State AI Guidance for K12 Schools
34 states (and Puerto Rico) now have official guidance or policy on the use of AI in K12 schools. We’ve compiled them in this handy resource which includes summaries and links to the full guidance for each.
(Updated 10/28/2025)
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The following AI for Education resources have been included in various state level guidance:
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This AI Policy Template from the Alabama State Department of Education (ALSDE) released in June 2024, provides guidance for Local Education Agencies (LEAs) in Alabama to develop and implement AI policies in K-12 education. The document emerged from the ALSDE AI Summit in November 2023 and subsequent sessions, representing a collaborative effort among various education stakeholders.
Key Areas Covered:
1. Eight foundational pillars: Strategy, Governance, Data Privacy and Security, Procurement, Implementation, Competency Development, Risk Management, and Utility and Effectiveness
2. Clear definitions of AI terminology and systems
3. Comprehensive guidance on AI usage in educational settings
4. Data privacy and security compliance requirements
5. Procurement and implementation guidelines
6. Risk management framework based on NIST standards
7. Detailed rules for responsible AI use by all stakeholders
Unique Aspects:
1. Alabama-specific context: The template is tailored to Alabama's educational system, with input from diverse stakeholders including the Governor's office, state education associations, and local education agencies.
2. Strong emphasis on human oversight:
- Explicitly states that AI systems will supplement, not replace, human instruction
- Requires human verification of AI-generated content and grading
- Mandates human-in-the-loop development in AI systems
3. Detailed data protection measures:
- Includes specific contract language for AI vendors (Appendix A)
- Prohibits unauthorized use of school data for training new AI models
- Requires explicit documentation and approval processes for any AI system training
4. Implementation accountability:
- Requires establishment of AI Governance Committees
- Mandates regular compliance audits
- Requires corrective action plans for any identified issues
5. Comprehensive usage guidelines:
- Clear rules for citing AI use
- Verification requirements for AI-generated content
- Process for contesting AI-generated grades
- Restrictions on AI-powered surveillance and behavioral tracking
The template stands out for its practical approach to AI integration while maintaining strong protections for student data and emphasizing the primacy of human judgment in education.
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This AI guidance from the Alaska Department of Education & Early Development (AKDEED), developed with the Alaska AI K12 Advisory Group, provides recommendations for districts implementing AI in K-12 education. The framework emphasizes flexible guidance over strict mandates, helping districts move beyond blanket AI bans toward balanced, responsible implementation.
Key Areas Covered:
Seven guiding principles for AI integration: Human-Centered, Fair Access, Transparency, Oversight, Security, Ethical Use, and Cultural Responsiveness
AI definitions and educational context, including GenAI, LLMs, and popular chatbots
Academic integrity framework addressing plagiarism and citation requirements
Data privacy and security protocols aligned with FERPA and CIPA
Implementation guidance for policy development, vendor vetting, and procurement
AI literacy programs with curated resources for educators and students
Risk management addressing bias, misinformation, and AI limitations
Unique Aspects:
Alaska-specific context: Addresses remote and rural connectivity challenges, references 2023 DEED survey on student technology access, and links to existing Alaska district policies.
Strong cultural responsiveness emphasis: Aligns with Alaska Standards for Culturally Responsive Schools, requires engagement with diverse stakeholders including elders and community members, addresses algorithmic bias, and mandates that AI tools affirm rather than diminish the diverse cultures of Alaska. Warns against misinterpretation, misappropriation, or exclusion of crucial local context.
Comprehensive digital equity framework: Acknowledges Alaska's significant broadband disparities, emphasizes AI literacy education is as critical as tool access, and provides strategies to actively mitigate the digital divide.
Flexible approach: Designed as "recommendations and considerations" rather than mandates, encourages moving beyond blanket bans, and acknowledges that robust evidence on AI effectiveness is still emerging.
Implementation guidance with external resources: Recommends districts develop key documents, references effective prompting frameworks, provides links to external resources for educators and students, and directs users to a companion resource website for tailored support.
Transparency modeled in practice: Includes AI Use Disclaimer acknowledging the document was drafted with AI assistance while emphasizing extensive human oversight, demonstrating the human-centered principle in action.
The framework stands out for balancing innovation with protection while addressing Alaska's unique geographic and cultural context through flexible guidance that respects local autonomy.
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This comprehensive guidance document from the Arizona Institute for Education and the Economy provides an overview of generative artificial intelligence (GenAI) in K-12 education. It covers key areas such as understanding GenAI, powerful teaching and learning, AI literacy, responsible and ethical implementation, and recommendations for implementation. The guidance emphasizes the importance of human agency and oversight, responsible AI use, and preparing students for an AI-powered future.
Includes:
1. Specific focus on Arizona's educational context, including references to state academic standards and local school district examples.
2. Emphasis on the "human agency and oversight imperative" throughout the document, and includes AI for Education's Top 6 Questions for GenAI EdTech Providers.
3. Detailed discussion of five key ethical considerations: bias, misinformation, intellectual property, data privacy, and equitable access.
4. Three-stage implementation recommendation: Create a Strong Foundation, Build Momentum, and Continuous Improvement.
5. Provides additional resources and research, including AI for Education's free course: An Essential Guide to AI for Educators
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This comprehensive guidance document from the California Department of Education addresses the implementation of artificial intelligence (AI) in K-12 education. It covers topics such as understanding AI, its potential uses in teaching and learning, ethical considerations, and implementation strategies. The guidance emphasizes the importance of human relationships in education, AI literacy, equity, and responsible use while exploring potential applications in classroom instruction and school operations.
Unique aspects include:
1. A focus on California-specific educational standards and initiatives.
2. Emphasis on integrating AI skills with California's computer science standards.
3. Guidance on developing AI in schools, not just using existing AI tools.
4. Incorporation of the "5 Big Ideas of AI" framework for K-12 education.
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This comprehensive roadmap document from Colorado provides guidance for integrating artificial intelligence (AI) into K-12 education across the state. It covers topics such as reshaping teaching and learning, advancing equitable access, developing policies for transparent and ethical use, and next steps for implementation. The guidance emphasizes the importance of human relationships in education, AI literacy, equity, responsible use, and collaboration while exploring potential applications and considerations for AI in classrooms and school operations.
Includes:
1. A focus on Colorado's specific educational context, including its local control structure.
2. Recommendations tailored for both school districts and statewide organizations.
3. Inclusion of student voices and perspectives throughout the document.
4. Emphasis on continuous learning and adaptation as AI technologies evolve.
5. Specific tools developed by working groups, such as the "If and How Checklist" and "AI Resource Evaluation Tool."
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This comprehensive guidance document from the Connecticut Commission for Educational Technology provides an overview of artificial intelligence (AI) in K-12 education. It covers key areas such as types and applications of AI, instructional and decision-making best practices, potential risks, policy considerations, and resources for educators. The guidance emphasizes the importance of responsible AI use, ethical considerations, and equitable access while providing practical guidance for educators and school leaders to integrate AI effectively.
Includes:
Specific focus on Connecticut's educational context, including references to state laws and policies.
Emphasis on the need for human oversight and discernment when using AI tools in education.
Discussion of social and emotional risks associated with AI use among students.
Inclusion of equity considerations, particularly regarding access to AI tools and technology.
References to recent and pending legislation in Connecticut related to AI in education.
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This comprehensive guidance document from the Delaware Department of Education provides an overview of artificial intelligence (AI) and generative AI in K-12 education. It covers key areas such as understanding AI, implementation strategies for districts and charter schools, classroom integration, professional learning opportunities, and next steps. The guidance emphasizes the importance of responsible AI use, ethical considerations, data privacy, and equity while providing practical guidance for educators and school leaders to integrate AI effectively.
Includes:
1. Specific focus on Delaware's educational context, including references to state policies and initiatives.
2. Inclusion of a version history table to track updates to the guidance over time.
3. Use of the SAMR model to illustrate AI integration in classrooms at different levels.
4. Emphasis on both short-term and long-term actions for AI implementation.
5. Acknowledgment of the need for continuous review and adaptation of AI practices in education.
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This comprehensive guidance document from the Georgia Department of Education (January 2025) provides a framework for implementing AI in K-12 education, focusing on ethical, effective, and secure use. It covers key areas including ethical considerations, privacy safeguards, policy development, and classroom implementation strategies.
Key areas covered:
- Overview of AI and its educational applications
- Ethical and responsible use guidelines
- Privacy protection and data security measures
- District policy adoption processes
- Professional development requirements
- Classroom implementation strategies
- AI attribution protocols
Unique aspects:
1. Clear distinction between high-stakes and non-high stakes AI uses, with specific examples of appropriate and inappropriate applications
- Prohibits AI for IEP goals, educator evaluations, and subjective grading
- Allows AI for lesson planning assistance, rubric development, and multiple-choice grading
2. "Traffic Light" System for AI Use:
- Red: AI not allowed (academic dishonesty)
- Yellow: AI allowed for content creation assistance
- Green: AI encouraged with proper citation
3. Comprehensive Evaluation Process Rubric for AI tools, including:
- Educational value
- Data privacy compliance
- Usability and accessibility
- Cost considerations
- Scalability
- Vendor reputation
- Age restrictions
4. Integration with TrustEd Apps platform for vetting AI applications
5. District Self-check sections throughout the document, providing structured evaluation points for implementation
The document emphasizes maintaining human oversight while leveraging AI's benefits, with particular attention to Georgia's educational context and compliance requirements.
On June 16, 2025, Georgia also released their Ethical Considerations in the Appropriate Use of AI for Educators providing voluntary statewide guidance for Georgia P-12 educators, administrators, and staff regarding ethical AI use in schools and classrooms.
Seven Core Ethical Principles
Responsible and Ethical Use
Academic Integrity and Modeling
Data Privacy Protection
Professional Practice Standards
Transparency and Communication
Bias Mitigation
Continuous Learning and Development
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This guidance document from the Hawaii State Department of Education provides concise recommendations for employees on the responsible use of artificial intelligence (AI) in education. It covers key areas such as accountability, fairness and equity, human oversight, assessment and effectiveness, professional development, and data protection. The guidance emphasizes the importance of ethical AI use, critical evaluation of AI-generated content, and the need for ongoing professional development.
Includes:
1. Specific focus on Hawaii's educational context, referencing state policies and resources.
2. Emphasis on avoiding AI detection tools for plagiarism due to their limitations.
3. Recommendation to cite AI-generated content to prevent plagiarism and uphold ethical use.
4. Guidance on using AI to transform assessments and provide personalized instruction.
5. Inclusion of links to various resources and support offices within the Hawaii Department of Education for further guidance on AI implementation.
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This guidance document from Indiana provides an overview of artificial intelligence (AI) in K-12 education, focusing on AI literacy, instruction and learning, impact, security, and resources. The guidance emphasizes the importance of responsible AI use, critical thinking, and preparing students for an AI-driven future while providing practical guidance for educators and school leaders.
Includes:
1. Strong emphasis on AI literacy as essential for developing empowered learners and citizens.
2. Integration of AI literacy with computer science concepts and skills.
3. Discussion of how AI can enhance instruction and learning through personalization, time-saving, and improved feedback.
4. Comparison of student and educator experiences with AI, highlighting the importance of understanding AI principles and ethical use.
5. Focus on security considerations, including compliance with FERPA/COPPA and protecting personal identifiable information.
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This guidance document from the Kentucky Department of Education provides an overview of artificial intelligence (AI) and its implementation in K-12 education. It covers key areas such as emerging technology considerations, guiding principles for AI use, application paradigms, and post-adoption monitoring. The guidance emphasizes the importance of responsible AI use, ethical considerations, equity, and transparency while providing practical guidance for educators and school leaders to integrate AI effectively.
Includes:
1. Specific focus on Kentucky's educational context, including references to the Kentucky Educational Technology Systems (KETS) Master Plan.
2. Inclusion of "Policy-in-Action Spotlights" highlighting specific roles and programs implementing AI in Kentucky schools.
3. Discussion of three paradigms for AI in education: AI-directed, AI-supported, and AI-empowered learning.
4. Emphasis on treating AI similarly to other emerging technologies to normalize its use and mitigate unfounded fears.
5. Connection of AI literacy to digital citizenship and computer science education initiatives in Kentucky.
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This comprehensive guidance document from the Louisiana Department of Education (LDOE) provides a framework for integrating artificial intelligence (AI) in K-12 education.
Released in Fall 2024, it covers key areas such as AI implementation strategies, challenges, safeguards, technical considerations, and relevant laws and policies. The guidance emphasizes responsible AI integration while prioritizing student safety, data privacy, and educational effectiveness.
Unique aspects include:
1. LDOE Framework for AI Integration: Features a four-component cyclical approach focusing on Purpose & Research, Policy & Guidance, Engage Stakeholders, and Evaluation & Monitoring, designed specifically for Louisiana's educational context.
2. AI Integration Tiered Approach: Introduces a unique four-tier system (AI-Empowered, AI-Enhanced, AI-Assisted, and AI-Prohibited) aligned with the SAMR model for technology integration, providing clear guidance on appropriate AI usage levels.
3. Comprehensive Safeguards: Detailed recommendations at both system and classroom levels, including specific considerations for data storage, software approval processes, monitoring protocols, and human oversight requirements.
4. Detailed Technical Implementation Guidance: Addresses specific infrastructure needs, including bandwidth considerations, cybersecurity protocols, and digital citizenship requirements for AI integration.
5. Louisiana-Specific Legal Framework: References state-specific laws and regulations (e.g., Louisiana Student Privacy Law R.S. 17:3914) alongside federal regulations, providing a localized legal context for AI implementation.
6. Practical Resource Integration: Includes a curated list of AI-powered tools for teachers with age-band recommendations and specific use cases, plus a comprehensive glossary of AI terms relevant to education.
The document stands out for its practical, implementation-focused approach while maintaining strong emphasis on student privacy, data security, and ethical considerations. It provides a balanced framework that promotes innovation while safeguarding student interests in Louisiana's educational context.
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This interactive guidance toolkit from the Maine Department of Education provides comprehensive support for ethical AI integration in K-12 education. The toolkit covers foundational AI concepts, teaching and learning applications, assessment strategies, and leadership frameworks for implementing AI responsibly across schools. The guidance is organized around the core principle to "KEEP THE HUMAN IN AI" and emphasizes that AI should enhance—not replace—human connection and critical thinking.
The toolkit addresses key areas including:
Ethical AI Integration: Five interconnected principles (Teach Critical Thinking, Promote Ethical Practices, Empower Human Agency, Commit to Lifelong Learning, Model Ethical Behavior)
AI Foundations: Grounding AI education in computer science, computational thinking, and digital citizenship
Teaching & Learning: Practical applications for lesson planning, accessibility, ethical use, student engagement, and assessment/feedback
Leadership: The "ROOTS" framework (Responsibility, Oversight, Opportunity, Transparency, Sustainability) for district-level AI implementation
Unique aspects include:
Asset-based approach to technology: Maine DOE explicitly rejects technology prohibitions, stating that "technology prohibitions prevent students from learning critical skills to function in today's technology-enriched society and do not prepare them for the reality they will face."
Future-Ready Student Competencies framework: Integrates AI learning with broader competencies including Digital Leadership, Computational Thinking, Effective Collaboration, Ethical Creation, Clear Communication, and Engaged Leadership.
Interactive toolkit structure: Features clickable navigation with sections including Overview, AI in Education, AI Explained, Ethics and AI, AI Foundations, Teaching & Learning, and Leadership, with embedded resources and practical examples including AI for Education’s Drafting a GenAI Academic Policy document
Academic integrity and transparency: Emphasizes open conversations about ethical AI use at all levels, with clear expectations for when and how students and teachers should use AI tools appropriately—supporting, not substituting, authentic work.
Reinforcement of effective teaching practices: Reassures educators that strong pedagogical practices remain valuable in AI-integrated classrooms, highlighting "AI-resistant" teaching strategies that maintain their effectiveness regardless of technology.
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This comprehensive guidance document from the Massachusetts Department of Elementary and Secondary Education provides voluntary guidance for districts exploring or implementing artificial intelligence (AI) in K-12 education. It covers key areas such as understanding AI types and capabilities, ethical principles for responsible use, implementation frameworks, equity considerations, legal compliance, AI literacy (teaching both about and with AI), academic integrity, and district operations. The guidance emphasizes that AI integration is a change management process requiring transparency, human oversight, bias mitigation, and data privacy while providing practical tools for educators and school leaders to integrate AI thoughtfully and equitably.
Includes:
Five core ethical principles that serve as the foundation for all AI decisions: data privacy & security, transparency & accountability, bias awareness & mitigation, human oversight & educator judgment, and academic integrity.
Distinction between teaching ABOUT AI and teaching WITH AI, with teaching about AI focused on understanding how AI works, its societal impacts, bias, and ethics across all roles (students, educators, families, community partners), while teaching with AI emphasizes using tools to enhance instruction while maintaining human-centered learning.
Framework addressing three digital divides identified in the 2024 U.S. National Educational Technology Plan: access divide (devices, internet, assistive technology), use divide (meaningful student and educator engagement with AI), and design divide (teacher capacity to design AI-enhanced learning experiences).
Action-oriented planning tables in each section with three columns allowing districts to identify potential action steps aligned with core commitments, document steps already taken for self-assessment, and create plans to move forward.
Explicit guidance against AI detection tools due to unreliability and punitive effects, recommending instead trust-based, transparency-focused approaches to academic integrity that create safe spaces for disclosure and emphasize process-oriented assessment and reflection.
Cross-departmental operational guidance extending ethical AI principles beyond instruction to district operations including budgeting and financial planning, human resources and hiring systems, data use and dashboards, and procurement and vendor management with consistent oversight.
Alignment with Massachusetts Digital Literacy and Computer Science (DLCS) Framework and integration of AI literacy into existing curriculum standards, ensuring AI concepts are embedded across content areas rather than treated as standalone technology skills.
Collaborative development process involving DESE's AI Task Force with representatives from 14 Massachusetts districts, partnership with ISTE+ASCD, and acknowledgment that this is living guidance requiring continuous adaptation as AI technology and educational practices evolve.
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This comprehensive guidance from Michigan Virtual, endorsed by major state education organizations, provides a structured framework for districts and educators to responsibly integrate artificial intelligence across teaching, learning, and operations. The Michigan Department of Education (MDE) has endorsed these resources as official guidance and is committed to continuing support as quality AI resources become available. The guidance emphasizes strategic planning, ethical implementation, and maintaining the irreplaceable human elements of education while leveraging AI as a supportive tool.
Includes:
AI Integration Framework (Rubric):
• Three-stage maturity framework (Investigating → Implementing → Innovating) across eight domains: Leadership & Vision, Policy/Ethics/Legal, Instructional Framework, Learning Assessments, Professional Learning, Student Use, Business Operations, and Outreach.
• Progressive benchmarks for each domain showing how districts evolve from initial exploration to full integration with documented evidence of impact, including efforts to narrow educational equity gaps.
Planning Guide for School Districts:
• District-level planning priorities requiring dedicated implementation teams, Board involvement, alignment with strategic goals, and comprehensive risk assessments addressing concerns about job displacement, data privacy, and algorithmic bias.
• Emphasis on localizing AI integration to each district's unique needs through stakeholder dialogue with educators, parents, students, and community members.
• Clear positioning of AI as augmenting, not replacing, human capabilities, specifically preserving educators' roles in empathy, creativity, interpersonal communication, and critical judgment.
• Operational optimization strategies for business functions including HR, facilities management, transportation, financial management, data analysis, and technology troubleshooting.
• Community engagement protocols requiring regular communication with stakeholders, readiness assessments, awareness training, and two-way dialogue to gauge comfort levels and address misconceptions about AI implementation.
Teacher Guide to AI in Education:
• Practical teacher applications including content adaptation for diverse learners (ELL, special education, multiple reading levels), formative assessment enhancement, and administrative task automation with ready-to-use prompt examples.
• Student-centered AI literacy development teaching critical evaluation of AI outputs, understanding of bias and privacy concerns, and creation of ethical guidelines for AI use in schools.
• Transparency and oversight requirements including validation of AI-generated content for accuracy, compliance with FERPA and COPPA, monitoring for bias, awareness of environmental/resource costs, and maintaining human decision-making authority.
• Professional development pathways offering reflective practice tools, simulated classroom scenarios, and personalized learning opportunities for educators to build AI expertise.
• Parent communication resources including FAQ templates, parent night presentation guidelines, and multilingual communication tools to build awareness and trust around classroom AI use.
Additional Resources:
• Curated collection of supplementary materials including links to the U.S. Department of Education's AI Toolkit for Safe, Ethical, and Equitable AI Integration, MDE's December 12 memo on AI resources, REMC AI in Education resources, and sample guidance to support ongoing implementation and professional learning.
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This guidance document from the Minnesota Department of Education provides an overview of artificial intelligence (AI) in K-12 education. It covers key areas such as guiding principles, opportunities and challenges of learning with AI, creating guidance for AI implementation, and resources for further information. The guidance emphasizes responsible AI use, centering people in decision-making, and advancing equity.
Unique aspects include:
1. Focus on Minnesota's educational context, including references to state statutes and local school district examples.
2. Emphasis on starting with existing guidance and policies when implementing AI.
3. Recommendation to prioritize learning and AI literacy for all staff and students.
4. Encouragement of innovation and knowledge sharing in AI use.
5. Comprehensive list of resources, including those from other states and national organizations.
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This guidance document from the Mississippi Department of Education provides an overview of artificial intelligence (AI) in K-12 education. It covers key areas such as defining AI, its impact on the classroom, leveraging AI for learning, and considerations for creating AI use policies. The guidance is organized around five components of digital learning: digital citizenship, standards-aligned content and tools, active learning and engagement, formative assessment and feedback, and accessibility.
Includes:
1. Specific focus on Mississippi's educational context, including references to state standards and initiatives.
2. Emphasis on the importance of human oversight and critical thinking when using AI tools.
3. Detailed strategies for students, teachers, and administrators to leverage AI in each of the five digital learning components.
4. Discussion of AI training needs for all stakeholders, including topics like informed use, accuracy checking, and bias awareness.
5. Inclusion of a curated list of AI tools and resources for classroom use.
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This AI Guidance for Local Education Agencies from the Missouri Department of Elementary and Secondary Education, released as Version 1.0 for the 2025-26 school year, provides comprehensive guidance for Missouri's Local Education Agencies (LEAs) in developing and implementing AI policies in K-12 education. The document was developed collaboratively by Missouri's Computer Science Advisory Council, comprising specialists in both education and computer science from across the state.
What stands out about Missouri's approach is their focus on practical implementation - from detailed prompt engineering guidance using AI for Education's "Five S" model to a cyclical seven-step policy development process. They've also integrated AI guidance directly with their existing computer science education initiatives, showing how AI can complement broader digital literacy efforts.
Like other states, Missouri aligns on core principles of data privacy, academic integrity, and AI literacy. Their guidance emphasizes human oversight and the importance of AI as a tool to enhance rather than replace educators. They've also created strong connections to resources like the Missouri School Boards' Association AI Toolkit.
In addition to the prompt framework, Missouri has also included a few other AI for Education resources, like our Uncovering Deepfakes classroom guide and Gen AI Explainer graphic.
Key Areas Covered:
Comprehensive AI Framework:
Clear definitions of AI types (reactive, predictive, and generative AI)
Focus on AI as a tool to enhance rather than replace human intelligence
Emphasis on responsible implementation with human oversight
Multi-Level Challenges and Benefits Analysis:
Student-level considerations (intellectual property, plagiarism risks vs. personalized learning support)
Building-level applications (lesson planning, data analysis vs. educator comfort levels)
District-level priorities (data privacy compliance, policy development vs. security concerns)
Stakeholder engagement (parent/community concerns vs. accessibility benefits)
Best Practices Implementation:
Four core principles: Responsible Implementation, Transparency, Rigor, and Curiosity
Strong emphasis on human oversight and critical evaluation of AI outputs
Guidelines for ensuring human decision-making remains central
Professional Development and AI Integration:
Eight focus areas for professional development (ethics, access, productivity, pedagogical practices)
Detailed prompt engineering guidance with the "Five S" model and "Who, What, Why, Where" framework
Emphasis on AI literacy across all grade levels and curriculum areas
Policy Development Framework:
Cyclical seven-step policy process (Purpose, Compliance, Knowledge, Balance, Integrity, Agency, Evaluation)
Comprehensive regulatory compliance (FERPA, COPPA, IDEA, CIPA, Section 504, ADA)
Detailed procurement guidelines and vendor evaluation criteria
Focus on addressing fairness, bias, and equitable access
Practical Implementation Tools:
Specific AI use guidelines for different stakeholder groups
Academic integrity expectations and honor code recommendations
Resource compilation including professional development opportunities through DESE
Unique Missouri Elements:
Integration with existing DESE Computer Science Education initiatives
State-specific legislative context (Missouri Revised Statutes Section 171.011)
Emphasis on local control while providing statewide guidance framework
Connection to Missouri School Boards' Association AI Toolkit
Reference to DESE Computer Science webpage and listserv for ongoing support
The document positions Missouri as taking a measured, educationally-focused approach to AI integration, emphasizing local autonomy within a supportive state framework while prioritizing student outcomes and ethical implementation.
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This guidance document from the Montana Office of Public Instruction (OPI) and Montana Digital Academy (MTDA) provides comprehensive support for Montana educators, administrators, families, and policymakers in responsibly integrating artificial intelligence into K-12 education. The guidelines are grounded in Montana's educational vision and designed as a living document with biannual review cycles to adapt to evolving technologies and practices.
The guidance addresses key areas including:
Core Principles for AI Use: Five foundational principles—Data Privacy & Security, Transparency & Accountability, Bias Awareness & Information Verification, Human Oversight & Educator Judgment, and Academic Integrity—that anchor local policy and implementation
AI in Teaching and Learning: Human-centered approach emphasizing developmentally appropriate curriculum integration, ethics and safety considerations, creativity and critical thinking, family engagement, and responsible innovation tied to instructional goals
Professional Learning for Educators: Comprehensive framework for building AI literacy, embedding ethics and equity, providing role-specific training, and fostering continuous professional growth
Accessibility: Strategies to close opportunity gaps, ensure accessibility by design, and maintain cultural relevance while respecting Indigenous Education for All (IEFA) requirements
Data Privacy and Security: Compliance with FERPA, COPPA, and Montana-specific laws including the Montana Pupil Online Personal Information Protection Act, with emphasis on Indigenous data sovereignty
Policy and Governance: Montana's “Constitutional Players” framework, tribal sovereignty consultation requirements, local control principles, and connections to higher education and workforce development
Implementation Roadmap: Five-phase approach covering foundation building, policy development, capacity building, accessibility pathways, and continuous improvement with support from the Frontier Learning Lab
Unique aspects include:
Rural-centered design: Explicit attention to Montana's rural context with practical solutions for small districts facing limited technology staff, constrained budgets, intermittent connectivity, and the need for shared services and cooperative models
Tribal sovereignty and IEFA integration: Strong constitutional and statutory commitment to tribal consultation, Indigenous data sovereignty, and culturally respectful education about Montana's first peoples, with clear guidance that AI tools should not alter or remix tribally authored materials
Living document with structured feedback: Biannual review cycle with explicit versioning and dedicated feedback portal ensuring the guidance remains practical, relevant, and responsive to Montana's unique landscape
AI transparency in development: Explicit acknowledgment of how AI tools were used to support (but not determine) the document's creation, modeling the human oversight principles advocated throughout the guidance and demonstrating responsible AI use in practice
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This comprehensive guidance document from the Nevada Department of Education provides a structured framework for integrating artificial intelligence into PreK-12 education through the STELLAR principles: Security, Transparency, Empowerment, Learning, Leadership, Achievement, and Responsible Use. Developed in partnership with the Leadership Institute of Nevada and the Nevada Community Foundation through the Nevada AI Alliance, the guidance reflects input from statewide stakeholder engagement including town halls, focus groups, and a Student Voice Group conducted from January to May 2024.
The document addresses critical areas including:
STELLAR Ethical Framework: Seven interconnected principles that form Nevada's "North Star" for ethical AI integration, emphasizing that "Artificial intelligence is not a substitute for human intelligence; it is a tool to amplify human creativity and ingenuity"
Stakeholder-Specific Best Practices: Tailored guidance for school districts, administrators, teachers, parents, and students with actionable recommendations for each group
AI Literacy Development: Four-stage learning framework (Understand, Apply, Integrate, Grow) with specific goals to increase AI literacy across Nevada
Data Privacy and Security: Comprehensive coverage of FERPA, COPPA, CIPA, and PPRA compliance with vendor evaluation criteria
Unique Aspects
Integration with Nevada's PCBL Framework: Explicitly connects AI capabilities to Nevada's Personalized Competency-Based Learning (PCBL) initiative, explaining how AI can provide real-time feedback, personalized learning pathways, and data-driven insights that allow students to advance upon demonstrating mastery regardless of time, place, or pace, while developing future-ready skills like critical thinking and adaptability
Equity-Focused Digital Divide Framework: Distinguishes between the "digital access divide" (inequitable access to connectivity and devices) and the "digital use divide" (students engaging as passive consumers rather than creators), with strategies to address both dimensions aligned with Nevada's Statewide Digital Equity Plan
Technology Integration Frameworks: Includes visual comparison of TPACK (Technological Pedagogical Content Knowledge) and SAMR (Substitution, Augmentation, Modification, Redefinition) models adapted specifically for AI tools, helping educators move beyond substitution to transformational uses
Living Document Commitment: Explicitly states that "as our understanding of AI continues to evolve, this document will be updated to reflect the latest advancements and insights," with a QR code linking to the most current version on the Nevada Department of Education website, acknowledging the rapidly changing AI landscape
Comprehensive Resource Ecosystem: Provides extensive resources including Nevada-specific materials, other state guidance including AI for Education’s State Guidance for K12, federal resources, professional learning platforms, and AI competency frameworks from UNESCO for both students and teachers, and resources for parents including AI for Education’s Cheat Sheet for Parents
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While New Jersey has not provided official AI guidance, they have curated and developed various resources intended to support educators and provide an overview of artificial intelligence (AI) in education.
Resources include:
1. Glossary of key AI terms and concepts, including examples for each.
2. Classification of AI systems into weak/narrow AI and strong/general AI.
3. Curated list of resources for educators to learn about AI and teach AI concepts to students.
4. Inclusion of links to free AI applications for exploration and hands-on learning.
5. References to New Jersey-specific resources, such as a pre-recorded technical assistance webinar on AI in education.
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The New Mexico AI Guidance for K-12 Education 1.0 from the New Mexico Public Education Department (NMPED), released in May 2025, provides comprehensive guidance for schools and districts to responsibly integrate artificial intelligence into teaching and learning. The document was developed through collaboration with the William & Ida Friday Institute for Educational Innovation at North Carolina State University and represents extensive stakeholder input from across New Mexico's educational communities.
Key Areas Covered:
1. AI Literacy Development
Age-appropriate AI education strategies for early grades (K-5), middle grades (6-8), and high school (9-12)
Focus on understanding, evaluating, and using AI systems effectively
Professional development resources for educators
2. Human-Centric AI Framework
Emphasis on keeping educators "in the loop" rather than replacing them
Four-step cycle: Inquiry, Input, Interpretation, and Insight
Positioning AI as a tool to support, not replace, human judgment and relationships
3. Guiding Principles for Ethical Use
Five core protections based on the White House AI Bill of Rights: safe systems, discrimination protection, data privacy, transparency, and human alternatives
M.A.Z.E. framework for AI adoption: Monitor data privacy, Assess for accuracy, Zero-in on bias, Evaluate value
4. Digital Learning and Equity
Addressing three digital divides: access, use, and design
Ensuring equitable access to AI tools and infrastructure
Supporting diverse learning needs through culturally-relevant practices
5. Framework for AI Integration
Standards alignment strategies for both "teaching with AI" and "teaching about AI"
SAMR model implementation (Substitution, Augmentation, Modification, Redefinition)
Student-centered learning supports including individualized experiences and academic recovery
6. Academic Integrity Guidelines
Five-level AI Assessment Scale from "No AI" to "AI Exploration"
Clear guidance on appropriate AI use in coursework
Emphasis on transparency and proper disclosure of AI assistance
7. Policy and Governance
Local policy development guidance leveraging existing Responsible Use Policies
Compliance with federal regulations (FERPA, COPPA)
Resources and examples from other districts
8. Future Considerations
Partnerships with state institutions and national laboratories
Workforce preparation and career readiness
Addressing emerging challenges like deepfakes and misinformation
The guidance emphasizes New Mexico's commitment to digital equity through the NM Digital Equity in Education Act (2023) and positions the state to leverage partnerships with organizations like the New Mexico AI Consortium (NMAIC) to create cutting-edge, equitable AI education opportunities for all students.
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This robust and practical guidance document from the North Carolina Department of Public Instruction provides detailed recommendations for implementing artificial intelligence (AI) in K-12 education. It covers key areas such as leadership and vision, human capacity, curriculum and instruction, data privacy and cybersecurity, and technology infrastructure. The guidance emphasizes responsible AI implementation, AI literacy for all, and the importance of adapting to rapid technological changes.
Includes:
1. Specific focus on North Carolina's educational context, including references to state standards and initiatives.
2. Detailed AI implementation roadmap for public schools based on AI for Education's work.
3. Emphasis on AI literacy across all grade levels, with specific recommendations by grade span.
4. Inclusion of frameworks like CRAFT for effective AI prompting and AI for Education's EVERY for responsible AI use.
5. Guidance on creating AI guidelines and evaluating generative AI edtech tools at individual schools
5. Comprehensive list of free resources for school leaders, staff development, and teaching students about AI.
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This guidance document from North Dakota provides an overview of artificial intelligence (AI) in K-12 education. It covers key areas such as implementation roadmaps, AI strengths and weaknesses, considerations for different student grade levels, and AI for accessibility. The guidance emphasizes the importance of responsible AI implementation, human oversight, and AI literacy.
Unique aspects include:
1. A focus on North Dakota's educational context and initiatives.
2. Inclusion of a detailed implementation roadmap and checklist for schools based on AI for Education's work.
3. Brief history of AI development and its impact on education.
4. Specific considerations for AI implementation at different grade levels (K-2, 3-5, 6-8, 9-12).
5. Discussion of AI's potential for enhancing accessibility and personalized learning for students with special needs.
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This AI toolkit from Ohio provides guidance and resources for integrating artificial intelligence (AI) in K-12 education. It covers key areas such as policy development, resources for stakeholders, and summaries of relevant AI guidelines. The toolkit emphasizes the importance of a methodical approach to translating high-level principles into actionable policies for AI in education, while providing practical resources for policymakers, teachers, and parents.
Includes:
1. A step-by-step approach to policy development for AI in education, from landscape analysis to implementation.
2. Detailed summaries and analysis of 21 sets of AI guidelines, both education-specific and general.
3. Focus on Ohio's educational context and the need for trusted resources for educators.
4. Inclusion of resources specifically tailored for policymakers, teachers, and parents.
5. Summary table showing each guideline's coverage of policy development steps and relevance for different stakeholders.
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This guidance document from the Oklahoma State Department of Education provides an overview of artificial intelligence (AI) in K-12 education. It covers key areas such as understanding AI in education, benefits and risks, roles and responsibilities, academic integrity, essential elements for classroom integration, and implementation considerations. The guidance emphasizes responsible AI use, data privacy, and the importance of human oversight in AI implementation.
Includes:
1. Specific focus on Oklahoma's educational context, including references to state initiatives and academic standards.
2. Detailed AI Acceptable Use Rating Scale for managing student AI use in assignments.
3. Three essential elements for integrating AI in the classroom: transparency, rigor, and curiosity.
4. Risk assessment framework for AI tools categorized as low, medium, and high risk.
5. Comprehensive list of resources for school leaders, staff development, and teaching students about AI, including AI for Education's free curriculum and prompt library for educators.
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This guidance document from the Oregon Department of Education provides an overview of generative artificial intelligence (AI) in K-12 education. It covers key areas such as defining generative AI, equity implications, data privacy considerations, potential classroom applications, and policy development guidance. The guidance emphasizes responsible AI use, addressing equity impacts, and the importance of human oversight in AI implementation.
Includes:
1. Specific focus on Oregon's educational context, including references to state policies like the Oregon Student Information Protection Act.
2. Detailed table of strategies to address equity impacts of AI use in classrooms, covering issues like bias, inaccuracy, and plagiarism.
3. Table of potential instructional strategies for using generative AI in K-12 classrooms across various areas.
4. Discussion of AI's potential to support students with disabilities and multilingual learners.
5. References to Oregon-specific resources like the "Key Components of Digital Learning" and "Online and Remote Learning Guidance" for policy development.
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This AI Policy Guidance from the Puerto Rico Department of Education provides comprehensive guidance for integrating artificial intelligence in the education system with a human-centered approach. The document was developed by the Undersecretary for Academic and Programmatic Affairs and represents Puerto Rico's first comprehensive AI policy framework for K-12 education.
Key Areas Covered:
Three Types of AI Integration:
Classroom applications focused on personalizing learning and addressing individual student needs
Administrative office applications for optimizing management and decision-making processes
Home and community applications to facilitate learning and improve time management
Human-Centered Approach Framework:
Nine core objectives including AI literacy, digital citizenship, privacy protection, personalized learning, and responsible AI use
Emphasis on AI as a tool to enhance rather than replace human capabilities
Focus on maintaining teacher autonomy and student agency in the learning process
Ethical Principles and Guidelines:
Seven foundational principles: transparency, equity and non-discrimination, privacy and data security, human responsibility, teacher/student autonomy, educational improvement, and continuous evaluation
Compliance with FERPA, COPPA, and CIPA regulations
Clear guidelines for responsible data management and algorithmic bias prevention
Professional Development Requirements:
Seven core areas for staff training including innovation, personalized learning, equity, digital literacy, leadership, impact evaluation, and collaborative learning networks
Emphasis on developing soft skills alongside technical AI competencies
Importance of powerful questioning techniques for effective generative AI use
Risk Management and Challenges:
Identification of three main challenge categories: ethical issues, data privacy/security concerns, and dependency/autonomy risks
Specific attention to algorithmic bias, lack of transparency, and over-reliance on AI technologies
Strategies for maintaining educational equity and preventing technological dependence
Unique Aspects
• "Conecta y CRECE" integration - AI embedded within broader "Connect with Learning and GROW" educational transformation theme
• Explicit anti-replacement mandate - Teachers repeatedly identified as "main resource" with AI strictly as support tool
• 5-Step Student Scaffolding Scale - Detailed framework from no AI use to AI co-creation with specific academic integrity requirements
• Dual soft skills framework - Separate competency development plans for both students and staff
• Socioeconomic inequality prevention - Prominent emphasis on preventing AI from worsening existing disparities
• Common good mandate - Repeated focus on AI serving broader social justice and community benefit
• Resource-conscious security - Specific guidance for staff evaluating AI tools outside official networks
• Generative AI questioning techniques - Detailed section on "powerful questioning" strategies for effective AI interaction
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This comprehensive guidance document from the Rhode Island Department of Elementary and Secondary Education (RIDE) provides a framework for artificial intelligence (AI) integration in K-12 education. It covers key areas such as instructional applications, academic integrity, equity and bias, security and privacy, meeting diverse learner needs, college and career readiness, administrative operations, and family engagement. The guidance emphasizes responsible AI use, data protection, and equitable access while providing practical checklists and policies for educators and school leaders to implement AI safely and effectively.
Includes:
Extensive stakeholder engagement data from 1,252 survey respondents, focus groups, and town halls across Rhode Island.
Strong emphasis on AI as a tool to empower teachers and enhance—not replace—the student-teacher relationship.
Developmentally appropriate use cases by grade level (K-2, 3-5, 6-8, 9-12) with specific caveats and supervision requirements.
Detailed procurement checklist addressing data privacy, FERPA/COPPA/CIPA compliance, bias mitigation, and vendor accountability.
Sample acceptable use policies, parent communication letters (in English and Spanish), and LEA implementation checklists.
Alignment with RIDE's Strategic Plan priorities: Equity, Excellence in Learning, Engaged Communities, World Class Talent, and Governance Structures.
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Tennessee has not provided formal state AI guidance from the Department of Education, but the state legislature passed Public Chapter 550 in spring 2024, mandating that all Tennessee K-12 districts, public charter schools, and universities adopt their own AI policies. In response, the Tennessee School Boards Association (TSBA) developed Model Policy 4.214: Use of Artificial Intelligence Programs (June 26, 2024), which most districts adopted in full—though some, like Metro Nashville Public Schools, personalized their policies. TSBA also created an accompanying AI toolkit to support implementation.
Key Areas Include:
Approval and Oversight Requirements - Only approved AI programs may be used for student instruction or student work; district technology staff must review programs for compliance with state and federal data privacy laws.
Strict Data Privacy Protections - Employees are prohibited from entering personally identifiable information, financial information, intellectual property, or confidential information into AI systems.
Mandatory Professional Development - AI training must be incorporated into staff professional development, focusing on responsible use, best practices, data privacy compliance, and proper data security.
Staff Use Guidelines - Staff may use AI for work tasks but must disclose AI use when required, verify all outputs with reliable sources, and avoid incorporating AI outputs into proprietary works.
Student Use and Academic Integrity Standards - Teachers may allow students to use approved AI programs that align with curriculum standards; students must receive instruction on responsible AI use, including when AI is appropriate, how to verify accuracy, and the difference between cheating and legitimate support.
Parent Communication Requirements - Districts must provide parents/guardians with notice about AI program use and an approved list of AI programs.
Annual Accountability and Reporting - Directors of Schools must submit annual reports to their Board of Education each June on policy enforcement plans, which are then submitted to the Tennessee Department of Education by July 1st.
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This framework document from the Utah State Board of Education provides guidance on the appropriate and responsible use of artificial intelligence (AI) in Utah's P-12 education system. It covers key areas such as guiding principles, responsible and prohibited uses of AI tools, and special considerations for security, privacy, and safety. The guidance emphasizes the need for a balanced approach that maximizes learning opportunities while addressing potential risks and security concerns.
Includes:
1. Specific focus on Utah's educational context, including references to state codes and existing policies.
2. Emphasis on maintaining student and teacher agency when using AI tools.
3. Commitment to educating staff and students about AI literacy.
4. Inclusion of a section on prohibited uses of AI tools, addressing issues like plagiarism and privacy concerns.
5. Recognition of the need for regular review and updates to the framework due to the rapidly evolving nature of AI technologies.
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Released January 23, 2026 by the Vermont Agency of Education. This comprehensive 50-page guidance provides a framework for responsible AI adoption in K-12 schools, emphasizing human-centered implementation that enhances rather than replaces educator-student relationships.
Key Highlights
Developmental framework: Recommends no AI chatbot use for PreK-2; curriculum-embedded AI only for grades 3-5; structured education-specific chatbots for grades 6-8; broader AI fluency development for grades 9-12
Four principles framework: (1) Streamline administrative work, (2) Support personalized learning, (3) Develop student AI literacy, (4) Enable cognitively demanding tasks
Local control emphasized: Districts empowered to adapt timelines and approaches based on their context and student populations
Strong focus on risks: Extensive guidance on academic integrity, cognitive offloading, data privacy, mental health, student safety, bias, equity, and ethics
Human oversight required: Educators must review all AI outputs; AI should enhance not replace professional judgment
Content knowledge priority: Emphasizes students need strong foundational skills to use AI effectively; AI literacy depends on content mastery
Notable Features
Includes role-specific quick start guides for elementary, middle school, high school educators, and IT/school leaders
Provides tool vetting framework for evaluating AI applications across three categories: general purpose tools, education-specific chatbots, and AI-embedded applications
Addresses Google Gemini availability for all Vermont schools (all districts use Google for Education)
Comprehensive FAQ section and prompting guide for educators
Explicit guidance on when NOT to use AI (high-stakes grading, sensitive student situations, legal documentation, medical information)
Resources for parent/guardian engagement
Professional development resource compilation
AI for Education Resources Cited in Vermont Guidance
The Vermont cites multiple AI for Education resources as recommended materials for educators and administrators:
Strategic Planning
Policy Development
Educator Resources
Student Instruction
View FULL GUIDANCE
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This comprehensive guidance document from Virginia outlines the integration of artificial intelligence (AI) in K-12 education. It covers key areas such as AI literacy, ethical considerations, responsible implementation, and supporting educators with AI tools. The guidelines emphasize the importance of balancing AI's potential benefits with safeguarding student privacy and ensuring equitable access.
Includes:
1. Specific focus on Virginia's educational context, referencing state standards and local examples.
2. Emphasis on balancing AI benefits with ethical considerations like privacy and equity.
3. Recommendations for professional development and AI literacy programs for educators.
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This comprehensive guidance document from the Washington Office of Superintendent of Public Instruction provides a framework for integrating artificial intelligence (AI) into K-12 education. It covers key areas such as understanding AI, ethical considerations, implementation strategies across grade levels and subject areas, and recommendations for educators, administrators, and other stakeholders. The guidance emphasizes a human-centered approach to AI in education, focusing on the "Human AI Human" (H AI H) model that prioritizes human inquiry and empowerment.
Includes:
1. Specific focus on Washington state's educational context, including references to state policies and local school district examples.
2. Detailed 5-step scaffolding scale for student AI use, ranging from no AI assistance to AI as co-creator.
3. Inclusion of sample classroom protocols, student AI code of conduct, and professional ethics for educators.
4. Emphasis on equity considerations and supporting students with diverse needs.
5. Incorporation of AI use in the document's creation process, with a disclaimer acknowledging responsible AI engagement.
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This comprehensive guidance document from the West Virginia Department of Education provides a framework for integrating artificial intelligence (AI) into K-12 education in West Virginia schools. It covers key areas such as understanding AI, ethical considerations, implementation strategies across grade levels, and recommendations for educators, administrators, and other stakeholders. The guidance emphasizes a human-centered approach to AI in education, focusing on responsible and safe use while leveraging AI's potential to enhance learning.
Includes:
1. Specific focus on West Virginia's educational context, including references to state policies and alignment with existing West Virginia Board of Education policies.
2. Inclusion of a version history table to track updates to the guidance over time as AI rapidly evolves.
3. Emphasis on computational thinking as a framework for teaching AI literacy to students.
4. Detailed prohibited uses of AI tools in educational settings to mitigate risks.
5. Provision of a Canvas self-enrolling resource directory for educators to access additional AI-related materials and professional development resources.
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This comprehensive guidance document from the Wisconsin Department of Public Instruction provides a framework for integrating artificial intelligence (AI) into K-12 education and library settings in Wisconsin. It covers key areas such as core concepts and goals, partner engagement, ethics and data privacy, security and infrastructure, professional development, curriculum and pedagogy, and continuous improvement strategies. The guidance emphasizes a human-centered approach to AI in education, focusing on responsible and ethical use while leveraging AI's potential to enhance learning and library services.
Includes:
1. Specific focus on both K-12 education and public libraries in Wisconsin.
2. Inclusion of a "Human > AI > Human" (H > AI > H) mnemonic tool to remind users of responsible AI use practices.
3. Emphasis on five training pillars for K-12 educators, including hands-on AI experiences and continuous learning.
4. Detailed recommendations for AI literacy across different grade spans (elementary, middle, and high school).
5. Provision of Wisconsin-specific resources and professional development opportunities, such as SLATE conferences and CESA-based workshops.
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This comprehensive guidance document from the Wyoming Department of Education provides a framework for developing artificial intelligence (AI) use policies in K-12 education. It covers key areas such as defining AI, guidelines for policy development, guiding principles, and questions to consider when implementing AI in educational settings. The guidance emphasizes the importance of responsible and ethical use of AI while leveraging its potential to enhance teaching and learning.
Unique aspects include:
1. Specific focus on Wyoming's educational context, including alignment with the state's Digital Learning Plan.
2. Emphasis on a cyclical process for policy development, involving continuous improvement and organizational learning.
3. Detailed guidance on forming an AI guidance team with diverse stakeholders.
4. Inclusion of a "Student AI Usage Continuum for Empowered Learning" to help determine appropriate AI use in classrooms.
5. Recognition of AI as a rapidly evolving field, with commitment to regular review and updates of the guidance.
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