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Research·

What 3,735 students in 145 countries actually do with an AI tutor

Ten months of usage data on the formats students choose, the files they upload, and why both answers are older than the technology.

Every AI study tool is sold on the same promise: that learning is about to become immersive, gamified, generated. We build those things. We also watched what 3,735 students in 145 countries did when we put roughly three dozen of them on one screen and let people choose.

They chose flashcards.

Finding 1: given 27 formats, students picked the two oldest

Over ten months, students generated 1,688 study artefacts. They had their pick of immersive 3D worlds, interactive games, generated video, podcasts, live AI classes, exam simulators and more. Flashcards and mind maps account for 44% of everything made. Every immersive or game format combined accounts for less than 6%.

SHARE OF 1,688 GENERATED STUDY ARTEFACTS Flashcards 29.4% Mind map 14.6% Slides 10.0% Audio 7.7% Interactive lesson 5.5% Image generation 3.4% Quiz 2.9% Infographic 2.8% 3D world (advanced) 2.4% Exam simulator 2.0% 17 other formats 18.3% the two oldest study techniques = 44%

Flashcards and mind maps predate every technology on this page. They still win.

The pattern is not an artefact of one audience. Flashcards rank first in India, the United States, the Philippines and South Africa; in Egypt mind maps edge ahead, with flashcards immediately behind. Four very different markets, the same answer.

Finding 2: a quarter of what students hand an AI is a photograph

Of 4,939 files uploaded, 1,102 are images. Not documents: pictures. A page of a textbook, a whiteboard before it gets wiped, a handwritten problem set, a worksheet the teacher printed.

WHAT 4,939 UPLOADS ACTUALLY ARE PDF 59.7% PHOTOS 22.3% DOCX 7.9% · PPTX 7.5% · everything else 2.6% 1,102 photographs, from 269 students an average of 4 each; the five heaviest account for 7%

The camera roll is a study tool. Most software still assumes a file picker.

This is a broad behaviour rather than a handful of outliers: the photographs come from 269 separate students, averaging four each, and the five heaviest uploaders account for only 7% of the total. It is worth stating the limit precisely, though: those 269 students are 16.5% of the 1,628 people who uploaded anything. The right claim is that 22% of uploads are photographs, not that 22% of students photograph things.

What we think this means

The two findings point the same way. Students are not asking for a new medium. They are asking for a very old one, delivered faster, from whatever is in front of them.

That is an uncomfortable result for a company that builds 3D worlds, and we are publishing it anyway, because the alternative reading is worse: that the industry keeps building for a student who does not exist. The demand we can measure is for the boring thing, produced instantly, from a photograph taken thirty seconds ago in a classroom.

Two implications we would offer for anyone building in this space. First, image input is not an accessibility feature or a nice-to-have; on this evidence it is close to a quarter of your input volume, and a tool that only accepts documents is invisible to that behaviour. Second, novelty is not the same as demand. The formats that photograph well in a launch video are the ones our users generate least.

Methodology

  • Population. 3,735 individual accounts on iTutor's public platform, spanning 145 countries by signup region.
  • Window. 3 November 2025 to 27 August 2026, inclusive. All figures are cumulative over that period.
  • Finding 1 counts 1,688 study artefacts generated across 27 distinct formats. Each row is one artefact a student asked for. Institutional and corporate accounts are included; automated and internal test accounts are not.
  • Finding 2 counts 4,939 uploaded files, classified by detected file type at ingestion. "Photographs" means the image class, which covers camera captures and screenshots; we cannot separate those two, and the figure should be read as "images" rather than strictly "camera photos".
  • Suppression. No group smaller than 25 accounts is reported individually. Country-level observations are drawn only from the 22 countries at or above that threshold.
  • Anonymity. Every figure is an aggregate count. No individual, institution, document or message is identified, and no user content was read to produce this report.
  • What this cannot tell you. These are iTutor's users, not a random sample of students, and people who choose an AI study tool are not representative of students generally. The sample is modest and skews toward markets where we have distribution. Treat the direction as informative and the precise percentages as specific to this population.

CITE THIS

iTutor (2026). What 3,735 students in 145 countries actually do with an AI tutor. Retrieved from https://itutor.study/how-students-use-ai

We intend to repeat this annually at the same address, so the figures can be compared over time. If you are researching this area and want a cut of the aggregate data we have not published, write to us.