The market consensus seems unanimous: GEO is the magic word. New analysis tools are being evaluated, prompts monitored, and content curated so that language models will treat a company’s brand more favorably. There’s often an underlying assumption that this is primarily about solving a technical translation problem.



What’s easily overlooked in all this: Of course, data structures, discoverability, and external mentions influence what language models output. But if we take a closer look, the debate reveals a remarkable imbalance. In its current guidelines on generative search, Google continues to recommend clean foundations, technically accessible content, and original, helpful information—and explicitly warns against certain optimization tricks marketed specifically for AI.  And Google is currently the operator that delivers by far the most AI responses through AI Overviews in search results and Gemini prompts.

So while a widely used model operator emphasizes substance, other service providers are already offering the next tactical “secret” shortcut. And even if the GEO measures bear fruit and the brand is mentioned more frequently, it’s worth asking—as always—the follow-up question: Does this effect also lead to more business, value creation, and sustainability? The first AI response is rarely the end of a search: We usually ask two or three times, and the recommendations change along the way. If GEO tools fail to capture this, their validity is, at the very least, debatable.



GEO must therefore be optimized in a highly nuanced and in-depth manner, and optimized figures are often far from being optimal figures. But even if GEO functions flawlessly from a technical standpoint, many questions remain unanswered: What are we actually communicating within this optimized system? What brand identity are we actually presenting there? We’re currently investing considerable energy into teaching machines what our brands stand for, but do all the people who work on and with this brand every day actually share a consistent understanding of it—its core messages and the direction our marketing efforts should take?



Especially in the OTC market, completely different perspectives clash on a daily basis: The brand should be simple, approachable, and distinctive for consumers. At the same time, the organization works with complex scientific data, strict HWG limits, approved indications, and the very specific dynamics of pharmacies, retail, and e-commerce.



Today, we take it for granted that a language model will synthesize a crystal-clear brand narrative from regulatory texts, medical information, PR releases, discount promotions, product pages, and third-party sources. But do we, as an organization, truly succeed in translating this complexity into a shared understanding internally? After all, when Brand Management, Medical Affairs, Trade Marketing, and agencies each conceive and articulate their own version of the brand in their day-to-day work, even the most sophisticated GEO setup conveys exactly that: a non-optimized understanding of the brand. At best, it merely makes our own lack of clarity more quickly machine-readable. So perhaps GEO isn’t the wrong task after all. Perhaps we’re just tackling the tasks in the wrong order.