even click.
The companies that win over the next decade won’t choose one or the other — they’ll combine both:
– SEO for discoverability
– AI for trust and validation
– Schema and knowledge graphs for machine understanding
– First-party data for authority
Final Thoughts
AI search isn’t here to replace Google, but it’s already changing how people learn, buy, compare, and make decisions. For marketers, ignoring this shift is like ignoring mobile SEO in 2012 or social in 2015 — you can, but it will cost you later.
The key mindset shift is simple:
Traditional SEO optimizes for ranking.
AI search optimization (AISO) optimizes for inclusion.
