Inbound 2025 Recap: What I Learned About AEO and the Future of AI Search

At HubSpot’s INBOUND 2025 conference, one topic stole the spotlight: Answer Engine Optimization (AEO) – the practice of structuring content so it becomes the chosen answer in AI-driven search results. Two standout sessions provided the most clarity on this fast-evolving area: “How to Win at AEO with Zero Budget” by Amanda Kopen, Manager of AI Search and Interactive Experiences at HubSpot, and “Zero-Click SEO Conversion Strategies: AI and Google Search” by Dale Bertrand, President at Fire&Spark.

This Recap Covers:

• SEO vs. AEO – What’s changing and why clarity matters more than keywords.
• Delphic Cost of Search – How AI reduces friction by delivering direct answers.
• Hyper-Personalization – Why AI results are increasingly tailored to each user’s context.
• How AI Search Works – Query fan-out and modular content extraction.
• Evolving Customer Journeys – How AI compresses awareness, consideration, and decision stages.
• Why AI Traffic Converts Better – Fewer clicks, clearer intent, stronger trust.

What is The Difference Between SEO and AEO?

SEO has always been about documents and rankings. AEO focuses on answers. Instead of optimizing for keywords and hoping for a top spot, the goal is to structure content so it can be pulled directly into AI-generated responses.

That means:

• Write clear subheadings that match user questions.
• Put the answer first, then explain.
• Use schema markup so content is machine-readable.

One way to help AI engines recognize and surface your content is by writing in semantic triples. This means structuring facts in a clear subject–predicate–object format that’s easy for AI to parse and cite.

Semantic triple example:

• Subject: Schema markup
• Predicate: Helps AI interpret content
• Object: Increases chances of being cited in AI results

The shift is from ranking to being chosen. If your content is easy for AI to extract, you have a better chance of being the cited source.

What is The “Delphic Cost” of Search?

Amanda introduced the idea of the Delphic cost of search — the effort users spend piecing together answers from multiple links. Traditional search required several clicks, comparisons, and lots of patience.

AI search lowers that cost. Instead of digging, users ask once and get a synthesized, trusted response. For businesses, this means less focus on driving traffic at the very top of the funnel and more focus on ensuring your content is part of those instant answers.

It’s not without risk. If your content isn’t cited, you may miss out entirely. But if you are included, you benefit from reduced friction: visitors who do click through are usually further along in their decision-making.

How Does Hyper-Personalization Change AI Search?

One of the most important shifts discussed at INBOUND was around hyper-personalization. Generative AI doesn’t give everyone the same response. It can tailor answers based on context, behavior, and intent — meaning two people who ask the same question might see different results.

This is possible because AI engines can use signals like search history, user behavior, or broader context to shape what’s returned. For marketers, this means content can no longer be one-size-fits-all. Content that includes clear examples, industry-specific insights, and persona-driven details has a much better chance of being chosen as the answer for the right audience.

For marketers, this means creating content with depth. Include specific examples, industries, and use cases so AI can adapt your content to different contexts. Buyers want answers that feel relevant to them, not just generic content.

How Does AI Search Work Behind the Scenes?

Dale broke this down in a way that really clicked. AI search doesn’t just run one query and spit back results. It:

1. Predicts the best format for an answer (list, table, explanation).
2. Fans out the query into sub-queries.
3. Pulls in relevant context and passages.
4. Synthesizes everything into a single response, with citations

This process means your content doesn’t need to win the whole search — just one piece of it. That’s why structuring content into modular, self-contained sections matters so much.

How is The Customer Journey Evolving with AI Search?

In the past, a typical journey might look like this:

Search → Blog → Sales Page

Now, AI search compresses that journey. A user might get an answer directly in Google’s AI summary, skip early nurturing and land on your site already comparing products or reviewing pricing.

This makes mid-funnel content like product comparisons, FAQs, and case studies more important than ever. AI often surfaces this type of content, and it’s exactly what users need when they’re closer to making a decision.

Why Does AI Traffic Convert Better?

Here’s the upside. The traffic you get from AI may be smaller in volume, but it’s higher in quality. Why?

• AI has already answered basic questions.
• Objections are often addressed before the click.
• Users arrive with clearer intent.
• Being cited by AI builds trust.

When someone lands on your site after engaging with an AI answer, they’re usually further along in their decision-making.

Final Thoughts: Why The Human Touch Still Matters

Leaving INBOUND, my main reflection is that none of us have this all figured out. Search is becoming more answer-driven, more personal, and less predictable. But through all the discussion of algorithms and AI, one theme stood out to me: the human touch still matters.

AI can summarize, extract, and personalize. What it can’t do is replace the creativity, empathy, and expertise we bring to our industries. The best AEO strategies won’t just be technically optimized. They’ll be fueled by real insights, authentic perspectives, and content that genuinely helps people.

Contact Strategic 7 Marketing today or visit our AI Optimization Services page to learn more.