ChatGPT and Gemini Rarely Agree on Top Local Businesses, Study Finds
AI visibility is not a single score that a business can measure once and treat as settled. A cross-engine study of local-service searches found that ChatGPT and Gemini named the same top business in only 4.2% of identical queries . For small businesses trying to be discovered through AI assistants, that gap means a strong result in one engine may say very little about how another assistant…
A recent study has revealed that AI assistants like ChatGPT and Gemini typically agree on only 4.2% of top local businesses when answering identical queries. This research, conducted by Steady Demand's AI Citation Ledger, examined 1,487 searches across 50 U.S. cities and 10 service sectors. The key findings show that AI-driven discovery is fragmented by engine, source mix, location, and category.
This means that checking a brand's presence in one AI assistant may not provide a complete picture of its visibility across all AI platforms. The study highlights the importance of understanding how each AI system sources its information, as this can significantly impact the businesses it recommends. For instance, Gemini places a strong emphasis on business websites, while ChatGPT leans more towards Reddit and traditional directories.
These differences in source mix can lead to variations in the businesses that are highlighted by each AI assistant. Furthermore, the study found that repeated queries often produce different sources, a phenomenon referred to as "grounding drift." This variation in source alignment can result in instability in the top results generated by AI engines.
While the study does not directly link AI responses to increased conversions or overall ranking quality, it establishes a useful baseline for marketers to understand the limitations of AI-driven local business discovery. For small and medium-sized businesses, the findings suggest a more disciplined approach to evaluating AI visibility.
Rather than merely checking if a brand appears in AI assistants, businesses should monitor how consistently they are named and cited across different platforms. This involves testing multiple engines, using representative prompts, repeating queries over time, and recording both the named businesses and cited sources. By segmenting results by service category and market, businesses can identify areas for improvement and tailor their strategies accordingly.
While the study does not guarantee a universal optimization formula, it emphasizes the importance of monitoring the source environment when managing online visibility.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
