How accurate is AI marking?
AI marking accuracy depends on the task, mark scheme quality, handwriting clarity, subject, and teacher review.
Published 2026-05-19 · Updated 2026-05-19
AI marking accuracy is not one fixed number. It depends on the clarity of the mark scheme, the quality of the script image, the subject, the question type, and whether teachers review the output.
The mark scheme matters
AI-assisted marking performs best when the criteria are explicit and the teacher has checked the extracted scheme before marking starts.
- Structured mark schemes are easier to apply consistently.
- Ambiguous credit rules should be reviewed by the teacher.
- Teacher edits improve the final reliability of the class results.
Handwriting and scans affect confidence
Poor scans, missing pages, rotated scripts, and unclear handwriting can make any marking workflow less reliable.
- Use clear scans or photos where possible.
- Review low-confidence reads first.
- Keep the original script visible during review.
Accuracy should be managed through workflow
The key practical question is not whether AI is perfect. It is whether the tool surfaces uncertainty and lets teachers correct the final record.
Can AI marking be 100% accurate?
No marking workflow should be treated as perfect. MMT is designed so teachers review and adjust the AI draft before export.
What improves AI marking accuracy?
Clear mark schemes, readable scripts, question-level criteria, and careful teacher review all improve the reliability of the final marks.