How to evaluate AI vendors for schools

Quick answer

Districts should evaluate AI vendors by data handling, training terms, security posture, teacher oversight, student guardrails, auditability, implementation support, and proof from real classroom pilots.

Set the district expectation

Start by naming what AI vendor evaluation for schools should accomplish for students and teachers. The strongest AI rollout language is specific enough for classrooms and plain enough for families, administrators, and support staff to understand.

• Ask what student data is collected.
• Confirm whether data trains models.
• Review subprocessors and retention.

Turn the expectation into a workflow

Policy only helps when teachers can use it during normal class work. Connect the rule to approved tools, student account handling, teacher visibility, and a response path for confusion or misuse.

• Check classroom-level controls.
• Require teacher-visible student activity.
• Test support and escalation paths.

Review before expanding

A district should treat early AI use as an evidence-gathering pilot. Check whether the workflow protects privacy, keeps students learning, and gives teachers enough context to intervene without adding heavy monitoring work.

• Pilot before broad procurement.
• Review legal and privacy documents.
• Compare evidence, not demos.

District review points

• Data collection
• Training terms
• Subprocessors
• Security review
• Teacher oversight
• Student guardrails
• Pilot proof

Frequently asked questions

What should districts ask every AI vendor?

Ask what student data is collected, whether it trains models, who can access student activity, how data is deleted, and how teachers supervise classroom use.

Should districts pilot before buying?

Yes when possible. A pilot reveals classroom fit, teacher support needs, student behavior patterns, and privacy questions before district-wide rollout.