The way people shop is changing fast. AI-assisted shopping traffic to retail sites surged between 2024 and 2025, and 42% of consumers now use AI tools as part of their shopping journey. Another 17% have already turned to AI for product recommendations — a clear signal that product discovery is being reshaped in real time.
The bigger question isn’t whether shoppers are using AI. It’s what determines which products AI chooses to recommend.
Research from Google, Microsoft, and emerging AI visibility studies points to the same conclusion: AI systems favor products backed by complete content, rich media, ratings and reviews, and trusted product data. AI doesn’t browse PDPs like a shopper — it evaluates structured facts and trust signals. Products with incomplete or inconsistent content are far less likely to be surfaced, compared, or recommended.
The good news? The same content foundation driving digital shelf performance today is the foundation for AI visibility tomorrow.
Join us to learn what AI systems actually use to understand and recommend products, where most brands have content gaps, and how to build a practical roadmap to becoming AI-ready.
What You’ll Learn
- What new research reveals about how AI chooses which products to recommend
- Why attributes, images, video, and reviews are critical inputs for AI-driven discovery
- The most common content gaps limiting AI visibility today
- How governance, enrichment, and syndication contribute to AI readiness
- A practical framework for assessing your catalog and prioritizing what drives results