Here's the trend most B2B sellers haven't fully registered yet.
B2B buyers are increasingly researching suppliers via AI tools (ChatGPT, Perplexity, Gemini) before they ever visit a vendor's website. They're asking AI assistants to find products, compare suppliers, and surface the right SKUs for their requirements.
If your B2B catalog isn't structured, indexed, and exposable to these tools, you're invisible in the channel where your buyers are starting their journey.
This is showing up in two ways:
Natural-language search on your own platform. Buyers searching for "stainless 10mm outdoor bolts" instead of a part number should get the right result without needing to know your taxonomy. AI-driven semantic search makes this work even in large, complex catalogs.
AI catalog exposure externally. Structuring your product data so AI shopping tools and assistants can surface your catalog in response to buyer queries. This is a new distribution channel that didn't exist three years ago and is growing fast.
In both cases, the underlying requirement is the same: clean, complete, well-structured product data. AI search built on incomplete or inconsistent catalog data still fails.
The brands investing in catalog data quality and AI-ready product structure today are building a discovery advantage that will compound for years.