58% of Shoppers Lose Brand Trust over Faulty AI Suggestions

Why It Matters

Faulty AI recommendations erode brand trust, turning data quality into a competitive advantage. Brands that ensure accurate, consistent product information can retain shoppers and capture AI‑driven discovery growth.

Key Takeaways

• 58% blame brand for faulty AI recommendations
• 70% UK shoppers used AI for shopping recently
• Only 5% verify AI info on retailer sites
• Price accuracy most critical factor for AI suggestions
• 1 in 5 bought unknown brand via AI

Pulse Analysis

Agentic commerce—where shoppers rely on AI agents to surface and compare products—has shifted the trust equation from brand reputation to data fidelity. As Rithum’s report reveals, a majority of consumers now attribute AI missteps to the retailer, making inaccurate product details a direct threat to loyalty. This dynamic is especially pronounced in the United Kingdom, where 70% of respondents have engaged with AI tools for shopping within the last quarter, yet the conversion funnel remains largely manual, with under 15% completing purchases through the AI interface.

For brands, the findings underscore the strategic imperative of mastering product information management. Price emerges as the single most important attribute for AI recommendations, with 67% of shoppers insisting on price accuracy, while 44% call for better data on availability and details. The verification window is strikingly narrow—only 5% of shoppers cross‑check AI suggestions on the retailer’s own site—meaning that any data error can cement a negative perception before the brand even has a chance to intervene. Companies that invest in centralized, real‑time product data platforms can ensure consistency across marketplaces, search, and emerging AI agents, safeguarding trust and reducing churn.

Conversely, the AI surge offers a foothold for emerging brands. The study notes that one in five shoppers purchased from a previously unknown label after an AI recommendation, and 64% of 18‑27‑year‑olds act on AI suggestions without further verification. To capitalize, smaller players should prioritize high‑quality, price‑accurate feeds and leverage AI‑friendly content structures. Meanwhile, established retailers must audit and enrich their product catalogs, adopt automated price monitoring, and embed AI‑ready metadata. As AI continues to dominate the discovery phase, brands that treat product data as a core asset will not only protect trust but also capture the growing share of AI‑driven sales.