Two different large language models, given the same simple prompt to find a family vehicle under $50,000, returned 10 vehicle suggestions with only a single model in common. That fragmentation is now a central challenge for brands whose visibility depends on what these AI models recommend. According to an October 2025 McKinsey report, 50% of Google searches already include AI summaries, a figure expected to surpass 75% by 2028, funneling an estimated $750 billion in U.S. revenue through AI-powered search. Brands that are unprepared could see traditional search traffic drop by as much as 50%.
The scramble to understand and influence these results has birthed a new discipline called Generative Engine Optimization, or GEO. Major marketers describe the current state as the 1998 equivalent of search or 2006 for social media-a foundational moment moving at a much faster pace. While startups pitch rapid content generation to feed AI models, brand executives and agencies say the reality is more nuanced and rooted in classic marketing fundamentals.
The foundation is still classic brand management
When an LLM answers a query about a product, it distills information from across the internet-executive LinkedIn posts, customer Reddit threads, major media coverage, and a brand's own content. Jim Prosser, a public relations veteran, recently argued that GEO is essentially a strong communications strategy paired with monitoring how a brand surfaces in AI tools. Meghan Signalness, global head of media, marketing planning and operations for Philips's $4 billion personal health consumer business, agrees. "There's a lot of hype around it, but at the same time, it has basically confirmed marketing fundamentals," she said. "In some ways it's just SEO sped up."
Philips has run multiple GEO audits and found that the most effective lever is showing up consistently. LLMs look for the words most associated with a brand-a concept Signalness calls old-school marketing. Ally Financial CMO Andrea Brimmer said the scope of what matters has expanded. "We've come to realize really quickly that brand has never been more important than it is now," she said. "You better have really damn good customer experience and PR around your products, you better have a strong reputation in the marketplace, you better show up as a good citizen of the world, and you better treat your employees really well because all of those elements of what makes a great brand are more important now than ever before."
Owned content and clear answers win
Roughly 60% to 65% of AI citations can derive from a brand's own digital assets, according to Chris Neff, global chief AI officer at Anomaly. That has increased the value of structured brand landing pages with citable assets and clear architecture. Brad Nunn, vice president of media at Gale, said FAQ pages are particularly important. Clear, factual, one-sentence answers prevent LLMs from making incorrect assumptions. "You're mentioning the brand up front, and you're saying exactly what it's solving," he said. James Cadwallader, cofounder and CEO of AI-native marketing platform Profound, added that owned content gives LLMs the best opportunity to understand a business. Generative AI and LLM Courses can help marketing teams build the skills to structure this content effectively.
Brimmer's team at Ally uses a tool called Scrunch to monitor how the brand appears across LLMs, then holds weekly cross-disciplinary meetings with PR, tech, HR, and a dedicated AI team. When they find outdated or incorrect information, they create new content and work with PR to correct the original sources the bots are citing. The goal is to make the brand's online presence as clear and consistent as possible for AI models to interpret.
Building authority in a messy information environment
LLM search currently prioritizes sources high in expertise, authoritativeness, and trustworthiness, but problems arise when a high-authority source contains wrong information. Brimmer described this phase as a "Wild, Wild West" where brands must engage in "hand-to-hand combat" to ensure accuracy. When Ally announced customers could deposit cash at Walmart, major LLMs still told users the bank did not offer the feature. Fixing it required a long-term content push across the brand's own site and third-party sources.
Philips experimented by hosting an "Ask Me Anything" on Reddit with credentialed engineers and doctors to provide factual content on a platform AI models scrape heavily. The results were encouraging, though Signalness said it remains far from an exact science. The company also tested influencer strategies and found that LLMs give more weight to professionals-doctors, dentists-than to general content creators. "While we know there's a role for influencers, in the context of an LLM there's not as much of a role for that 20-year-old with a cellphone as there is for a doctor, a dentist, or another professional," she said. "So it's stripping away a lot of noise, which is really refreshing."
Human fingerprints over AI slop
Every source interviewed warned against mass-producing AI-generated content. Taryn Crouthers, CEO of Big Spaceship, pointed to a "trust gap" where consumers tune out or recoil from material they perceive as AI-made. "So now brands need human fingerprints or evidence of effort," she said. "You can make something using AI and make sure that the GEO attributions are all there, but you need to also show the human side of that storytelling, how hard it was to make it, why you made it, how you made it."
Ndidiamaka Oteh, CEO of Accenture Song, said LLM visibility moves beyond traditional product attributes into conversational context. A black crewneck sweater is no longer just about the item itself but about how it fits into an afternoon ski trip-context a traditional attribute list would never include. This shift requires a different approach to how brands describe and position their products. For marketing professionals adapting to these changes, AI for Marketing Courses offer practical guidance on navigating AI-driven discoverability.
Why this matters for marketers
Only 16% of brands currently track AI search performance systematically, according to McKinsey, leaving a wide gap between the hype and actual measurement. The tools to monitor LLM visibility-from Profound to Bluefish to Scrunch-are maturing, but the AI companies themselves have not yet built the brand liaison departments that Google, Meta, and TikTok offer. Signalness said the answers to brands' questions about data and partnership "aren't coming back clearly." For now, the most practical steps are monitoring how your brand surfaces, correcting misinformation at its source, and ensuring owned content is structured, factual, and consistent. The brands that will win in LLM search are the ones already winning at the fundamentals.
Your membership also unlocks:
