AI marking should not be designed as a black box that directly becomes the final grade.
A better workflow is: student submits work, the system extracts text, the model proposes a mark and feedback, then the teacher reviews and approves the final result.
That gives the system speed without removing accountability. It also creates useful data: where the model was accepted, where it was corrected, and which question types need better grading rules.