Gemini gives a completely different description of my CEO than Google web results. What’s going on?

This is a common diagnostic question, and the answer is structural rather than a glitch: Gemini and a Google web-results page draw on different sources, so they can describe the same CEO in different terms. Gemini sits on Google’s infrastructure, it queries the Knowledge Graph for entity facts, and the Knowledge Graph itself draws on sources including Wikipedia. A standard Google web-results page reflects the wider live index, including recent news, trade coverage, and a company’s own pages that may not yet be reflected in those reference sources.

Why the two can diverge

• Gemini leans on the reference layer. Google’s Knowledge Graph aggregates information from sources including Wikipedia; Gemini draws on that reference layer when describing a person or company. Generative engines also synthesize from their training corpus plus live retrieval at query time, but for canonical entity facts, the Knowledge Graph layer is a primary input.
• Google web results draw on the wider index. The standard results page surfaces recent news, industry coverage, and a company’s own pages, material that can describe an executive’s current role before the reference sources have been updated to reflect it.
• A lag between the two opens the gap. If the Wikipedia article or Knowledge Graph entry is incomplete or out of date while the wider web has already moved on, Gemini can describe an older version of the executive while Google web results show the newer reality. The same lag can run the other way: the reference sources are current but the broader index has not caught up.

The fix is engine-specific

Because each engine relies on a different source, there is no single fix. We identify the gap separately for each engine to determine which source is feeding the description it returns, then target that source. Where Gemini appears to be drawing on an outdated reference record, the work focuses on the Knowledge Graph entry and the Wikipedia article that feed it. Where the gap runs the other way, the reference sources are current but the broader index is stale, the work targets the underlying coverage and the company’s owned content. AIQ pinpoints which engine is drawing on which source, so intervention is aimed at the source actually driving the gap rather than guessed at.