Key Takeaways:
- Skydeo‘s Mike Ford details how AI-powered search shifts focus from ranking to recommendation, emphasizing clarity, consistency, and citation density for B2B marketers.
- Bottom-of-funnel content like FAQs, comparisons, and case studies is crucial for AI-driven searches, which target decision-stage prompts.
Search engines are fundamentally changing how they deliver information, forcing B2B marketers to rethink their entire organic strategy. For years, traditional SEO focused heavily on getting specific web pages to rank at the top of search results.
Now, artificial intelligence (AI) answers user queries directly by aggregating information from across the web. Buyers now use AI assistants to make bottom-of-funnel decisions, asking for direct product comparisons and specific use cases instead of generic discovery questions.
Because language models do not read content like humans do, they constantly scan for clear, verifiable answers they can easily extract and repeat. If your brand relies solely on promotional, first-person marketing copy, you risk being left out of the conversation entirely. AI rewards structure, specificity, and objective information validated by trusted third-party sources.
To understand this shift, we spoke with Mike Ford, CEO of Skydeo. In this Q&A, Ford shares his expert insights on navigating the transition to AI-powered search, how to make AEO marketing assets recommendation-ready, why off-site mentions matter more than ever, and how to measure success in a zero-click environment.
Demand Gen Report (DGR): Mike, thanks for taking time Is AI search fundamentally different from traditional SEO, and what should brands focus on?
Mike Ford: Happy to have the conversation. Traditional SEO was about getting your page to rank. AI search is about getting your brand mentioned in the answer.
Language models don’t rank results; they aggregate responses based on what they know, what they are most frequently asked about, and what they are most confident in extracting. This fundamentally changes the game from getting visibility to getting influence. There are three things that brands should focus on:
Clarity: getting answers easily extracted
Consistency: getting answers mentioned consistently across platforms
Citation density: getting answers mentioned across trusted third-party platform
The winner in AI search is not the most optimized result but the most memorable and most validated source.
DGR: How do B2B brands make their content ‘recommendation-ready’ for AI search?
Ford: First off, AI assistants are not reading content like humans do. They are scanning for answers they can lift and repeat instantly.
For recommendation-readiness, brands should start with the answer in the first 1-2 sentences; use question-based headers; structure content in bullets, tables, and sections; focus on FAQ, comparison, and use case content. The big change is that brands should now be writing content that is meant to be lifted, summarized, and repeated by AI assistants.
What AI Content Shows Up on Searches
DGR: Why do AI-driven searches convert better, and how do brands capitalize on this trend?
Ford: To begin with, AI-driven searches are coming from decision-stage prompts, not discovery-stage prompts. So, users are asking questions like:
- What is X?
- What is X used for?
- What are the features of X?
- But in AI search, users are asking:
- Best platform for [use case]
- Compare X vs Y
- Is this worth it?
This means that AI presents brands at the point of consideration. Therefore, there is more intent and stronger conversion behavior. For brands to capitalize on this, they need to invest in comparison page content, pricing transparency, implementation and onboarding content and case study content that is linked to results Bottom-of-funnel content is no longer optional; it’s where AI search wins.
DGR: What types of content is AI most likely to surface?
Ford: AI is most likely to surface content that reduces uncertainty and is easy to extract. High-performing content includes comparison tables and “best of” lists, FAQ and how-to content, product guide and support content, case study content that is linked to results, and user-generated content such as Reddit, YouTube, and forums.
Low-performing content includes vague thought leadership content, keyword-stuffed long-form content and content that buries the answer. AI rewards structure, specificity, and repeatability.
DGR: What role does Reddit, YouTube, and review sites play—and how does a brand show up here?
Ford: AI search is heavily influenced by something called “earned AEO”—how many times and where your brand is mentioned outside of your own site. AI models pull information from:
- Reddit threads
- YouTube reviews and demos
- Third-party “best of” lists
- Review platforms
In many instances, AI is aggregating this information and presenting it as consensus when providing recommendations. For brands to win here, they need to:
- Invest in digital PR and creators
- Show up in roundups and category comparisons
- Create content that is worthy of being shared
If you don’t show up in those places, you don’t show up in the answer.
Mistakes You Should Be Avoiding
DGR: Why does third-person brand content work better for AI discovery?
Ford: Well, AI models prefer content written in neutral, verifiable language, rather than promotional content. The reason is that third-person content is more objective and easier to reuse, written the same way as reviewers and analysts write, and removes the impression of bias towards the model.
On the other hand, first-person promotional content, like “we’re the best,” leaves a lot of uncertainty. The rule of thumb: Write the way you’d like to be written about, not the way you’d like to write about yourself.
DGR: What are the most common mistakes made by brands?
Ford: The most common mistakes we see:
- Placing answers after lengthy intros
- Using too much promotional or vague content
- Focusing too much on owned content, ignoring off-site presence
- Inconsistent content across all channels
- Focusing too much on top-of-funnel content
One of the most common mistakes made is thinking of AI search as a ranking problem. It’s actually a recommendation problem.
DGR: What are the best practices for writing great content for FAQs, case studies, and pricing pages?
Ford: These types of content are actually some of the most valuable assets you can have in AI search, if done well. For FAQs, you should mirror real prompts exactly and answer immediately, directly, and succinctly. When creating case studies, highlight specific cases, include clear metrics, outcomes, and data, and always use consistent terminology.
Your pricing pages need to be transparent, structured, and unambiguous. Clearly define what you offer at each level so the AI never has to guess. In all of these cases, the goal remains the same: make it easy for the AI to understand, verify, and reuse the content.
In all of these cases, the goal remains the same: make it easy for the AI to understand, verify, and reuse the content.
DGR: How can brands utilize directories and profiles?
Ford: For the AI models, it’s essential to understand the importance of entity validation and consistency.
This implies that your presence on
- G2 / TrustRadius / Capterra
- Industry directories
- Google Business / Wikipedia
- Review sites
…will help solidify:
- Who you are
- What category you are
- How other people talk about you
Inconsistency breeds doubt. Consistency breeds confidence. And confidence breeds recommendations.
Keys to AEO Success
DGR: How can brands succeed in the new AI-powered search?
Ford: The winning brands will think of the AI space as a new layer of the entire marketing ecosystem.
Here are the key ways to succeed:
Map for high intent prompts in your category
Develop for specific use cases
Achieve more earned mentions
Publish original data and insights
Optimize for citation, not clicks
These are all shifts away from traffic acquisition and recommendation engineering.
DGR: How can brands measure the effectiveness of the new AI-powered search?
Ford: Since the AI space is a zero-click environment, we need to rethink the way we measure the effectiveness of our presence. Instead of Voice traffic, screens and engagements, B2B marketers need to to measure by AI citation, share of answer, sentiment, branded search and post-purchase attribution (“I saw you on ChatGPT”)
The key insight here is that the decisions driven by the AI-powered search are happening before the analytics can even measure them.
DGR: What is the biggest mental shift B2B marketers need to make?
Ford: The biggest mental shift marketers need to make is to understand that the new zero-click environment represents a new level of visibility.
You can:
- Shape the perception
- Influence the decisions
- Drive the conversions
…without ever owning the interaction.
So, the new question is no longer: “Did we rank?” The new question is: “Were we included in the answer? And were we positioned correctly?”
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