Why marketers must factor large language models into their playbook

Marketing has changed dramatically. Ask a Gen Z consumer when they last googled something and clicked through five articles for an answer, and you’ll get a blank stare. Today, they go straight to a preferred Large Language Model (LLM), ask a question, and get an instant answer.

A recent Semrush survey predicts that by 2028, LLMs will drive nearly 75% of brand revenue. A visitor from ChatGPT is 4.4 times more likely to convert than one from Google, making LLM traffic far more valuable than search engines.

This is the new search engine, one that doesn’t index content but interprets it. And that subtle shift changes everything for marketers.

The big shift: From indexing to interpretation

Traditional search crawled pages, indexed keywords, and rewarded authority. Marketers played to that system with SEO checklists, backlinks, and keyword-rich titles.

LLMs don’t crawl the web in real time. They train on large datasets, structured content, user input, and credible sources. They don’t “find” your site; they remember what they’ve been taught. And when asked, “Is a brand trustworthy?” they don’t return links; they tell a story based on training.

That’s not a search engine. That’s a storyteller, telling your story, with or without you. So, LLMs don’t index in the traditional way; they interpret.

What’s changing (and disappearing)

Organic SEO as discovery – Traffic from non-branded keywords is already plummeting in sectors like e-commerce, B2B SaaS, and local services.

Click-based journeys – People no longer need to click five links to compare options. LLMs summarise reviews, testimonials, and specs instantly.

Ranking-focused content – Long keyword-optimised guides add little if a model has already seen the data.

Brand invisibility – If your content isn’t structured, referenced, or clear, LLMs may not surface it, or worse, they may hallucinate misinformation.

The first impression now belongs to the model, not your website.

What brands must do now

Publish human-valuable, machine-readable content – Focus on clarity and structure with schema markup, product specs, and FAQs. LLMs love clarity.

Be present where models look – Build high-authority mentions, verified knowledge graphs, and consistent brand narratives across properties.

Monitor model output – Regularly ask ChatGPT, Claude, and Gemini what they “know” about your brand.

Leverage internal LLMs – Big brands are building proprietary GPTs to serve staff and customers. If you can’t, feed public models better.

Treat brand storytelling as training data – Every case study, review, or explainer is also for the machine.

The future: Branding in the age of machines

You’ve optimised for Google and designed for mobile. Now there’s a new gatekeeper, the model introducing you to your next customer. It doesn’t care about your ad budget; it only knows what it’s been taught.

Teach it well. Because if LLMs are the new interface of the internet, marketers aren’t just creating content anymore; they’re shaping machine memory. And that might be their most important job yet.

(Our guest author, Sapna Desai, is the Chief Marketing Officer at ManipalCigna Health Insurance)