Anda Gansca Warns Against Over-Optimizing for GEO/AEO at LA Times Event
At this year’s Cannes Lions, one of the clearest reality checks in the AI marketing conversation came from Anda Gansca, founder and CEO of Knotch. Speaking with LA Times Studios, she pushed back on a trend that has been building for months: the rush to over-optimize for GEO and AEO while neglecting the actual human experience.
Her point was straightforward and hard to dismiss. Just because a brand appears inside a generative engine doesn’t mean it’s creating business value. Visibility is not the same as conversion. In many cases, the push to get cited by AI systems has left brands with fragmented web experiences people don’t actually want to use.
The Problem Behind the GEO/AEO Gold Rush
As AI-native behavior becomes more common, marketers have been scrambling to adapt. GEO, or Generative Engine Optimization, and AEO, or Answer Engine Optimization, quickly became the new frontier. Brands responded by publishing large volumes of comparison pages, FAQ content, and AI-friendly landing pages meant to increase discoverability in large language models and answer engines.
Gansca’s warning at the LA Times event cut through that hype: taken too far, this strategy can backfire.
She pointed to a stark number: more than 80% of LLM-referred traffic bounces. That says plenty. Users may discover a brand through an AI interface, but the moment they click through to a traditional website, the experience often falls apart. The flow feels broken. A conversational, intuitive interaction suddenly gives way to a static page that wasn’t built for that moment.
Her metaphor was especially sharp: people land in the middle of a comparison page “stuck in the middle of a desert with no map.” That captures the problem well. AI may deliver the user to the page, but the page often does little to move them forward.
Why This Matters More Than It Seems
What stands out in Gansca’s comments is how clearly they reflect a broader shift in digital strategy. For years, marketers treated traffic acquisition as the primary goal. Now the path from discovery to action is changing, and AI is introducing a new kind of friction right in the middle of that journey.
The consumer has changed faster than most brand experiences have. People are getting used to natural-language interfaces, quick summaries, personalized recommendations, and low-friction exploration. When they leave an LLM and arrive on a rigid, conventional website, the mismatch is obvious.
That’s why Gansca’s critique matters. She isn’t arguing against optimization for AI channels. She’s arguing against doing it blindly.
That distinction matters.
From Visibility to Conversion
At Cannes, Gansca made the case that brands need to move beyond visibility metrics and focus on conversion outcomes. That means tracking whether AI-driven discovery actually leads to engagement, trust, and action across the full customer journey.
This is where Knotch’s broader positioning enters the conversation. Just days before Cannes, the company launched ACE, its AI experience infrastructure for what it calls the “conversational web.” The idea is that websites should no longer act like fixed destinations. They should adapt dynamically to user intent while still remaining structured enough for AI agents.
It’s a practical response to a real problem.
According to launch data shared around ACE, early implementations showed roughly a 20% reduction in bounce rate, a 5x lift in engagement, and 3x conversions. Google was cited as one of the early examples. Whether those numbers become standard across the industry remains to be seen, but they support the broader point: brands need infrastructure that serves both machines and humans without compromising either.
- 20% lower bounce rate
- 5x higher engagement
- 3x more conversions
The Real Issue: Experience Debt
The deeper message behind Gansca’s warning is that many companies are building AI-era discovery tactics on top of outdated web assumptions. That creates what could fairly be called experience debt.
A brand can produce AI-optimized content at scale, but if the downstream site architecture, measurement model, and journey design haven’t evolved, the gains are superficial. You may win the mention and lose the customer.
That’s also why her criticism of siloed organizations matters. In many enterprises, one team owns awareness, another owns content, another owns digital product, and another owns conversion. AI doesn’t respect those boundaries. It reshapes the entire journey at once. If companies remain fragmented internally, they’ll have a hard time building coherent external experiences.
Her phrase “pilot purgatory” fits here too. Many organizations have experimented with AI, but too few have operationalized it across the customer journey in a way that is measurable, scalable, and genuinely useful.
A More Grounded View of the AI Web
One of the most useful takeaways from the LA Times discussion was Gansca’s balanced framing: “Everything has changed, and nothing has changed.”
It sounds paradoxical, but it’s accurate. The channels are changing. Discovery patterns are changing. Consumer expectations are changing. But the fundamentals are still the fundamentals. Brands still need trust. They still need relevance. They still need journeys that convert. They still need to prove business impact.
In that sense, the AI era doesn’t eliminate marketing discipline. It raises the bar.
The brands that win won’t be the ones flooding the web with AI-bait pages. They’ll be the ones that connect AI visibility with seamless human follow-through.
FAQ
What is GEO?
GEO stands for Generative Engine Optimization. It refers to optimizing content so it is more likely to be surfaced or cited by generative AI systems.
What is AEO?
AEO stands for Answer Engine Optimization. It focuses on helping content appear in answer-driven environments such as AI assistants and search features that provide direct responses.
What was Anda Gansca’s main warning?
Her main point was that brands should not chase AI visibility at the expense of user experience. Showing up in an LLM is not enough if the click-through experience fails to convert.
Why does high bounce rate from LLM traffic matter?
It suggests a disconnect between AI-driven discovery and the on-site experience. If users arrive and leave immediately, visibility is not translating into meaningful business results.
Conclusion
The takeaway from Anda Gansca’s Cannes message is simple: don’t confuse being found with being effective. GEO and AEO matter, but over-optimizing for them without fixing the user experience underneath is a losing strategy. The next phase belongs to brands that can connect AI discovery and human conversion with intelligence, flexibility, and measurable outcomes. For teams trying to navigate that shift more strategically, AIuthority is worth considering as part of a smarter AI content and optimization toolkit.