How to Get ChatGPT to Recommend Your Brand

Fifty-three percent of users distrust AI search results after ChatGPT recommended competitors to users seeking the best software providers, marketing agencies, or eCommerce platforms, according to a report by DesignRush News published August 10, 2026. This lack of confidence stems from perceived biases in how generative AI identifies and suggests industry leaders.

The data indicates a growing friction between how brands build authority and how AI models curate recommendations. While companies spend years establishing market presence, AI models may prioritize different data signals, leading to results that users find unreliable or skewed toward specific competitors.

User Distrust in AI-Driven Brand Recommendations

The DesignRush News report highlights that more than half of surveyed users do not trust AI search when it comes to selecting professional services. This distrust is specifically linked to instances where ChatGPT suggests competitors over established brands that users believe should be ranked higher.

The tension arises from the “black box” nature of AI recommendations. Unlike traditional search engines that provide a list of links for users to vet, AI search often provides a definitive answer or a short list, which users are increasingly questioning for accuracy and neutrality.

Impact on Software and Agency Discovery

The trend is particularly evident in high-stakes B2B categories, including software providers, marketing agencies, and eCommerce platforms. In these sectors, the cost of a wrong choice is high, making the 53% distrust rate a significant hurdle for AI adoption in the procurement process.

Brands with extensive experience are finding that historical reputation does not always translate into AI visibility. Because LLMs rely on training data and patterns rather than real-time verified credentials or updated portfolios, established firms may be overlooked in favor of competitors with a stronger digital footprint in the AI’s training set.

AI Search vs. Traditional Search Logic

Traditional search engines use indexed data and specific ranking factors to display a variety of options. AI search, however, synthesizes information to provide a direct recommendation. According to the DesignRush News findings, this synthesis is where users perceive a lack of objectivity.

When ChatGPT recommends a competitor, it may be based on the frequency of mentions across the web or specific phrasing in its training data, rather than a qualitative assessment of the provider’s actual performance or current market standing.

This discrepancy creates a gap in “AI visibility,” where the companies that are most respected by industry peers may not be the ones most frequently cited by generative AI tools.