GEO and AI: How Brands Are Shifting Their Strategies
As buyers research through ChatGPT and Perplexity, brands are shifting from ranking pages to being cited in AI answers. Here is how their strategies are changing.
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Brands are shifting from optimizing for search rankings to optimizing for AI answers. As buyers ask ChatGPT, Perplexity, and Google AI Overviews for shortlists, the goal moves from ranking a page to becoming the source those models cite. That shift, from SEO alone to generative engine optimization (GEO), is the biggest change in B2B marketing strategy right now. Corbelix is a generative engine optimization agency for B2B SaaS and established brands.
Here are the specific ways brands are changing how they work, and what is worth copying.
From ranking pages to being cited in answers
The old goal was a ranked page that earns a click. The new goal is being part of the synthesized answer a model gives before the buyer clicks anything. Brands are learning that ranking and being cited are related but different jobs, and are budgeting for both.
The pressure is real: in early 2024, Gartner predicted that traditional search engine volume would drop 25% by 2026 as buyers shift to AI assistants. Whether or not that exact number lands, the direction is clear, and research from Gartner and Forrester already puts the share of the B2B buying journey completed before a buyer contacts sales at roughly 70% to 80%.
For the underlying difference, see our breakdown of GEO vs SEO and how AI answers are assembled in our guide to generative engine optimization.
From keywords to entities and questions
Keyword lists are giving way to entity clarity. Brands are making their name, category, and description consistent everywhere, adding structured data, and publishing content that answers the exact questions buyers ask an AI. Clear, quotable answers beat keyword-stuffed pages, because models lift clean statements, not density.
- Consistent entity data and schema across the site and profiles
- Question-style pages that lead with a direct answer
- An llms.txt file that summarizes the business for AI crawlers
From content volume to corroboration
The biggest strategic change is realizing that content on your own site is not enough. Models weigh agreement across independent sources, so brands are investing in earned signals: digital PR, genuine presence in communities, and reviews. What third parties say now carries more weight than another blog post.
To see where the gaps are, brands start with an AI visibility audit and then close them at the source.
From one-off campaigns to compounding authority
Finally, brands are treating this as an ongoing system rather than a campaign, because AI citations compound: each corroborating source makes the next one likelier. Starting earlier widens the gap. For a realistic timeline, see how long GEO takes to work, and for what a program includes, what a GEO agency actually does.
If you want to see where your brand stands today, run our free AI readiness grader or book a strategy session.
Key takeaways
- Brands are shifting from ranking pages to being cited in AI answers.
- Entity clarity, structured data, and question-style content are replacing keyword lists.
- Corroboration from PR, communities, and reviews now outweighs more owned content.
- AI share of voice is becoming a tracked, board-level metric.
- The work is treated as a compounding system, not a one-off campaign.
Frequently asked questions
How is AI changing brand marketing strategy?
Buyers increasingly ask AI engines like ChatGPT and Perplexity for shortlists before visiting websites, so brands are shifting from ranking pages to becoming the sources those models cite. That means investing in entity clarity, structured data, clear answers, and third-party corroboration.
What is GEO and how does it differ from SEO?
Generative engine optimization (GEO) aims to get your brand cited inside AI-generated answers, while SEO aims to rank pages in search results. GEO depends more on clarity, consistent entity data, and corroboration across trusted sources than on any single ranking signal.
What should brands do first to adapt?
Start with an audit of how AI engines currently describe you, fix inaccuracies and entity data, publish clear answers to real buyer questions, and build corroboration through digital PR, communities, and reviews. Then track your AI share of voice over time.
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