Everyone’s talking about AI search right now, and for good reason. Generative engines have some of the highest rates of consumer adoption in the history of technology. They've created a tectonic shift in how people find information and how brands get discovered.
Large language models generate answers, offer opinions, and make recommendations in context. Being discovered in AI means understanding that LLMs differ from traditional search engines. Here’s how:
- AI generates answers, it doesn’t retrieve them
- AI search is conversational, not keyword-driven
- AI search is probabilistic (varied answers), not deterministic (fixed results)
- AI search recommends brands with context, rather than ranking them by links
- AI search is fragmented, not monopolized
What does this mean for the marketer trying to build their brand in AI discovery?
You’re shaping perception, not just optimizing pages. LLM’s don’t just scan your website. They synthesize everything ever said about your brand across the web: press, reviews, blog posts, forums, partnerships, social media, influencers, and more.
Brand narrative is your new keyword strategy. LLMs reward consistency. When your brand pillars show up in PR, blog posts, thought leadership, influencer content, and even customer reviews using similar language, models are more likely to confidently recommend you.
Owned and earned media are now inseparable. AEO/GEO/AIO blurs the line between what you publish and what others say about you. To influence AI outputs, your messaging needs to extend across both.
Distribution becomes the differentiator. It’s not just what you say, it’s how often and where it shows up. LLMs trust repetition from authoritative sources.
The job isn’t to optimize for an algorithm anymore, it’s to educate AI about your brand by being authentic, authoritative, and consistent.
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