Why 39% of AI Systems Disagree on Brand Recommendations (and How to Fix It)

By Sarah | GEO Research | 8 min read

Discover why 39% of AI systems diverge on brand recommendations. Learn how to fix gaps in AI brand visibility using data-driven strategies and GEO techniques.

Tags: AI visibility, brand monitoring, cross-provider analysis, generative engine optimization, data insights

Why 39% of AI Systems Disagree on Brand Recommendations (and How to Fix It) Here’s a question I hear a lot lately: why do AI systems recommend different brands for the same query? It’s a fair question. When you ask ChatGPT about the best running trainers, and then Google’s AI Overview the exact same thing, you’d expect consistent answers. But they’re not. According to data from our Contxt platform, 39% of prompts deliver conflicting recommendations between those two systems. That’s almost two in five queries producing wildly different commercial outcomes based purely on the AI system someone happens to use. Think about what that means. Your brand might be highly visible on one platform and completely invisible on another. And if you’re not paying attention, that’s a whole chunk of your market slipping through the cracks. That gap, or what we call the “AI recommendation gap”, can be both a commercial risk and a massive opportunity. So, let’s break it down: why does this gap exist, what’s the real-world impact, and, crucially, what can you actually do about it? A visual comparison of brand visibility in ChatGPT vs Google AI Overview recommendations The 39% Divergence: What’s Going On? First, the brutal truth. There is no universal AI. Every system, whether it’s ChatGPT, Google AI Overview, Claude, or Perplexity, is trained differently, with different datasets, algorithms, and priorities. That’s why, across our dataset of 2981 prompts run through four major AI systems, we saw major discrepancies in brand mention rates. For example: ChatGPT had the highest mention rate at 75.8%. Google AI Overview lagged significantly behind at 46.5%. Claude and Perplexity pulled in at 67.6% and 55.0%, respectively. Here’s the kicker: the same prompt, tested across all four, frequently delivered different recommendations. To put some numbers on it, 39% of prompts resulted in conflicting answers between ChatGPT and Google AI Overview. That’s huge! And we’re not just talking minor differe