The AI Search Reality Check: What's Actually Working (and What's Just Hype)

Winning in AI Search: How Conductor Is Rebuilding Marketing for the AEO Era AI-driven discovery has reshaped how customers research, compare, and choose products, especially in B2B. In this Game Changers CMO Series conversation, Kathleen Booth (VP Marketing, Sequel) sat down with Lindsay Hagan (VP of Marketing & Co-Head of Revenue, Conductor) to unpack what’s actually changing, what still matters, and what marketers should do next. Below are the key themes from the webinar, each anchored with one standout quote, followed by a short, practical unpacking that ties back to the broader conversation. 1) The acronym chaos is real, here’s the stake in the ground “Let’s put the stake in the ground. It’s AEO.” For marketing teams trying to plan, budget, and communicate, terminology sprawl becomes a real problem: GEO, AIO, AI SEO, and more. Hagen’s point isn’t just semantic, alignment unlocks execution. By standardizing on AEO (Answer Engine Optimization), teams can more clearly define responsibilities, tooling, measurement, and priorities. It also frames the shift accurately: we’re optimizing to be chosen and cited in answers, not just to rank for a query and win a click. This connects to the rest of the discussion because it sets up a central premise: customer behavior has moved from short keywords to long, specific prompts across multiple AI “surfaces,” and marketing needs a shared language to evolve with it. 2) AEO is an evolution of SEO, but the game board is different “AEO is an evolution of SEO… the AI engines aren’t the same as the good old Google bots.” Hagan reinforces that marketers shouldn’t throw away SEO fundamentals; technical health, crawlability, and strong content still matter. But she’s equally clear that AI systems behave differently: they’re not simply indexing and ranking pages the way traditional search has for decades. That changes how you think about content coverage, structure, freshness, and what “winning” even means. In context, this expands on Booth’s question about whether “good SEO” should naturally translate to “good AEO.” The answer is: the foundation carries over, but the operating environment has changed enough that strategies must adapt, especially when prompts (not keywords) drive discovery. 3) The content bar is higher: depth, breadth, and “unique wisdom” win “It’s not about just creating more content, but the content really has to have unique wisdom and insights in it.” This is the heart of modern content strategy, and a warning against volume-for-volume’s sake. As Hagan describes it, AI is “insatiable” for content across the buyer journey, personas, and edge cases. But generic AI-written pages create sameness: if multiple brands publish nearly identical, LLM-generated articles, none of it becomes differentiating signal. Her “unique wisdom” framing ties into what content actually performs in an AI era: research, point-of-view, customer stories, interviews, and proprietary insight, content competitors can’t easily replicate. It also echoes Booth’s observation that “great content is great content in any age,” with a sharper requirement now: it must be genuinely differentiated, not merely well-optimized. 4) Bottom-of-funnel is where the leverage is shifting “What you really want… is… when potential customers are searching for AEO technology, GEO technology, SEO technology… we want to be disproportionately recommended.” This is a critical strategic shift. In traditional inbound, top-of-funnel traffic was the engine: rank for educational terms, earn clicks, convert visits to leads. Hagen points out the new reality: LLMs increasingly satisfy early research without sending traffic back, and citation click-through rates are low. So Conductor is focusing content where it can still influence decisions: shortlist terms, vendor comparisons, and “Conductor vs. competitor” queries, places where the buyer is closer to selection and where positioning and accuracy matter most. It’s a direct answer to Booth’s question about whether marketers have historically under-invested in detailed product content: yes, and in the AI era, that content can be disproportionately valuable. 5) Measurement is moving from traffic to visibility, mentions, and sentiment “We’re going from traffic to a world where you need to be looking at things like visibility, brand mentions, recommendations, sentiment.” If traffic is being “cannibalized” by AI answers, funnel dashboards alone won’t tell the story of marketing’s impact. Hagen describes a new measurement stack designed for AI discovery, tracking whether your brand is being mentioned, cited, and recommended, and whether the sentiment and positioning are correct. She also makes an important organizational point: AEO is increasingly a board-level conversation, which raises the stakes for credible reporting. The takeaway is not “traffic doesn’t matter,” but rather “traffic is no longer the whole proof.” Marketing teams need metrics that reflect influence in the places where decisions now begin. 6) Gated content needs a hybrid approach to work in an AI world “We… put an ungated long form piece of the content on the site for discoverability… and… a dedicated landing page with the artifact behind the gate.” This is one of the most practical sections of the webinar. Conductor tested putting an HTML page behind a gate to allow AI bots to crawl it, but found bot activity spiked and then dropped off, suggesting the approach wasn’t reliably producing ongoing visibility. Their solution: keep the demand-gen motion intact (gated PDF/asset for campaigns), while publishing an ungated, long-form version for AI discovery and citation. Booth adds a complementary insight from her own tests: people may convert better after they’ve seen the quality, gating the PDF version can work as a “proof-first” exchange. The strategic tie-in: AEO requires content to be accessible to systems that summarize and cite. If it’s locked away, it can’t shape answers, so teams must separate “content for discovery” from “assets for capture.” 7) Competitor pages are a high-impact AEO tactic, if you keep them fresh “We… published our own conductor versus competitor pages… and… a lot of the content that’s getting cited is our content, and so we’re able to influence the narrative.” Competitor comparisons used to feel risky: too “salesy,” too revealing, too likely to spark rebuttals. Hagan argues the opposite in an AEO world. If AI systems will generate comparisons anyway, brands should participate by publishing clear, accurate, well-structured comparisons that represent them properly. The nuance is operational: these pages can’t be “set and forget.” Conductor updates them on a cadence, every two weeks, because freshness signals matter and because product realities change. This ties directly back to the earlier themes: AEO is about being represented correctly in answers, and that representation is shaped by what the models can find and trust. 8) Repositioning as an incumbent: don’t chase startups, define the category “We’re going to define what an AEO platform is… and… our roots in SEO… are what make us a strong AEO platform.” Hagan’s repositioning lesson is especially relevant for established brands facing AI-native entrants. The instinct is to mimic the startups’ aesthetics, language, and product posture. Conductor chose a different path: leverage credibility, enterprise experience, and deep SEO roots to lead the market conversation about what “AEO platform” means (versus “tool”). She also highlights the mechanics of category definition, analyst briefings, market education, and consistent messaging, because enterprise buying is heavily influenced by third-party validation. This ties to Booth’s observation about “AI-powered everything” blending together: differentiation comes from clarity, not buzzwords. 9) AI can accelerate content, but only when grounded, reviewed, and human-led “There’s nothing that’s going from idea to publish without human in the loop and without someone… infusing wisdom into it.” Hagan draws a clear line between AI as a drafting and scaling tool versus AI as an unsupervised content factory. Her framework: AI content must be grounded in real company context, knowledge bases, transcripts, internal docs, personas, performance data, otherwise it becomes generic “AI slop” that fails to differentiate and may not sustain performance. This closes the loop on the webinar’s central tension: yes, marketers need more content than before (to cover more prompts and more nuanced journeys), but the solution isn’t mass generation. It’s smarter creation, AI-assisted, context-rich, and editorially owned by humans with expertise.