AI Policy and Guidance Template for K-12 Education
Published April 8, 2026 at 7:00 p.m. CT by the Mississippi Artificial Intelligence Network.
Mississippi Artificial Intelligence Network
AI Policy and Guidance Template for K-12 Education
A practical framework for schools, districts, and education agencies developing local guidance for AI in instruction, operations, student safety, data stewardship, and procurement.
What this is
A planning and governance template for developing institution-specific K-12 AI policy and guidance.
Who it is for
School boards, superintendents, district leaders, principals, educators, technology leaders, and other school-system stakeholders.
How to use it
Adapt the sample language to local mission, grade spans, legal obligations, community expectations, and technology capacity.
AI governance in K-12 education
AI can support teaching, learning, accessibility, school operations, and staff capacity. Its use also creates decisions about student safety, academic integrity, privacy, cybersecurity, procurement, equity, and age-appropriate access.
The policy objective is to enable legitimate educational innovation while protecting students, institutions, data, systems, and educator judgment through proportionate governance.
How to Use This K-12 AI Policy Template
Use the template to organize local decisions, draft enforceable policy language, and separate durable policy from procedures and tool-specific guidance.
Adapt each section to local grade spans, approved uses, prohibited uses, data rules, and review authority.
Approve the final policy through the appropriate governance process, train users, and schedule recurring review.
K-12 AI Policy Template: Policy, Guidance, Procedures, and Best Practices
Before drafting local language in your K-12 AI policy template, it is important to distinguish between these four document types. Most school systems will need all four.
Policy
Sets formal expectations, boundaries, authority, and accountability, including who can approve AI-related decisions, which uses are prohibited or restricted, what review processes apply, and how compliance expectations will be handled.
Guidance
Explains how to interpret policy in practice. Usually more flexible than policy and easier to update as AI tools and use cases evolve.
Procedures
Describe the steps staff must follow, such as how to request approval for a tool, how to complete a privacy review, how to escalate incidents, or how a vendor is evaluated.
Best Practices
Recommended approaches and examples, including model disclosure language for classroom use, staff verification routines, accessibility checks, family communication suggestions, and age-appropriate use examples.
Foundation
Core Design Principles for a K-12 AI Policy Template
When developing an AI policy and guidance template for K-12 education, schools and districts should consider a set of core principles that can guide decision-making across all use cases.
Educational purpose first: AI should serve a legitimate educational, operational, or support purpose.
Human responsibility remains central: Humans should remain accountable for consequential decisions.
Student safety, privacy, and dignity are essential: Treat these as foundational, not optional.
Age-appropriateness matters: Expectations for elementary, middle, and high school students should not be identical.
Build in accessibility and inclusion from the start: AI use should support broad participation and meaningful access.
Transparency is important: Schools should be able to explain which AI tools they use, why they use them, and what safeguards apply.
Evidence should matter: Districts should not rely on vendor claims alone.
Continuous review is necessary: AI governance should be iterative, not static.
To define authority, accountability, review structures, and governance processes for AI and generative AI across the school system.
Key Questions to Consider
Who owns districtwide or schoolwide AI governance?
Which uses require central approval, school-level approval, or educator discretion?
How will high-risk uses be identified and reviewed?
How often will guidance be reviewed and updated?
Sample Guidance Language
“Artificial intelligence tools and systems may be used only in ways that align with the school system’s educational mission, applicable law, board policy, student safety expectations, and approved technology governance processes. The district or school shall maintain a cross-functional AI governance process to evaluate instructional, operational, privacy, security, accessibility, and ethical considerations before authorizing higher-risk uses.”
Implementation Considerations
Schools and districts may wish to establish an AI steering committee, task force, or review council that includes leadership from curriculum and instruction, information technology, privacy, legal, cybersecurity, special education, student services, assessment, procurement, communications, and school administration.
Common Pitfalls
Treating AI as only a technology issue
Allowing fragmented adoption across schools or departments
Focusing only on classroom tools and ignoring operations, HR, communications, and student support
Having no formal process for escalation or review
Stakeholders to Involve
Superintendent or head of school, district cabinet, principals, curriculum leaders, CIO or CTO, privacy officer, legal counsel, special education leaders, assessment leaders, student services, communications staff, educators, students where appropriate, families, and governing boards.
2
Stakeholder Engagement and Collaborative Decision-Making
Purpose
To ensure AI-related decisions reflect educational values, community expectations, instructional realities, and practical concerns.
Key Questions to Consider
Who needs to be consulted before AI-related guidance is finalized?
How will educators, students, staff, and families provide input?
How will the school system communicate changes and gather feedback?
How will disagreement or concern be handled?
Sample Guidance Language
“The school system will engage educators, students, families, staff, and community stakeholders in the development and review of AI-related policy and guidance. The district or school will communicate clearly about approved uses, known risks, privacy considerations, and opportunities for feedback.”
Implementation Considerations
Districts should create a stakeholder engagement plan that includes staff listening sessions, family-facing FAQs, school leader briefings, student input where appropriate, and periodic review opportunities.
Common Pitfalls
Drafting AI guidance without classroom educators
Failing to communicate with families until after implementation
Using language that is too technical or vague
Excluding students from discussions about student-facing tools
Stakeholders to Involve
Teachers, principals, school counselors, paraprofessionals, librarians, students where appropriate, families, community representatives, communications staff, and employee representatives where relevant.
3
Balancing Innovation, Student Safety, Instructional Value, Educator Autonomy, and Responsible Use
Purpose
To help schools and districts avoid both unrestricted adoption and blanket prohibition by taking a balanced, educationally grounded approach.
Key Questions to Consider
What educational or operational problem is AI intended to address?
What actual value does the tool provide?
Where should caution take priority over speed?
When should educator autonomy be preserved?
Sample Guidance Language
“The school system seeks to support responsible innovation while safeguarding students and preserving professional judgment. AI tools may be explored where they improve teaching, learning, access, efficiency, or support services, but they shall not replace required human judgment in matters involving student safety, discipline, grading, placement, eligibility, or other high-stakes decisions unless explicitly authorized and reviewed.”
Implementation Considerations
Districts should define categories such as encouraged uses, allowed uses with conditions, restricted uses, and prohibited uses. They should also clarify that the presence of a tool does not automatically justify its use.
Common Pitfalls
Adopting AI because it is available rather than because it is useful
Over-automating decisions that require human context and judgment
Creating pressure for educators to use AI in ways that conflict with sound pedagogy
Ignoring accuracy, bias, and overreliance risks
Stakeholders to Involve
Instructional leaders, teachers, student services leaders, legal counsel, privacy and security leaders, governing board members, students where appropriate, and families.
4
Age-Appropriateness and Developmental Considerations
Purpose
To ensure AI expectations are developmentally appropriate and aligned with student age, maturity, and learning needs.
Key Questions to Consider
Which AI uses are appropriate by grade band?
When should AI use be teacher-mediated rather than student-directed?
What supervision is needed for younger students?
What differences should exist across elementary, middle, and high school?
Sample Guidance Language
“AI-related expectations shall be developmentally appropriate. For younger students, educator-mediated access and use should be prioritized whenever feasible. Independent student use of AI tools should occur only when age, maturity, supervision, tool design, and applicable legal or contractual requirements support such use.”
Implementation Considerations
Districts may wish to structure expectations by grade band. Elementary use may focus on educator-mediated exposure and foundational AI literacy. Middle school may involve structured and supervised use. High school may allow broader responsible use with stronger expectations for disclosure, verification, and appropriate academic use.
Common Pitfalls
Applying adult workplace norms to children
Allowing students to use tools that are not designed for their age group
Ignoring developmental implications such as overreliance or reduced persistence
Using the same communication strategy for all grade levels
Stakeholders to Involve
Elementary and secondary leaders, curriculum leaders, counselors, family engagement staff, privacy leaders, legal counsel, educators, and families.
5
Teaching, Learning, Curriculum, and Instruction
Purpose
To define how AI may support high-quality teaching and learning without undermining rigor, professional judgment, or instructional goals.
Key Questions to Consider
Which instructional uses are encouraged, allowed with conditions, restricted, or prohibited?
How may educators use AI for planning, differentiation, feedback, accessibility, or communication?
How will AI-generated instructional materials be reviewed before use?
What AI literacy should students learn?
Sample Guidance Language
“Educators may use approved AI tools to support planning, differentiation, accessibility, communication, and administrative efficiency, provided that instructional decisions remain grounded in professional judgment, content standards, student needs, and district curriculum expectations. AI-generated instructional materials must be reviewed for accuracy, bias, age appropriateness, accessibility, and alignment before use with students.”
Implementation Considerations
Districts should distinguish between AI for teacher productivity, AI for student-facing support, AI embedded in existing platforms, and AI for content generation or adaptation. Expectations should be clear that AI output must be reviewed by a qualified human before use.
Common Pitfalls
Using AI-generated materials without review
Weakening rigor by allowing AI to replace student thinking
Failing to teach source evaluation, bias awareness, and verification
Relying on vendor claims of personalization without oversight
Stakeholders to Involve
Curriculum leaders, instructional coaches, teachers, digital learning staff, librarians, special education leaders, English learner leaders, assessment leaders, and students where appropriate.
6
Assessment, Grading, and Academic Integrity
Purpose
To establish clear expectations about appropriate and inappropriate AI use in student work, assessment design, and educator practice.
Key Questions to Consider
When must student AI use be disclosed?
What forms of AI support are allowed for specific assignments or assessments?
How should assessment design change in response to AI?
How will academic integrity concerns be investigated fairly?
Sample Guidance Language
“Schools and educators shall clearly communicate expectations for AI use in assignments and assessments. Acceptable use may vary by grade level, subject, and learning objective. Students may be required to disclose, describe, or cite their use of AI tools when directed by the teacher or school. Automated AI-detection tools shall not be used as the sole basis for disciplinary or grading decisions.”
Implementation Considerations
Districts should support assessment redesign where older task formats are less valid in an AI-rich environment. Guidance should emphasize assignment-level clarity, authentic assessment strategies, and due process for academic integrity concerns. MAIN’s evidence guide to AI detection and verifying learning explains the research and a practical review process.
Common Pitfalls
Assuming AI detectors are accurate enough for discipline
Using inconsistent rules across classrooms or schools
Students: Responsible Use, Digital Citizenship, and AI Literacy
Purpose
To define what students should know about AI, how they may use it, and what boundaries apply.
Key Questions to Consider
What baseline AI literacy should all students receive?
How will students learn about misinformation, hallucinations, bias, and source evaluation?
How will student acceptable use expectations address AI specifically?
What supports are needed for younger students and students with differing needs?
Sample Guidance Language
“Students shall use AI tools in ways that are honest, safe, respectful, and consistent with instructional expectations. Students may not use AI to harass, impersonate, create harmful or deceptive content, bypass learning expectations, or disclose personal or sensitive information in violation of school rules or law.”
Implementation Considerations
Districts should include AI literacy within digital citizenship, media literacy, and responsible technology use. Students should learn how AI works at a basic level, what its limitations are, how to verify outputs, and how to use it responsibly in academic and civic contexts.
Common Pitfalls
Focusing only on misuse and not on literacy
Assuming students understand tool limitations
Ignoring peer harm, impersonation, and synthetic media misuse
Failing to address privacy or civic implications
Stakeholders to Involve
Teachers, librarians, curriculum leaders, school counselors, digital citizenship leads, student services, students, and families.
8
Teachers, Instructional Staff, Support Staff, and Administrative Staff
Purpose
To clarify how employees may use AI in planning, communication, support services, administrative work, and operational workflows.
Key Questions to Consider
What employee uses are permitted, restricted, or prohibited?
What information may never be entered into public or unapproved AI tools?
What review and verification expectations apply?
How will staff training be provided?
Sample Guidance Language
“Employees may use district-approved AI tools to support professional tasks such as planning, drafting, summarizing, translation, data organization, and communication preparation, provided they do not input confidential, protected, or otherwise restricted information into unapproved systems and they remain responsible for the accuracy, legality, accessibility, and appropriateness of final work products.”
Implementation Considerations
Districts should distinguish between approved enterprise tools, district-managed tools embedded in existing platforms, and public consumer tools. Expectations should address confidentiality, records retention, accessibility, communications quality, and mandatory human review.
Common Pitfalls
Entering student information into public tools
Using AI outputs in family communication without verification
Using AI to support sensitive personnel or student decisions without review
Rolling out expectations without adequate training
Stakeholders to Involve
Teachers, paraprofessionals, school leaders, counselors, registrars, HR, communications staff, IT staff, legal counsel, and privacy leaders.
Local and self-hosted models
“District IT and technical staff may run open-source or self-hosted AI models on district-controlled, offline hardware for evaluation and learning without tool-by-tool approval, as long as no student or district data leaves that hardware and the work stays exploratory. Student records and other regulated data follow their normal rules, downloaded models come from reputable sources, and any move toward classroom or operational use goes through normal review.”
9
Student Data Privacy and Information Governance
Purpose
To ensure AI use aligns with student privacy expectations, records governance, data minimization, access controls, and lawful handling of information.
Key Questions to Consider
What student data may be used in AI systems?
What contractual, technical, and legal safeguards are required?
How are data retention, deletion, and secondary use addressed?
When should privacy officers or legal counsel be involved?
Sample Guidance Language
“District personnel shall not disclose student education records, personally identifiable information, or other protected student data to AI tools or services unless the disclosure is authorized by law, district policy, and contract, and the district has completed required privacy and security review.”
Implementation Considerations
Schools should require privacy review before approving tools that process student information. Districts should examine what data is collected, how it is stored, whether it is used for training or product improvement, how long it is retained, and whether the vendor contract includes enforceable limitations.
Common Pitfalls
Assuming a tool is safe because it is widely used
Relying only on a privacy policy without contract review
Overlooking model training or secondary-use practices
Confusing anonymized, de-identified, and identifiable data
Stakeholders to Involve
Privacy officer, legal counsel, IT and security leaders, procurement staff, curriculum leaders, special education leaders, registrars, and communications staff.
10
Cybersecurity and Operational Resilience
Purpose
To address AI-related cybersecurity risks, including phishing, impersonation, unauthorized access, data exposure, and service disruption.
Key Questions to Consider
How does AI change phishing, impersonation, and fraud risk?
How will AI-enabled systems be secured before deployment?
How are incidents reported, investigated, and communicated?
What logging, access control, and monitoring requirements apply?
Sample Guidance Language
“AI-enabled systems must meet district cybersecurity requirements before deployment. The district shall assess identity, access, logging, vendor security, data flow, incident response, and continuity considerations for AI-enabled products and services.”
Implementation Considerations
Districts should integrate AI governance with broader K-12 cybersecurity planning. AI-related review should include third-party integrations, account security, access controls, logging, incident handling, and business continuity expectations.
Common Pitfalls
Ignoring AI-enabled phishing and social engineering threats
Failing to assess third-party integrations
Having no incident response workflow for AI-related harms or failures
Treating cybersecurity as separate from student safety
Stakeholders to Involve
CIO or CTO, cybersecurity leaders, incident response team, superintendent or designee, legal counsel, communications staff, principals, and privacy leaders.
11
Student Safety and Well-Being
Purpose
To address harmful content, manipulation, harassment, impersonation, surveillance, and other risks that may affect student safety or well-being.
Key Questions to Consider
What student-facing AI uses create elevated safety risks?
How will the district respond to synthetic media misuse, impersonation, or bullying?
What limits should apply to surveillance or behavior-inference tools?
How should schools communicate with families after incidents?
Sample Guidance Language
“The district prohibits the use of AI to create or distribute deceptive, harmful, harassing, discriminatory, or exploitative content involving students, staff, or community members. Student-facing AI systems that may affect well-being, safety, discipline, or intervention decisions shall be subject to heightened review and human oversight.”
Implementation Considerations
Districts should address prevention, response, and education. This includes student digital citizenship, staff escalation protocols, family communication pathways, and heightened scrutiny for tools that claim to infer emotion, intent, or risk.
Common Pitfalls
Adopting surveillance-oriented tools without evidence or oversight
Handling synthetic media misuse only as discipline rather than prevention and education
Confusing automated flags with verified facts
Failing to coordinate communications after incidents
Stakeholders to Involve
Student services, counselors, school safety leaders, principals, legal counsel, privacy officer, communications staff, educators, families, and students where appropriate.
12
Family and Community Communication
Purpose
To maintain trust, transparency, and clarity about how AI is used across the school system.
Key Questions to Consider
What should families know about approved AI uses?
When should schools provide notice about student-facing AI?
How will questions, complaints, or concerns be addressed?
How will messaging differ by grade level or use case?
Sample Guidance Language
“The school system will communicate in plain language about approved AI uses, major safeguards, student expectations, privacy considerations, and channels for questions or concerns. Schools will provide additional notice when AI use materially affects student experience, data handling, or instructional practice.”
Implementation Considerations
Districts should create family-facing summaries, FAQs, website content, school leader talking points, and issue-specific notices when new systems or major changes are introduced.
Common Pitfalls
Using technical language that families cannot interpret
Waiting until after implementation to communicate
Creating inconsistent messages across schools
Failing to align communications with legal and privacy review
Stakeholders to Involve
Communications staff, principals, family engagement leaders, superintendent’s office, privacy officer, legal counsel, and educators.
13
Human Resources and Professional Learning
Purpose
To prepare staff to use AI responsibly, competently, and consistently across roles.
Key Questions to Consider
What baseline AI training is needed for all staff?
What differentiated training is needed by role?
How will ongoing support be provided as tools evolve?
How will expectations be reinforced over time?
Sample Guidance Language
“The district will provide ongoing professional learning on AI literacy, approved uses, privacy and confidentiality, accessibility, academic integrity, bias awareness, cybersecurity, and role-specific expectations. Staff are expected to use AI consistent with district guidance and to seek clarification when a proposed use involves uncertainty or elevated risk.”
Implementation Considerations
Professional learning should be ongoing rather than one-time. Districts should provide differentiated support for teachers, school leaders, counselors, central office staff, HR teams, and IT leaders.
Common Pitfalls
Issuing policy without training
Offering only a basic introductory session
Ignoring role-specific differences
Leaving educators to interpret ambiguous issues on their own
Stakeholders to Involve
HR leaders, professional learning staff, principals, teacher leaders, IT staff, communications staff, special education leaders, and district leadership.
14
Accessibility, Inclusion, and Equity
Purpose
To ensure AI use supports meaningful access, broad participation, and fair treatment for all students, families, and staff.
Key Questions to Consider
Does the tool work effectively for users with disabilities?
Does it support multilingual access and assistive technologies?
Could it produce biased or exclusionary outcomes?
Could it increase inequities in access or support?
Sample Guidance Language
“AI tools used by the school system must be evaluated for accessibility, inclusion, and equity impacts before and during implementation. The district will prioritize tools and practices that support broad access, meaningful participation, and nondiscriminatory outcomes for students, families, and staff.”
Implementation Considerations
Districts should assess accessibility before procurement and during implementation. This includes compatibility with assistive technology, multilingual functionality, captioning, readability, keyboard access, and the quality of accommodations-related support.
Common Pitfalls
Reviewing only functionality and not accessibility
Assuming AI translation or captioning is sufficient without review
Ignoring bias or disparate impact
Overlooking digital divide concerns such as devices, bandwidth, or cost
Stakeholders to Involve
Special education leaders, Section 504 or ADA coordinators, accessibility specialists, English learner leaders, curriculum leaders, IT, procurement, legal counsel, and family engagement staff.
15
Procurement and Vendor Considerations
Purpose
To ensure AI-enabled tools and services are reviewed carefully before adoption and governed through clear contracts and approval processes.
Key Questions to Consider
Does the vendor clearly disclose AI functionality and data practices?
What data is collected, retained, shared, or used for training?
What transparency, accessibility, security, and human-review controls exist?
What contractual protections are required?
Sample Guidance Language
“Procurement of AI-enabled tools or services shall include review of educational value, privacy, security, accessibility, bias and fairness risk, transparency, records considerations, integration architecture, and contractual protections. Vendors must provide sufficient information to support informed review before approval.”
Implementation Considerations
Districts should evaluate not only tools marketed as AI, but also AI features embedded in existing products. Vendor review should include privacy, security, accessibility, integration, records retention, and limitations on secondary data use.
Common Pitfalls
Purchasing tools before instructional, privacy, or accessibility review
Accepting vague vendor answers on risk-related questions
Overlooking downstream subcontractors or data flows
Ignoring AI features already embedded in current platforms
Stakeholders to Involve
Procurement staff, legal counsel, privacy officer, IT and security leaders, curriculum leaders, finance leaders, accessibility experts, and communications staff.
16
Risk Management, Ethics, and Compliance
Purpose
To define how the school system identifies high-risk use cases, sets red lines, and aligns practice with law, ethics, and local values.
Key Questions to Consider
Which AI uses are low, moderate, or high risk?
Which uses should be prohibited outright?
When is legal review required?
How will fairness, transparency, accountability, and recourse be addressed?
Sample Guidance Language
“The district will use a risk-based approach to AI governance. High-risk or high-impact uses, including those involving student records, discipline, safety, grading, placement, eligibility, surveillance, special education, or automated decision support, require enhanced review, documentation, and human oversight.”
Implementation Considerations
Districts should map AI use cases by risk level and ensure that higher-risk use cases receive stronger scrutiny, documentation, and approval requirements. Schools should consult legal counsel when proposed AI uses raise questions involving privacy, accessibility, civil rights, employment, records, procurement, or student discipline.
Common Pitfalls
Assuming AI governance is mainly about plagiarism
Failing to classify use cases by risk
Overpromising what AI can do reliably
Lacking complaint, recourse, or appeal mechanisms
Stakeholders to Involve
Legal counsel, privacy leaders, civil rights and accessibility leaders, HR, student services, assessment leaders, superintendent’s office, and governing board leadership.
17
Periodic Review, Revision, and Continuous Improvement
Purpose
To ensure that AI-related policy and guidance remain current as laws, tools, evidence, and community expectations change.
Key Questions to Consider
How often will the district review AI-related policy and guidance?
What events should trigger an interim review?
What evidence and feedback will inform revisions?
How will staff and families be informed when changes are made?
Sample Guidance Language
“The district shall review AI-related policy, guidance, procedures, and approved tool lists at least annually and more frequently when legal requirements, technology functionality, instructional practice, vendor terms, or risk conditions materially change.”
Implementation Considerations
Districts should establish annual review cycles and also identify interim triggers such as major incidents, privacy or security concerns, substantial product changes, changes in law or guidance, or evidence of inequitable outcomes.
Common Pitfalls
Publishing guidance and never revisiting it
Ignoring silent product updates in AI-enabled platforms
Updating guidance without retraining staff
Failing to archive outdated versions and communicate replacements clearly
Stakeholders to Involve
AI governance committee, legal counsel, privacy leaders, IT and security staff, curriculum leaders, principals, educator representatives, and communications staff.
K-12 AI Policy Template Resources and Research Areas to Monitor
Schools and districts should monitor authoritative guidance, standards, and research areas relevant to AI in K-12 education.
🏛️ Federal education guidance related to AI, privacy, and school operations
🔒 Privacy and data governance guidance related to student records and education technology
🛡️ Cybersecurity guidance for K-12 institutions
♿ Accessibility and disability access requirements affecting digital content and services
🎓 K-12 field guidance from recognized education organizations and leadership groups
📊 Cross-sector AI risk management frameworks and standards
🌐 International guidance on AI in education where relevant
🔬 Research on student learning, cognitive effects, educator workload, fairness, accessibility, academic integrity, synthetic media, and student well-being
Checklist for Developing or Revising a K-12 AI Policy Template
Use this checklist when developing or revising your district or school AI policy, guidance, procedures, and practices.
Governance and Scope
✓Have we defined what AI and generative AI mean for local purposes?
✓Have we distinguished policy, guidance, procedures, and best practices?
✓Have we defined who approves, reviews, and updates AI-related decisions?
✓Have we identified prohibited, restricted, and permitted uses?
Stakeholder Process
✓Have we engaged educators, students, families, IT, privacy, legal, and accessibility leaders?
✓Do we have a communication plan for staff and families?
Teaching and Learning
✓Have we clarified expectations for student and educator AI use?
✓Have we addressed curriculum, instruction, assessment, and academic integrity separately?
✓Have we included AI literacy expectations?
Student Protection
✓Have we addressed age-appropriateness and grade-band differences?
✓Have we addressed privacy, cyber risk, harmful content, impersonation, and well-being?
✓Do we have escalation procedures for incidents and complaints?
Equity and Access
✓Have we reviewed accessibility, disability-related access, multilingual needs, and digital divide concerns?
✓Have we considered bias and disparate impact?
Vendor and Tool Review
✓Do we know what AI features exist in our current platforms?
✓Do procurement and contract review processes address privacy, security, accessibility, transparency, retention, and secondary use?
✓Do we have a documented approval workflow?
Compliance
✓Have we reviewed applicable legal and regulatory requirements?
✓Have legal counsel, privacy leaders, and security leaders reviewed higher-risk use cases?
✓Have we identified areas that require board review or formal approval?
Review and Improvement
✓Have we set an annual review cycle and interim triggers?
✓Do we have a professional learning plan?
✓Do we have a process for gathering evidence, feedback, and incident data to improve guidance over time?
K-12 AI Policy Template Conclusion
A high-quality AI Policy and Guidance Template for K-12 education should be clear enough to guide action, flexible enough to adapt, and disciplined enough to protect students, support educators, and preserve sound educational judgment. The goal is not to produce a perfect permanent document, it is to build a thoughtful local framework that can evolve responsibly as AI changes.
Schools and districts that approach AI with clarity, collaboration, and appropriate safeguards will be better positioned to support innovation while protecting student interests and maintaining public trust.
Mississippi Artificial Intelligence Network
Supporting AI education and governance across Mississippi
Questions about this framework or MAIN’s AI programs? Contact us.
