Most tools that promise to build a quiz from a document do one thing when you upload a file: they pull the text layer out and hand that text to a language model. That works perfectly on a file exported from Word or Google Docs, because the text layer is right there. Hand the same tool a scan and it extracts nothing, because there is nothing to extract. The page is a picture. What you get back is an error, or worse, a set of generic questions invented from the filename and a few stray characters.
This is why so many teachers conclude that AI quiz tools do not work on their materials. The materials are fine. The pipeline was never built for paper. Anything that came from a copier, a departmental scanner, a phone camera, or a 1990s course pack lands in this category, and in a lot of school and training environments that is most of what people actually have.
Reading the page as an image instead solves it at the source. The page is interpreted the way a person reads it, so layout survives: a numbered list stays a numbered list, a table keeps its rows, a heading is still recognizably a heading. That structure matters more than it sounds, because questions written from a document that kept its shape follow the document's own logic rather than a flattened stream of words.
No OCR step
Upload the scan as it is. You do not need Acrobat, a separate OCR service, or a searchable-PDF conversion first.
No retyping
The alternative to a tool that reads scans is typing the handout back in by hand. On a ten page packet that is an evening.
Layout survives
Tables, numbered steps, and headings are read in place, so questions follow the structure of the original page.
Mixed packets work
A packet where some pages are scanned and some are digital is handled in one upload, not two workflows.