Google Docs AI Scanning Feature Is Slow and Unreliable
Google Docs AI scanning takes 5-10 seconds per page and frequently fails, causing users to revert to manual photo capture. Reported as a significant regression.
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Similar Problems
surfaced semanticallyGoogle Docs AI Document Scan Feature Regresses in Accuracy and Speed
A Google Docs user reports that a recent update degraded the AI document-scanning feature, making scans slower and less precise, while a UI redesign hid the frame-correction control behind the close button. The user, a longtime fan of the app, is frustrated that the regression apparently wasn't caught before release.
AI-Enhanced Document Scanning Introduces Upload and Orientation Glitches
Since a word-processing app added AI-powered scanning features, users report the app falsely claiming documents were uploaded when they weren't, and pages being rotated upside-down during scanning. This undermines trust in a core everyday workflow of digitizing paper documents.
Google Docs Mobile Scanner Severely Slowed by Update
The document scanning feature in Google Docs mobile app became significantly slower after a recent update. Users who previously relied on fast scanning for document capture now face degraded performance. Vendor-specific regression with no user workaround.
Google Drive Document Scanning Produces Blurry Output After Recent Update
A Google Drive update broke the built-in document scanning feature, causing pages to render blurry and applying incorrect filters automatically. Users cannot stop the incorrect processing mid-scan. The feature is now entirely unreliable for document capture.
Google Docs Scan-to-Save Feature Fails With Generic Error
Users of Google Docs' document scanning feature report a persistent 'something went wrong' error that prevents scanned documents from being saved, with the reporter noting the same failure is widely reported by other users online. This breaks a core mobile capture workflow while offering no actionable error detail to work around it. The consistency of the reports across users suggests a systemic bug rather than a device-specific issue.
Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.