Imagine this: content visibility is increasing, but traffic to your website is dropping considerably. According to Search Engine Land, more than half of today's Google searches end without clicks. And consumers are looking everywhere, including Google's AI overview and Reddit.
Is this your reality? Welcome to the playback of how people find information.
Payoffs from traditional SEO tactics were once huge. Currently, AI effectively provides everyone with access to unlimited, personalized knowledge about a diverse set of channels, and Google searches have lost users of AI search engines such as ChatGPT.
Once a reliable marketing playbook is officially confused. You can't rely on one distribution channel like search. As a brand, we need to diversify our content across our channels.
With the rise in AI adoption, one of those channels is AI search. When viewers find information in large language models (LLMS), it's time to optimize content strategies for both humans and machines. Hubspot breaks it down here.
AI usage has been increasing since 2023. A recent McKinsey survey found that 78% of organizations used AI in at least one business feature in 2024. This widespread adoption is fundamentally changing the way people consume information.
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As Google and other search engines deploy more AI capabilities, businesses face unique paradoxes. Even if rankings and impressions improve, there are fewer clicks. This is because AI engines are increasingly becoming the first stop for product discovery.
However, it is worth noting that the buyer's journey has not changed. Users continue to identify problems, determine solutions, find the right product for that solution, and ultimately buy. However, in the channels that guide these steps, AI searches are increasingly forming the first three phases.
Traditional SEO focused on bringing the best resources to surface through search engine results pages (SERPs). The content is designed to address simplified search queries, where users make multiple search attempts and perform manual investigations to compare results.
However, AEO prioritizes the best answers directly through LLMS. This means that users will develop content that meets specific natural language queries that will learn from the AI engine and ask conversation follow-up questions.
Successful in an AEO environment relies on two things: choosing the right topic and deliberate content design.
AI engines rely on vector embedding to understand the relationships between words, concepts, and entities. This means that brands need to build strong semantic relationships between their content and the product categories they want to own.
For example, project management software companies should target keywords beyond “project management tools” and create depths across related topics such as “resource allocation”, “workflow automation”, and “team collaboration best practices”. This will allow the AI engine to start associating brands with the entire product category.
Topic selection is not chasing individual keywords, but claiming and fully owning semantic territory. This can be done in three ways:
Category saturation: Develop a cluster of content that thoroughly explores topic categories, from definitions to advanced use cases.
Context-rich answer: Keyword-driven questions as well as keyword-driven questions that address subtle conversational queries such as “How SMEs manage projects with limited resources?”
Large personalization: Create content variations tailored to different industries, business sizes, or roles. This allows the AI engine to elicit the most relevant response to each user context.
AEO rewards width and depth of context. The more complete and interconnected content is, the more AI can understand it and recognize it as authoritative.
AI engines are prioritized for accurate and structured content. This is a strategic balance between de facto authority, semantic integrity and structured storytelling.
Consensus-driven, widely supported information is valuable. Citing trustworthy sources, linking to structured data, and presenting verified facts increases the likelihood of being cited. However, to stand out, content must also include information gains, i.e. insights and data that you won't find anywhere else.
For example, marketing companies publishing articles on “Top Emerging Marketing Trends” can also cite widely available data, but also include their own findings from their own research teams to increase the likelihood that they will appear in AI search results.
LLMS also indexes and retrieves “chunks” content. This means that each paragraph or section of content must exist alone as a complete thought.
Paragraphs explaining how workflow automation tools support tasks such as audience segmentation and lead scoring are far more valuable than simply referencing previous points. This integrity allows you to understand and retrieve content without relying on surrounding contexts.
Another important element here is entity associations. Content that clearly identifies and connects entities (companies, tools, processes, etc.) can help the AI engine understand information in context. This can be easier by writing techniques such as using semantic triples.
This is how it actually looks.
Semantic Triple: “CRM helps sales teams track leads.”
subject: Explained Entities (CRM)
predicate: Relationships or assets (help)
object: Value or related entity (track lead)
Great content alone is no longer guaranteed visibility. To break through today, you need to meet your prospects with accurate, comprehensive and simple content for both humans and AI to understand.
To make it truly important, brands need a smarter approach to distributions that amplify content that amplifies content across channels that buyers are already paying attention to.
This tactical, AI-driven change in search and discovery is outlined in Hubspot's Loop Marketing Playbook. This helps businesses evolve as customer habits change.
The loop has four stages:
Express Who you are: Define your preferences, tone, and perspective.
tailor Approach: Use AI to personalize interactions.
amplification Your reach: Diversify content across human and bot channels.
evolution In real time: Quickly and effectively repeat.
AEO is perfect for this Playbook in the Amplify stage. This stage focuses on diversifying the channel mix and hiring customers.
The components of the amplification stage were historically considered one simple play, distribution. However, these tactics are currently affecting LLM citation doses in the AI search era.
This is a simple breakdown.
This is discussed in detail as AEO will acquire a central stage as a new channel for information and product discovery. The key to diversification is to accept the channel more upside down. This includes AEO, but channels like community forums and videos also show big returns.
According to Statista, Reddit has seen a significant increase in daily active users across the region, with roughly 50 million users in Statista in the US reporting that YouTube has over 2.5 billion global audiences as of February 2025.
Channel strategies must reflect changing industry trends and follow audience behavior. The goal is not to be anywhere. We want to be part of the platform where messaging has the most impact.
When someone reaches your website, they already show high intentions. They are no longer casually browsing. They are actively assessing whether your product or service can solve their problems.
This makes on-site experiences as important as the channels they've appeared in.
Providing value at these moments requires immediacy. Buyers expect immediate responses, personalized recommendations, and a smooth path to action.
Software companies may integrate AI assistants that surface related tutorials or comparison pages the moment a visitor begins to study a feature. The goal is not to overwhelm the information, but to predict the next question and provide it before the buyer bounces back.
Real-time engagement also means removing friction. Fast load times and intuitive navigation help you create an experience that feels easy. After all, buyers are more likely to convert if they don't have to work too hard to find information.
Influence has shifted from traditional search to LLMS, but from sophisticated brand channels to trusted individuals.
Viewers today are more likely to believe product reviews from respected YouTubers and product reviews from honest LinkedIn posts from industry experts than from business press releases.
Partnering with creators, such as YouTubers and industry experts, builds credibility by transferring trust. These voices can be invaluable for amplification as your brand has already established relationships with the community you want to reach.
If it hasn't been revealed so far, there will be a high demand for fresh, relevant content across multiple platforms. AI can provide leverage to meet its demand without breaking the bank with personnel and budgets.
Using AI can help increase production, but use it wisely and don't forget about human involvement. You can ask the AI to:
Convert long content (blog posts, white papers) into bite-sized assets (social media posts/graphics, short form videos).
Personalize copies of different audience segments to ensure consistent messaging at scale.
Handle busy work and time-consuming tasks such as research and copy editing.
As a result, the content engine moves faster, adapts more easily, frees up teams and focuses on production creativity.
Advertising is at a stage where personalization and interactivity are no longer superior. Static banners and generic pre-rolls have replaced AI generation campaigns that adapt in real-time.
For example, SaaS companies may run LinkedIn video ads that automatically highlight various product features, depending on the audience's position. The CFO is looking at the ROI dashboard, while the sales manager looks at the pipeline tracking tool.
A common thread is relationship. By experimenting with new ad formats and technologies, brands can see viewers with timely messages that feel personal and stand up ahead of competitors who rely on old ways.
AI is restructuring the way buyers make decisions. There's no surprise.
Like a phone game, your business website has become essential to affect people, taking action, and affecting the AI engine you buy from you. The journey to product discovery spreads across LLM, communities, creators and dynamic brand experiences.
Winning this new era means that both humans and machines create trustworthy content and appear in spaces where buyers are already involved.
Companies that can adapt are not simply found. It is recommended, quoted and surfaced at the moment when the intention is highest.
This story Produced by hubspot Reviews and distribution Stacker.
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