AI is getting facts wrong about your product
Wrong pricing, outdated features, or a misdescribed category — when AI engines get basic facts about a product wrong, it's rarely random. It's almost always traceable to stale, conflicting, or missing structured data somewhere the engine is reading from.
By Nithish Govindasamy · Updated August 2026
Where the wrong facts usually come from
- Stale schema or structured data — pricing or feature data that hasn't been updated to match the live site.
- Conflicting third-party listings — a directory or review site with outdated info the engine treats as a valid source.
- Missing machine-readable facts — information that exists on the site only as an image or in a format engines can't reliably extract.
How this gets fixed
Correct the structured data and the highest-traffic pages first, then run the same buyer prompts weekly to confirm the wrong answer actually clears — a fix that isn't re-verified is just a guess that it worked.
Frequently asked questions
- Why does this happen at all?
- Engines synthesize from whatever sources they can find — the site, directories, review platforms, old press coverage. If those sources disagree, or if the newest facts aren't in a machine-readable format, the engine can surface outdated or conflicting information.
- Can this actually be corrected?
- Yes, usually within weeks — updating structured data, refreshing key pages, and correcting third-party listings that carry stale facts closes most of the gap, since engines re-ground more often than classic search re-indexes.