27-Feb-2026
Is Google dead because of AI?
AI changed how people begin research, not whether they search. The real AI impact on search behavior is a shift toward fewer generic clicks and more branded, high-intent queries.
Buyers now learn through feeds, AI answers, and social content before heading to Google to validate vendors. This leads to warmer traffic, stronger conversion rates, and new opportunities to shape how AI represents your brand.
What is the AI impact on search behavior?
AI now handles the simple tasks upfront, which means fewer people click on broad, early-stage queries. But when buyers need to compare vendors, check pricing, or confirm they’re making the right choice, they still turn to Google. The result is lower-intent traffic and a noticeable increase in branded and high-intent searches that lead to stronger conversions.
Is AI changing how people search online?
Yes. But not in the “Google is dead” way marketers typically hear. AI Overviews, zero-click feeds, and answer-first social content give buyers instant clarity earlier in the process. This shifts demand upstream rather than eliminating it.
AI acts like a modern GPS, giving people the first turn before they even open Google. But they still check the road signs — and that’s where search still plays a major role.
During our B2B Growth Show, Rand Fishkin pointed out that when people begin using AI tools, their Google usage actually increases because they use Google to validate what AI suggested. They search more and differently.
The takeaway: your traffic graph may dip, but buyer intent has never been stronger.
What parts of the search journey did AI change?
AI cut down the exploration phase. Those broad “what is…” or “best tools for…” questions get answered without clicking anywhere. People expect the summary first, not the source.
But validation still happens inside Google. Buyers rely on traditional search for:
- comparing solutions
- reviewing case studies
- confirming pricing
- checking integrations
- uncovering “gotchas”
The early-stage meandering — the “paper map” era of searching — has been replaced by a quick GPS-style overview. Buyers get their bearings from AI, then move into validation mode much faster.
As Rand put it, buyers didn’t stop searching. They just stopped clicking on stuff that doesn’t help them.
What you end up with is fewer random searches and more from buyers who already know what they’re trying to find. And honestly, those folks convert better because they’re not starting from scratch.
Where is demand created before search now?
Search is no longer where most people start. Buyers pick up what they need much earlier, in places like:
- LinkedIn carousels
- short-form POV videos
- YouTube explainers
- niche communities
- newsletters
- AI assistants
- dark social conversations
Buyers swipe through insights long before they tap into your site. Rand joked that people love to scroll but hate to click, and content must respect the medium if it hopes to capture attention.
This is why answer-first content wins. If your post requires a click to deliver value, it loses to someone who gave the takeaway upfront.
Brand memory > algorithm manipulation.
What is Language Model Optimization (LMO) and why does it matter?
SEO alone isn’t enough in an AI-shaped world. To influence how models describe your brand, you need LMO: the practice of shaping the data, phrasing, and authority signals AI tools ingest.
Based on Vende’s guidelines and Rand’s insights, strong LMO comes down to answering a handful of critical questions:
How do you create consistent entity language?
Use the same phrasing across bios, directories, partner listings, and conference pages. Rand shared how a single sentence in his bio (“makers of fine audience research software”) influenced how AI classified SparkToro everywhere it appeared.
What types of content do AI models trust?
Citable content: original data, clear definitions, “what is” explainers, and research that’s referenced across multiple sites. AI rewards patterns, not prose.
What expert signals help influence AI?
Real authors, SME commentary, sourced claims, and clear citations. Credibility is a pattern AI recognizes.
Why does structure matter?
LLMs extract information more accurately from FAQ schemas, Q&A sections, tightly structured headings, and one-question-one-answer formatting. This aligns with the LMO best-practice requirement for scannable, chunked sections and question-based headers.
Where should your brand appear for AI to notice?
Podcasts, reputable newsletters, niche publications, and platforms are likely to be scraped into model training datasets.
Think of LMO as making sure your business actually shows up on the map. If AI is the GPS, LMO is how you label your destination clearly so the system can point buyers toward it.
What content formats win with both humans and AI?
Content now requires dual citizenship: it must be readable by humans and extractable by machines.
Strong formats include:
- answer-first articles
- comparison matrices
- benchmark or data studies
- step-by-step implementation guides
- social video → long-form “canonical” pages
These formats satisfy LMO best practices and Yoast’s readability recommendations (short paragraphs, scannable sections, clear transitions).
How should marketers measure success now that clicks are declining?
Traffic is no longer the primary KPI. Views, impressions, and branded demand offer a more accurate picture of influence. Rand emphasized that impressions now correlate more strongly with the pipeline because decisions are being shaped on-platform, before the click even occurs.
Modern KPIs include:
- Branded search volume
- Qualified impressions
- Saves, shares, and replies
- Demo or “talk to an expert” rates
- Pipeline velocity
- Qualitative attribution (“heard about you on LinkedIn,” “ChatGPT recommended you”)
This aligns with Vende's best practices around LMO and content designed for extraction, not just ranking.
What steps can you take in the next 30–60 days?
Here’s a practical, LMO-optimized plan:
- Audit your entity language across all bios and listings.
- Build one answer-first hub for your most frequently searched problem.
- Add three comparison or alternative pages supporting it.
- Publish a mini data study with charts for citation.
- Post one weekly POV video answering a buyer question.
- Add a “How did you hear about us?” field and review with Sales monthly.
These steps are small but have a dramatic impact on AI visibility and branded demand.
Key Takeaways
- People aren’t searching less; they’re just starting in different places before they ever get to Google.
- Since AI handles the quick, easy stuff, the broad “what is…” clicks drop, and the searches you do get tend to be from buyers who already know what they want.
- Google still plays a big role. When buyers want to compare options or double-check information, that’s where they go.
- LMO basically helps AI talk about your brand the right way, the way you want it represented.
- Content that provides a clear answer upfront and is organized in a way that machines can understand is surfaced more often for both humans and AI tools.
- The numbers that matter now look different: branded searches, impressions, and conversions tell you more than raw traffic ever will.
Ready to Lead in the Clickless Future?
Many of the same shifts shaping AI-driven search are also redefining how the modern B2B pipeline is created, as explored in our perspective on the clickless future of B2B demand.
If strengthening your visibility and demand engine is a priority, our team can help you operationalize it.
Contact us to build a search strategy designed for how buyers actually behave today.
