AI in Schools / State report
Virginia requires local AI policies with human safeguards
School boards must adopt policies consistent with state guidance. The framework covers student-data use, human decisions and teacher access to student-AI transcripts.
Published
Research as of · Sources & Notes
Current law or policy
State law and guidance
Virginia's updated education code requires each school board to establish, implement and enforce policies consistent with department guidance. Its framework addresses vendor training on student information, human judgment in consequential decisions, and teacher access to transcripts of student-AI interactions in approved instructional use. Families and students can ask how interactions are reviewed; teachers need access and an escalation route; school leaders should examine contract restrictions and actual transcript availability, not merely publish a principles statement. Fairfax illustrates a more restrictive device rule below. [19]
Where does each authority retain human judgment?
NYC, Utah and Virginia set different limits on AI decisions
NYC reserves decisions for qualified humans. Utah prescribes limits in model language. Virginia requires safeguards for consequential decisions.
NYC, Utah and Virginia set different limits on AI decisions. NYC reserves decisions for qualified humans. Utah prescribes limits in model language. Virginia requires safeguards for consequential decisions. New York City. Authority: District March 2026 guidance. Human-decision safeguard: Grading, placement and discipline remain with educators or other qualified humans. Scope: March guidance used in this report. The database’s separate 2026–27 directive has its own scope. Evidence state: first party guidance. Utah. Authority: HB273 prescribed model. Human-decision safeguard: The model bars educators from independent AI grading or high-stakes determinations. Scope: Required model language. The report does not establish individual local adoption. Evidence state: model required. Virginia. Authority: Updated state education code. Human-decision safeguard: Safeguards preserve human judgment in consequential decisions. Scope: School-board policies must follow department guidance. Evidence state: operative.
| Jurisdiction or item | Authority | Human-decision safeguard | Scope |
|---|---|---|---|
New York CityOfficial guidanceSource notesSource notes [8] | District March 2026 guidance | Grading, placement and discipline remain with educators or other qualified humans. | March guidance used in this report. The database’s separate 2026–27 directive has its own scope. |
UtahModel requiredSource notesSource notes [20] | HB273 prescribed model | The model bars educators from independent AI grading or high-stakes determinations. | Required model language. The report does not establish individual local adoption. |
VirginiaCurrent law or policySource notesSource notes [19] | Updated state education code | Safeguards preserve human judgment in consequential decisions. | School-board policies must follow department guidance. |
View data and source notes
| Item | Authority | Human-decision safeguard | Scope | Status | Sources |
|---|---|---|---|---|---|
| New York City | District March 2026 guidance | Grading, placement and discipline remain with educators or other qualified humans. | March guidance used in this report. The database’s separate 2026–27 directive has its own scope. | first_party_guidance | [8] |
| Utah | HB273 prescribed model | The model bars educators from independent AI grading or high-stakes determinations. | Required model language. The report does not establish individual local adoption. | model_required | [20] |
| Virginia | Updated state education code | Safeguards preserve human judgment in consequential decisions. | School-board policies must follow department guidance. | operative | [19] |
Fairfax does not approve general-purpose AI on district-issued student devices
Fairfax says it does not provide or approve student access to general-purpose GenAI on district-issued devices; its separate guide for personally owned devices says the teacher's assignment rules come first and advises asking a caregiver before creating an account. Boston's TECH-06 policy and spring 2026 policy call for privacy-impact assessment, approved tools and family information. DCPS's AUP addresses approved student-learning tools and staff expectations; its annual enrollment acknowledgement is receipt of a policy, not a standalone consent to AI use. Together these cases show why device control, product approval and parental permission must be separate database fields. [26][13][23][14]
Which operational limit applies in each district?
Device rules, tool approval and family choice remain separate
Seattle, Fairfax, Boston and DCPS describe different operational safeguards. A policy acknowledgement does not itself establish AI consent.
Device rules, tool approval and family choice remain separate. Seattle, Fairfax, Boston and DCPS describe different operational safeguards. A policy acknowledgement does not itself establish AI consent. Seattle. Operational boundary: Attribution, responsible use and protection of student data. Family or assignment limit: A restricted-network request is a general mechanism, not an AI-specific opt-out. Evidence state: district procedure. Fairfax. Operational boundary: No provided or approved general-purpose GenAI access on district-issued student devices. Family or assignment limit: Personal devices follow teacher assignment rules. The guide advises asking a caregiver before account creation. Evidence state: district device scope. Boston. Operational boundary: Privacy-impact assessment, approved tools and family information. Family or assignment limit: TECH-06 and the spring 2026 policy supply the district context. Evidence state: district policy. DCPS. Operational boundary: Approved student-learning tools and staff expectations. Family or assignment limit: Annual enrollment acknowledgement records policy receipt. It is not standalone AI consent. Evidence state: district aup.
| Jurisdiction or item | Operational boundary | Family or assignment limit |
|---|---|---|
SeattleDistrict procedureSource notesSource notes [10] | Attribution, responsible use and protection of student data. | A restricted-network request is a general mechanism, not an AI-specific opt-out. |
FairfaxDistrict device rulesSource notesSource notes [26] | No provided or approved general-purpose GenAI access on district-issued student devices. | Personal devices follow teacher assignment rules. The guide advises asking a caregiver before account creation. |
| BostonDistrict policy | Privacy-impact assessment, approved tools and family information. | TECH-06 and the spring 2026 policy supply the district context. |
DCPSDistrict acceptable-use policySource notesSource notes [14] | Approved student-learning tools and staff expectations. | Annual enrollment acknowledgement records policy receipt. It is not standalone AI consent. |
View data and source notes
| Item | Operational boundary | Family or assignment limit | Status | Sources |
|---|---|---|---|---|
| Seattle | Attribution, responsible use and protection of student data. | A restricted-network request is a general mechanism, not an AI-specific opt-out. | district_procedure | [10] |
| Fairfax | No provided or approved general-purpose GenAI access on district-issued student devices. | Personal devices follow teacher assignment rules. The guide advises asking a caregiver before account creation. | district_device_scope | [26] |
| Boston | Privacy-impact assessment, approved tools and family information. | TECH-06 and the spring 2026 policy supply the district context. | district_policy | [13][23] |
| DCPS | Approved student-learning tools and staff expectations. | Annual enrollment acknowledgement records policy receipt. It is not standalone AI consent. | district_aup | [14] |
Sources & Notes
This report reflects research as of October 6, 2026. Reference numbers link to the cited publications.
The August tracker counts describe its historical snapshot. The reviewed policy database has a separate scope and release date. Neither is a census of classroom AI use.
- Guidance on Artificial Intelligencewww.schools.nyc.gov
- Policies : 2022SP Electronic Resources/Use of the Internet - Seattle Public Schoolswww.seattleschools.org
- Policieswww.bostonpublicschools.org
- Student and Staff Technology and Network Acceptable Use Policydcps.dc.gov
- Code of Virginia (2026 Updates)law.lis.virginia.gov
- HB0273le.utah.gov
- Clean Copy of FINAL_Redline V7 DRAFT AI Policy (for SC)resources.finalsite.net
- Student Guide: Artificial Intelligencewww.fcps.edu
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