September 27th 2025.
Imagine this: You're a business owner and you're seeing a strange trend in your online presence. Your content is getting more visibility, but your website traffic is plummeting. According to Search Engine Land, over half of Google searches now end with no clicks. On top of that, people are turning to places like Google's AI Overviews and Reddit for instant solutions to their problems. Sound familiar? Welcome to the new era of information discovery.
In the past, traditional SEO tactics were the key to success. But now, with the rise of AI, everyone has access to personalized knowledge on a variety of channels. As a result, Google Search is losing users to AI-powered search engines like ChatGPT. This means the old marketing playbook no longer works. You can't rely on one channel, like search, to do all the work for you. As a brand, you need to diversify your content and reach your audience where they are.
With the increasing adoption of AI, one of those places is AI search. When your audience is using large language models to find information, it's time to adapt your content strategy for both humans and machines. HubSpot has some great tips on how to do this.
Let's dive into the world of AI Engine Optimization (AEO). AI usage has been on the rise since 2023, with a recent McKinsey survey showing that 78% of organizations now use AI in at least one business function, compared to 55% the year before. This widespread adoption is completely changing the way people consume information.
As Google and other search engines introduce more AI features, businesses are facing a unique challenge. They may see improvements in their rankings and impressions, but they're also seeing a decrease in clicks. This is because more and more people are turning to AI engines as the first stop for product discovery.
However, it's important to note that the buyer's journey has not changed. Users still identify a problem, search for a solution, and make a purchase. But the channels guiding these steps have changed, and AI search is playing a bigger role in the first three phases.
Traditional SEO used to focus on providing the best resources through search engine results pages. Content was optimized for simple search queries, where users would make multiple attempts and do manual research to compare results. But now, AEO is all about providing the best answers directly through large language models. This means creating content that answers specific, natural language queries and allows users to ask conversational follow-up questions.
Succeeding in the world of AEO depends on two things: choosing the right topics and designing content with intent. Let's break these down.
Choosing the right topics is crucial. AI engines rely on vector embeddings, which means they need strong connections between your content and the product categories you want to be associated with. For example, if you're a project management software company, you should target keywords beyond just "project management tools." Instead, create content that covers related topics like "resource allocation," "workflow automation," and "team collaboration best practices." This way, AI engines can start to associate your brand with the entire product category.
Topic selection is all about claiming a semantic territory and owning it, rather than just chasing after individual keywords. There are three ways to do this:
- Category saturation: Create clusters of content that thoroughly explore a topic category, from basic definitions to advanced use cases.
- Context-rich answers: Addressing nuanced, conversational queries instead of just short, keyword-driven questions.
- Personalization at scale: Create variations of content tailored for different industries, business sizes, or roles. This allows AI engines to provide the most relevant response for each user's context.
AEO rewards breadth and depth of context. The more complete and interconnected your content is, the better AI can understand and recognize it as authoritative.
Designing content with intent is the second key to success in AEO. AI engines prioritize content that is accurate and structured for both human and machine readability. It's all about finding a balance between factual authority, semantic completeness, and structured storytelling.
It's important to include widely accepted information from credible sources, as well as unique insights or data that can't be found elsewhere. For example, a marketing firm could cite widely available data in their "Top Emerging Marketing Trends" article, but also include proprietary findings from their own research team.
Large language models also index and retrieve content in "chunks," so each paragraph or section of your content should be able to stand alone as a complete thought. This ensures that the content can be understood and retrieved without relying on surrounding context.
Entity association is also crucial. Content that clearly identifies and connects entities helps AI engines understand information in context. Writing techniques like using semantic triples make this easier. For example, "The CRM helps sales teams track leads" breaks down into the subject (CRM), the predicate (helps track), and the object (leads).
In today's world, great content alone is not enough to guarantee visibility. To really stand out, brands need a smarter approach to distribution that amplifies their content across the channels where buyers are already paying attention. This is where HubSpot's Loop Marketing playbook comes in, helping businesses evolve as customer habits change.
The Loop has four stages:
- Express who you are: Define your tone, style, and perspective.
- Connect with the right people: Use AI-driven targeting and personalization to reach your audience.
- Build trust and credibility: Provide valuable content and become a thought leader in your industry.
- Amplify your message: Use a combination of traditional and AI-powered distribution channels to reach a wider audience.
In conclusion, the rise of AI has completely changed the game for content visibility and distribution. To succeed, brands need to adapt their content strategy to meet the needs of both humans and machines. This means choosing the right topics and designing content with intent, while also amplifying their message through a mix of traditional and AI-driven channels. Are you ready to embrace the new world of AEO?
Imagine this: You have great content, but your website traffic is decreasing. According to Search Engine Land, more than half of Google searches don't result in clicks. People are turning to various sources like Google's AI Overviews and Reddit for quick solutions to their needs.
Is this happening to you? Welcome to the new era of information discovery. Traditional SEO tactics used to bring in huge returns, but now, AI has opened up unlimited access to personalized knowledge through different channels. As a result, Google Search is losing users to AI search engines like ChatGPT.
The old marketing playbook is no longer reliable. Relying on one distribution channel, such as search, is no longer enough. Brands need to diversify their content across channels to reach their target audience.
With the growing adoption of AI, one of those channels is AI search. When people are searching for information using large language models, it's time for brands to optimize their content strategy for both humans and machines. HubSpot explains this further.
The Rise of AI Engine Optimization
The use of AI has been steadily increasing since 2023. A recent survey by McKinsey found that in 2024, 78% of organizations were using AI in at least one business function, compared to 55% the year before. This widespread adoption is changing how people consume information.
As Google and other search engines introduce more AI features, businesses are facing a unique challenge. They may see an improvement in rankings and impressions, but fewer clicks. This is because AI engines are becoming the go-to source for discovering products.
However, it's important to note that the buyer's journey remains the same. Users still identify a problem, find a solution, research and compare products, and make a purchase. What has changed are the channels guiding these steps, with AI search playing a bigger role in the first three phases.
Traditional SEO focused on ranking high in search engine results pages. Content was designed to address basic search queries, where users often had to make multiple attempts and do manual research to find what they needed.
But with AEO, the focus is on providing the best answers directly through language models. This means creating content that satisfies specific, conversational queries, where users can learn from the AI and ask follow-up questions.
Succeeding in the world of AEO requires two things: selecting 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 establish strong connections between their content and the product categories they want to be associated with.
For example, a company that offers project management software should target keywords beyond just "project management tools." They should also create in-depth content on related topics such as "resource allocation," "workflow automation," and "team collaboration best practices." This helps AI engines associate the brand with the entire product category.
Selecting the right topics means claiming a semantic territory and fully owning it, rather than just targeting individual keywords. This can be achieved in three ways:
1. Category saturation: Developing clusters of content that thoroughly cover a topic category, from basic definitions to advanced use cases.
2. Context-rich answers: Addressing nuanced, conversational queries such as "How do small businesses manage projects with limited resources?" instead of just targeting short, keyword-driven questions.
3. Personalization at scale: Creating variations of content tailored for different industries, business sizes, or roles. This allows AI engines to provide the most relevant response for each user.
AEO values breadth and depth of context. The more comprehensive and interconnected the content is, the better AI engines can understand and recognize it as authoritative.
Designing Content with Intent
AI engines prioritize content that is both accurate and structured for machine readability and retrieval. It's a delicate balance between being factually correct, providing complete information, and telling a structured story.
There is value in using widely accepted information from credible sources. Citing sources, linking to structured data, and presenting verified facts can increase the chances of being cited. However, to stand out, content should also include unique insights or data that can't be found elsewhere.
For example, a marketing firm publishing an article on "Top Emerging Marketing Trends" could use widely available data but also include their own research findings to increase their chances of appearing in AI search results.
Language models also index and retrieve content in "chunks." This means each paragraph or section in your content should be a complete thought on its own. A paragraph that explains how workflow automation tools support tasks like audience segmentation and lead scoring is more valuable than one that simply references an earlier point. This ensures the content can be understood and retrieved without relying on surrounding context.
Another important factor is entity association. Content that clearly identifies and connects entities helps AI engines understand information in context. Techniques like using semantic triples make this easier. Here's an example:
Semantic triple: "The CRM helps sales teams track leads."
Subject: The entity being described
Predicate: The relationship or property
Object: The value or related entity
Having great content is no longer enough to guarantee visibility. To break through in today's world, brands need to reach their target audience by using accurate, comprehensive, and easily understandable content for both humans and AI.
To truly make an impact, brands need to have a smarter distribution strategy that amplifies their content across different channels where their target audience is already paying attention.
From Distribution to Amplification
This shift in search and discovery, driven by AI, is outlined in HubSpot's Loop Marketing playbook, which helps businesses adapt to changing customer habits.
The Loop consists of four stages:
1. Express who you are: Define your brand's voice, tone, and perspective.
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