Webinar Recap: Why AI Search is Bigger Than SEO

Sam Page, Head of AEO/SEO Services at AirOps, and Ali McCarty, VP and GM of Managed Services at AirOps, joined Josh Spilker, Head of Search Marketing, on an AirOps webinar to explain what this shift means for marketing teams.

The central idea: AI discovery reflects what a brand says, what customers experience, what publishers report, what creators explain, and what communities discuss. Winning requires a connected view of all five.

Top 5 Takeaways

1. AI Discovery Has Five Major Inputs

Owned content, external content, AI ads, social and influencers, and community all influence whether a brand gets found, trusted, cited, and chosen.

The website remains the foundation, but buyers and AI systems research a category across many surfaces. Marketing teams need to understand how those inputs reinforce one another.

2. Map Prompts to the Buyer Journey

Prompt tracking can show where a brand appears, which competitors are gaining visibility, and what sources an AI system cites. The full buyer journey is broader.

Buyers move from understanding a problem to comparing products, researching implementation, reading reviews, and evaluating price. A brand may perform well during one stage and disappear during another.

Map the journey first. Then track the prompts connected to the moments that matter most to the business.

3. Review Sites Are a Core AI Search Channel

AI systems look beyond a company’s website to understand how customers experience its product. G2, TrustRadius, Capterra, Amazon, and other category-specific review platforms can influence sentiment, comparisons, recommendations, and perceived fit.

Sam called third-party reviews “S-tier” material for LLMs.

Reviews contain the language customers use, the strengths they value, the weaknesses they notice, and the alternatives they considered. That makes review sites an important part of the AI search channel mix.

4. Relevance Can Matter More Than Reach

The source influencing an important AI answer may have a surprisingly small audience.

Ali described how a YouTube video with a few hundred views from a creator with roughly 2,000 subscribers could become a top-cited source for a valuable commercial prompt. It mattered because the content answered the right question with the right context.

Citation analysis gives teams another way to evaluate influence beyond follower counts and impressions.

5. AI Visibility Needs a Path to Business Impact

Mentions and citations are an important starting point. Marketing leaders also need to understand whether that visibility contributes to qualified traffic, conversions, pipeline, and revenue.

Every content refresh, review program, third-party placement, creator partnership, community investment, and ad test should have a measurable hypothesis. Track the action, measure the response, and use the result to guide the next decision.

Best Practices and Key Learnings

Manage AI Discovery as a Connected Channel Mix

A buyer may ask ChatGPT for a category overview, watch a cited YouTube video, read a G2 comparison, search Reddit for candid opinions, visit a product page, and return to an AI assistant with an implementation question.

Each source changes the context of the next interaction.

That makes coordination more important. A strong website cannot fully compensate for outdated third-party descriptions. A creator program may build awareness while leaving comparison questions unanswered. Positive reviews may build trust, but buyers still need clear information about pricing, integrations, setup, and fit.

Start with the business goal, then determine which channels have the most influence over it. A product launch, new market, and competitive displacement strategy will each require a different mix.

Build Prompt Tracking Around the Full Journey

A prompt list can become a dashboard of disconnected questions. It might show that a brand appears for “best software for X” while missing whether that brand survives practical questions about deployment, permissions, integrations, price, or support.

Build coverage across the major stages of the buyer journey:

• Problem and category education
• Use cases and audience fit
• Product discovery
• Alternatives and comparisons
• Reviews and customer experience
• Implementation and integrations
• Pricing and purchase readiness

Sales calls, support transcripts, customer interviews, win-loss analysis, and product marketing research can surface questions that keyword tools miss.

Once the journey is visible, teams can identify where the brand disappears, where competitors have an advantage, and which stage deserves investment.

Keep Owned Content Fresh and Specific

Owned content is the part of the system a brand controls most directly.

Sam recommended a regular refresh cadence, often every three to six months in a fast-moving category such as B2B SaaS. A useful refresh incorporates product changes, original research, expert insight, customer questions, and changes in the market.

Customer support calls, sales transcripts, reviews, webinars, and interviews with internal experts can improve existing pages and inspire net-new content.

Sam shared an example from InMotion Hosting. His team published an article about Discord when the topic showed essentially no search demand. As interest grew, the page became one of the company’s largest non-branded top-of-funnel traffic drivers.

Traditional search data describes what people have already searched. Customer conversations can point toward what they will need next.

Make Review Sites Part of the AI Search Program

Review programs often sit with customer marketing, product marketing, lifecycle, or partnerships. AI discovery gives that work a broader strategic role.

Review sites help AI systems answer questions a brand cannot credibly answer on its own:

• What do customers consistently like?
• Which limitations appear repeatedly?
• Which competitors do buyers consider?
• Which product fits a particular team, industry, or use case?
• Does the market’s perception reflect the current product?

Audit the platforms influencing your category. Look beyond the aggregate rating and study the language inside individual reviews. Recurring phrases can shape how AI systems summarize a product while revealing gaps in positioning, website copy, sales enablement, and onboarding.

Pay particular attention to stale information. A company may have changed its pricing, audience, integrations, or feature set while review profiles continue to reflect the previous product.

Create a consistent process for inviting honest feedback, responding to recurring issues, and keeping product profiles accurate. That gives buyers and AI systems better source material.

Target the External Sources AI Already Uses

External content includes comparison pages, industry publications, affiliate sites, analyst coverage, roundups, and partner pages.

Identify which URLs are cited for the commercial prompts that matter. Then determine whether the brand is missing, described inaccurately, or ranked too low to influence the answer.

Ali described this approach as a scalpel rather than a sledgehammer. A narrow comparison page may influence a high-intent AI answer more than a broad placement on a major publication.

A newer business often needs stronger owned content and more brand credibility first. An established company may need to correct years of third-party information that no longer reflects its product or positioning.

AI search acts like a mirror to the brand. When the internet reflects an old story, AI systems often repeat it.

Evaluate Creators by Citation Influence

YouTube has become an important source for AI answers, especially when buyers want explanations, walkthroughs, comparisons, or demonstrations.

Subscriber count and expected reach remain useful. Citation data answers a different question: whose content is influencing the AI answers that matter to your category?

A smaller creator may have deeper expertise or a video that directly answers a valuable commercial question. Teams can use that insight to prioritize partnerships and plan their own video content.

LinkedIn articles, TikTok, Facebook groups, Medium, and Substack may also influence discovery depending on the audience and category.

Approach Community as a Long-Term Trust Channel

Reddit, forums, user groups, and peer discussions give AI systems access to candid experience and real customer language.

Citation patterns change as AI platforms adjust their retrieval systems. Avoid rebuilding the strategy around every short-term spike or decline. Ask whether customers genuinely discuss the category there, whether the brand can contribute something useful, and whether the team can participate consistently.

A credible community presence grows from useful answers and sustained participation, not a rush to fix one negative thread.

Test AI Ads Alongside Organic Visibility

AI ads add another layer to the channel mix. The format is still developing, which makes this a useful period for controlled experimentation.

Evaluate sponsored and organic visibility together. A brand may already lead organically during one stage of the journey and need paid support elsewhere. Competitor ad activity may also reveal where commercial value is emerging.

Create a test budget, identify the buyer moments the experiment should influence, and measure the combined paid and organic result.

How to Put This Into Practice

Start with one business priority, such as a product launch, a new segment, or a competitive category.

Map the buyer journey and build a focused prompt set around it. Then audit the channels:

• Owned content: Is the website current, accurate, and useful across the journey?
• External content: Which third-party pages influence relevant answers?
• Review sites: What story do customers tell about fit, strengths, limitations, and competitors?
• Social and influencers: Which creators and assets appear in important answers?
• Community: Where do customers discuss the category?
• AI ads: Where could a paid test fill an organic gap or accelerate learning?

Choose the actions closest to the business goal. Give each one an owner, hypothesis, baseline, and review date.

The work can happen across several teams. The strategy needs one connected view.

What a Connected AI Discovery Program Looks Like

A mature AI discovery program understands which buyer moments matter, which channels influence those moments, and which action should come next.

The website stays fresh. Review profiles reflect the current product. External sources tell an accurate story. Creators and communities receive useful contributions. Paid experiments have a clear purpose. Every action feeds back into measurement.

That is how AI visibility becomes a channel the business can understand: one with priorities, owners, learning cycles, and a path to revenue.

For more on the five inputs shaping AI discovery and how marketing teams should prioritize them, watch the full conversation on YouTube.

To learn how AirOps can help turn AI discovery into a measurable growth channel, book a strategy call or email growth@airops.com with “webinar” in the subject line.

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