The data: AI can both drive brand exploration and kill purchases.

• 57.5% of US adult AI users have decided against buying something based on AI advice and information, per Semrush, and 74.2% would be less likely to buy an item if a chatbot surfaced mixed or negative reviews.
• Conversely, another 57.5% have made a purchase based on an AI recommendation, and 59.3% have found a new brand or product through AI.

What it means: Product reviews, customer complaints, social presences, pricing information, creator commentary, and other web information can all shape AI-mediated purchase decisions.

That highlights a distinction between paid visibility and recommendation influence. A chatbot surfacing a negative review or an unfavorable product comparison can discourage a sale as easily as a positive recommendation can spur one.

However, AI ads, which are becoming more widely supported across key AI services like ChatGPT, may not be the answer. Some 41.6% of AI users dislike ads in chatbots, with 66.1% saying they sow doubt about the integrity of AI answers, per Semrush. That makes it crucial for brands to think beyond paid placements and owned content and to evaluate the body of public evidence available when shoppers ask AI if something is worth purchasing.

Recommendations for brands: Buying exposure doesn’t guarantee consideration.

• Ensure accurate information about product specs, use cases, pricing, and return policies is clearly available online for AI to pull from.
• Audit popular AI models on a monthly basis to understand the information they surface, as index practices and model behavior are quickly changing.
• Weigh the pros and cons of advertising inside of AI, considering the potential benefit of broad reach along with the risk of an AI recommendation seeming less credible or disingenuous.