Google AI Critiques Brands More Than ChatGPT, According to BrightEdge

Google AI Critiques Brands More Than ChatGPT, According to BrightEdge

A recent report from BrightEdge reveals a marked trend in how Google and ChatGPT's AI summaries treat brands. According to the study, Google’s AI summaries are 44% more likely to express a negative sentiment towards brands compared to ChatGPT. This analysis is based on the examination of hundreds of millions of queries and digital data collected between mid-January and February 2026.

While the majority of brand mentions are positive or neutral, the 2.3% of negative mentions on Google and 1.6% on ChatGPT could be seen by millions of users each month. Jim Yu, CEO of BrightEdge, emphasized that AI, unlike traditional search, expresses an opinion, fundamentally transforming marketing.

A spokesperson for Google criticized the report, calling it "flawed methodology" and claiming that the sentiment difference noted is less than one percentage point. According to him, AI summaries simply reflect existing web content. OpenAI, for its part, has not commented on these findings.

New Marketing Strategies in Response to Evolving AIs

As AI chatbots evolve, brands are adapting their marketing strategies. They are turning to innovative techniques such as Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) to ensure precise and prominent visibility on these platforms. This field is rapidly changing, with AI models being continuously trained and updated, complicating the development of GEO strategies for many companies.

The Impact of Recent Events on AI Critiques

The study reveals that Google is more likely to criticize brands following recent news events or controversies. In contrast, ChatGPT displays a lower overall negativity rate, but this rate increases when users evaluate products, particularly before a purchase.

BrightEdge identified that brand controversies and legal issues are the main triggers of negative sentiment, representing 32% of cases. Other factors include product limitations (21%), safety concerns or recalls (17%), and service outages (11%).

Jim Yu also noted that even old negative stories can influence AI responses. He recommends that companies regularly produce new content, as "AI likes to find the most recent information." Yu also suggests encouraging customers to leave positive reviews and targeting the sources most cited by AI engines to optimize their online presence.