The way consumers shop is undergoing a seismic shift, driven by the rapid adoption of Large Language Models (LLMs) like ChatGPT, Copilot, and Gemini. These AI tools are no longer just answering questions. they’re actively influencing purchasing decisions, often before shoppers even visit a brand’s website. But a new report from Rithum reveals a critical challenge: trust.

The Erosion of Brand Trust in the AI Era

According to the Rithum report, 58% of shoppers lose trust in a brand when AI provides inaccurate product information. A significant 16% will abandon the purchase altogether. This highlights a growing concern: AI’s influence is powerful, but its accuracy is paramount. The stakes are high, as shoppers are increasingly relying on AI for product research and comparison.

The impact isn’t uniform. Shoppers aged 18-27 are particularly susceptible, with 64% acting on AI recommendations without further verification. This trend is even more pronounced among higher-income households, where 84% have used an LLM in their shopping journey.

The Rise of “Agentic Commerce” and the Data Imperative

This shift marks the emergence of “agentic commerce,” where AI acts as an intermediary between consumers and brands. However, the report underscores that product data quality is now a key competitive advantage. Brands that fail to provide accurate, consistent information risk being overlooked – or worse, actively losing customers to competitors.

Interestingly, when shoppers do verify AI recommendations, a mere 5% head directly to the retailer’s website. The vast majority – 95% – turn to search engines, reviews, or personal networks. This suggests that brands are losing control of the discovery process and need to focus on dominating search results and building strong reputations.

AI as a Brand Discovery Tool – and a Risk for Established Names

The report reveals a surprising trend: 1 in 5 shoppers have purchased from a brand they’d never heard of solely based on an AI recommendation. This demonstrates AI’s potential to level the playing field, allowing smaller brands to gain visibility and compete with established industry giants.

Price and Accuracy: The Cornerstones of AI Trust

Even as AI considers various factors, price accuracy is the most critical element for shoppers. 67% prioritize accurate pricing in AI recommendations, followed by product reviews (35%) and availability (34%). Nearly half (44%) of shoppers believe AI tools need to improve their accuracy regarding product details like price and availability.

What Brands Need to Do Now

The Rithum report emphasizes the need for brands to proactively address the challenges of agentic commerce. This includes:

• Prioritizing Product Data Quality: Ensuring accurate, consistent, and up-to-date product information across all channels.
• Optimizing for AI Discovery: Understanding how AI algorithms interpret product data and tailoring content accordingly.
• Monitoring AI Recommendations: Actively tracking how brands are being represented by AI tools and addressing any inaccuracies.
• Investing in AI-Powered Solutions: Leveraging AI to improve product categorization, profitability benchmarking, and overall commerce operations.

Frequently Asked Questions (FAQ)

As AI continues to reshape the commerce landscape, brands that prioritize trust, accuracy, and data quality will be best positioned to thrive in this new era of agentic shopping.

Learn more about the report: The New Discovery Engine.