What to ask before bringing AI grading into your district

Does it actually follow mathematical reasoning?

Generic AI tools scan for keywords and miss the reasoning. Ask any vendor to demonstrate on real handwritten student work: can it follow a multi-step solution, spot where the logic breaks, and award partial credit the way your teachers would? Ed.ai was built from the ground up for mathematical thinking, trained on 50,000+ math problems alongside math teachers.

Is it aligned to your state standards — by name?

“Standards-based” is not an answer. Ask which frameworks are mapped: California CCSS-M, Texas TEKS, North Carolina NCSCOS, Common Core across 40+ states. Every error Ed.ai identifies is tied to a specific standard, which is what makes department-level and district-level data actionable.

Who controls the grade?

The answer must be: the teacher. AI proposes, teachers decide — every score is reviewable and overridable, and the rubric belongs to the teacher. Adoption fails when tools position themselves as replacing professional judgment instead of accelerating it.

How is student data protected?

Require FERPA and COPPA compliance, adherence to your state’s student data privacy laws, and a contractual guarantee that student data is never used to train AI models. Ed.ai meets all of these — and your data protection officer can verify each claim before a single paper is scanned.

What does a pilot look like?

A serious pilot fits inside one grading cycle: a handful of math teachers, real assessments, five minutes to get started. Measure grading time, feedback quality, and teacher trust — then decide with evidence.