In 2020, the average internet user spent just over 5 minutes per session on a search engine—typing a few keywords, skimming a list of links, and clicking through the occasional ad. Fast forward to 2024, and a quiet revolution has taken hold: users are now spending up to 9 minutes per session with AI chatbots, engaged in open-ended, conversational interactions that more closely resemble dialogue than search.

The implications are enormous. This isn't just a shift in user interface—it’s a fundamental reordering of the web’s attention economy.

Search vs. LLMs: The Engagement Curve

Let’s examine the data:

The engagement delta is widening dramatically. In just two years, LLM-based sessions have outpaced traditional search by more than 60% in time spent per session—despite lower overall adoption rates.

Why Are LLMs Winning on Engagement?

1. Multi-Turn Depth
Unlike search engines, LLMs don’t stop at “top results.” They allow iterative refinement:

“What’s the best protein powder?” → “Which is better for women?” → “Any that ship to London?”

This back-and-forth design increases stickiness, capturing the kind of nuanced behavior that search engines once ignored.

2. Less Friction, More Personalization
Traditional search involves multiple steps: scan results, click, bounce, repeat. LLMs synthesize answers in-line, cutting the cognitive load and making it feel more like an assistant than a tool.

3. Product Research Has Moved
Recent studies show 60% of U.S. adults used an AI chatbot for product research in the last 30 days. Not only are users spending more time—but they’re closer to purchase intent than ever before.

Commercial Implications: Where Search Loses, LLMs Monetize

Search engines monetize clicks — and are losing them.
LLMs monetize trust — via embedded recommendations, product summaries, affiliate models, or native transactions (as seen with Amazon Rufus and Walmart’s Cosmo).

As more product research and decision-making migrates into LLM interfaces, the brands that adapt their visibility strategies to LLM-native ecosystems will be the ones who dominate tomorrow's marketplaces.

It's Not About Replacement—It’s a New Layer of the Stack

Just as mobile didn’t kill desktop, LLMs won’t fully kill search. But they are becoming the first stop for a growing number of use cases:

Product discovery
Health queries
Travel planning
Financial education
Learning & tutoring

Search remains a utility. LLMs are becoming a destination.

Where Do We Go From Here?

To compete in an LLM-first world, brands and platforms must:

Engineer for AI Visibility: Optimize how your brand appears in ChatGPT, Claude, Rufus, and Cosmo—not just in Google.
Measure Engagement Differently: Track conversational dwell time, multi-turn sequences, and assistant interactions.
Reimagine SEO: Use structured content, fine-tuned summaries, FAQs, and conversational metadata to train LLMs on your brand’s value.
Get Embedded: Push toward native integrations with assistants through APIs, plug-ins, and fine-tuned models.

Final Word

The web used to be a list of links. Now it’s a conversation.

And the more time people spend inside these AI agents, the less time they spend jumping between tabs and distractions. LLMs are capturing attention, trust, and transactions in a way search never could.

This is not just a UX shift. It’s a platform shift.

If your brand isn't visible inside the AI conversation, you're invisible.

From Queries to Conversations: How LLMs Are Redefining User Engagement