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Every week brings a new AI product promising to transform teaching. School leaders face a market that is crowded, fast-moving and full of confident claims. Buying well requires a disciplined process. This AI procurement checklist for schools is designed for heads of school, IT leaders and academic directors who need to evaluate AI platforms quickly without missing what matters.
1. Learning Value
- What specific problem does this solve for our students or teachers?
- Is there independent evidence, not just vendor case studies?
- Does it support our pedagogy, or require us to change it to fit the product?
- Can teachers control when and how students use it?
2. Data Protection and Security
- Where is data processed and stored? Is in-region hosting available?
- Is our data used to train models? Get a contractual “no.”
- Which sub-processors and model providers are involved?
- Does it support single sign-on, role-based access and audit logs?
- How are breaches reported, and how quickly?
3. Safety and Age-Appropriateness
- What content filters exist for student-facing features?
- Is the product designed for the age group we serve?
- Can we review student interactions when safeguarding requires it?
4. Accessibility and Language
- Does it meet accessibility standards for students with disabilities?
- How well does it work in the languages our students and families use?
5. Total Cost
- What is the per-user price after any free or pilot period?
- Are there usage caps, overage charges or premium tiers for key features?
- What training, integration and support costs will we carry internally?
6. Exit and Portability
- Can we export all our data and content in standard formats?
- What happens to our data at contract end, and when is it deleted?
- Are we locked into multi-year terms?
7. Vendor Stability and Support
- How long has the company existed, and how is it funded?
- Is there local or time-zone-appropriate support?
- How often does the product change, and how are schools notified?
The Equity Dimension
Free tools are tempting for budget-constrained schools, but “free” often means data monetisation or weak protections. School groups and ministries can level the field by negotiating framework agreements that smaller schools can join on the same terms as large ones.
A Simple Scoring Method
Score each section from one to five, set minimum scores for data protection and safety, and require two independent reviewers. Any product below the minimum on protection does not proceed, regardless of features.
Frequently Asked Questions
What should schools check before buying AI software?
Learning value, data protection, safety, accessibility, total cost, exit terms and vendor stability.
Should schools use free AI tools?
Only after reviewing their data terms. Free tools may use data in ways that are inappropriate for students.
Who should be involved in AI procurement?
Academic leaders, IT, data protection, finance and representative teachers.
