The channel strategy that's saving brands from AI search cannibalization
Picture this: Content visibility is up, but traffic to your website is way down. More than half of Google searches today end in no clicks, according to Search Engine Land. And consumers are looking everywhere — from Google’s AI Overviews to Reddit — for instant solutions to fit their needs.
Is this your reality? Welcome to the rebirth of how people find information.
Payoffs from traditional SEO tactics used to be huge. Now, AI has effectively given everyone access to unlimited, personalized knowledge on a diverse set of channels, and Google Search is losing users to AI search engines like ChatGPT.
The once reliable marketing playbook has officially been disrupted. You can no longer count on one distribution channel, like search, to do all of the work for you. As a brand, you need to diversify your content across channels to meet buyers where they are.
With the rise in AI adoption, one of those channels is AI search. When your audience is finding information in large language models (LLMs), it’s time to optimize your content strategy for both humans and machines.
The Scoop on AI Engine Optimization (AEO)
AI usage has been increasing since 2023. A recent McKinsey survey found that 78% of organizations used AI in at least one business function in 2024, compared to 55% the year prior. This widespread adoption is fundamentally changing how people consume information.
As Google and other search engines roll out more AI features, businesses are facing a unique paradox: they’re seeing fewer clicks even if their rankings and impressions improve. That’s because AI engines are increasingly becoming the first stop for product discovery.
It is worth noting, however, that the buyer’s journey hasn’t changed. Users still identify a pain point, determine a solution, find the right product for that solution, and ultimately make a purchase. But the channels guiding those steps have, and AI search is shaping the first three phases more and more.
Traditional SEO focused on surfacing the best resources through search engine results pages (SERPs). Content was designed to address simplified search queries, where users make multiple search attempts and perform manual research to compare results.
But AEO prioritizes surfacing the best answers directly through LLMs. This means developing content that satisfies specific, natural language queries, where users learn from the AI engine and ask conversational follow-up questions.
Succeeding in the AEO environment depends on two things: choosing the right topics and designing content with intent.
Choosing the Right Topics
AI engines rely on vector embeddings to understand the relationships between words, concepts, and entities. This means that brands need to build strong semantic associations between their content and the product categories they want to own.
For example, a project management software company should target keywords beyond “project management tools” and create depth across related topics such as “resource allocation,” “workflow automation,” and “team collaboration best practices.” That way, AI engines can begin to associate the brand with the entire …read more
Source:: HubSpot Blog
