United States’ Federal and State-Level K-12 Artificial Intelligence Education Policies: Analysis and Insights
Yuxi WEN, Zhilei TIAN
Peking University, China Institute for Education Finance Research
This is an abridged, but more research-oriented style of the original Chinese version, published as the 2025(13) issue of Chinese Education Finance. This English version is submitted for a proposal for the 2026 American Education Research Association’s Annual Conference.
Abstract
Generative artificial intelligence (AI) and its application to K–12 education has gained attention, yet U.S. policy analyses have overlooked simultaneous federal and state-level perspectives. This study addresses this gap by mapping five key federal directives and 25 state guidelines. Utilizing systematic web searches alongside content and thematic analyses, we identified contrasting federal strategies under Biden and Trump education-centered guidance versus technology-driven task forces—and characterize state policies as “living documents” with tailored audiences. Four recurring policy recommendation themes emerged: legal considerations, staged implementation, entry requirement, and content verification. Our findings offer a comprehensive snapshot of U.S. AI education policy, informing policymakers and guiding future research on equitable AI integration in K–12 schooling and for designing effective, context-sensitive guidelines.
Introduction
With the rise of generative artificial intelligence (AI), its application to K-12 education is gaining increasing attention, and the study of its policymaking has become an emerging research area (Cheah et al., 2025). The United State’s decentralized education system made both the federal and state-level policymakers key stakeholders, as policy and fundings from both levels can strongly influence K-12 public education. However, much of the existing literature either analyzes U.S. AI–education policy in a comparative international context (e.g., examining socioeconomic and governance differences across the U.S., EU, and UK (Capraro et al., 2024)), focuses narrowly on federal initiatives without addressing state-level frameworks , or discusses AI in education without engaging with policy dimensions . Thus, examining both the federal and state-level policy towards K-12 AI education not only fills gaps but is also valuable because of its exigence and pertinence (Hancock et al., 2024; Mastin et al. 2024). By focusing on the U.S. and landscaping both tiers, it may shed new light on AI education at a larger policy level, which may serve as a reference point and guidance for future research (Liebig, 2024; Tournier et al., 2025).
As such, this study focuses on the following questions: (1) what are the major federal and state-level policies on AI education from 2021 to 2025? (2) what themes, guidance, or recommendations have been reiterated by these documents? and (3) what are the differences between federal and state-level guidelines, and between the Biden and Trump administration’s approach in AI education?
Methods
Data Collection
For all federal-level policies, an extensive web search was conducted, using keywords such as “artificial intelligence”, “artificial intelligence education”, “AI education”, with specific attention to White House webpages (including Biden’s archived pages and Trump’s first term achieved pages), the NSF, and the Department of Education. In the end, five policy documents stood out: two are guidance documents from the Department of Education; two are executive orders, and one budget proposal. The exact titles of the documents are available in Appendix 1.
For state-level education policies, a state-by-state search is conducted online using “[state name] K-12 AI education guideline”, where each of the 50 U.S. states is inserted chronologically, and the relevant policy identified. If there are multiple documents, the guideline document is considered; if there are updates, then the newest version is considered. As of June 2025, 25 state-level documents were collected; the full list of states and documents is available in the Appendix 2.
Data Analysis
For federal-level policies, content analysis was used to summarize and pinpoint the policies and content relevant to the three research questions. For state-level policies, a combination of content analysis and thematic analysis was used. As the authors read through the exact documents, we realize that each state faces their unique challenges, and the state-level guidance is tailored to the circumstances of each state. We were also hesitant on traditional coding, as although the text is qualitative, policy documents cannot be coded like interviews. After discussion, the authors concurred on two themes that guided the characteristics: living document and intended audience; and four themes that guided the policy recommendations: legal considerations, staged approach, entry requirements, and content verification.
Results
Federal-Level Summaries & Shifts
The democratic and the republican parties hold very different views on generative AI education. Overall, the Biden administration sees this as a pure education issue, where the primary approach is through providing overall guidance to states and districts by the U.S. Department of Education’s Office of Educational Technology. The Trump administration sees this as an interdisciplinary issue of science and technology, where the chief of White House’s office of technology policy chairs a task force.
In March 2023, the Office of Educational Technology under Biden published Artificial Intelligence and Future of Teaching and Learning: Insights and Recommendations. As AI is developing in 2023, this document briefly introduced AI and then provided practical advice on teaching, learning and evaluation at a classroom level, while providing advice on classroom scenarios, design principles and potential state-level policies. In October 2023, Biden signed Executive Order 14110, which requires the Secretary of Education to produce a guidance document related to safety and privacy issues in developing AI. In July 2024, the Office of Educational Technology published Designing for Education with Artificial Intelligence: An Essential Guide for Developers, fulfilling the mandate of the Executive Order. This document centers on five core policy recommendations: (1) designing for teaching and learning, (2) providing evidence for rationale and impact, (3) advancing equity and protecting civil rights, (4) ensuring safety and security, and (5) promoting transparency and earning trust. Overall, the Biden administration relies heavily on the Department of Education to provide practical guidance to the broad education sector.
Trump, on the other hand, demonstrated consistency on funding AI’s scientific research throughout his two terms. As early as 2021, Trump has doubled AI and quantum information technology’s R&D funding in his budget. By March 2025, Trump has laid off the entire Office of Educational Technology. In April 2025, Trump signed Executive Order 14277, of which a special task force on AI education will be formed, where the director of White House’s office of technology policy will chair, and secretaries of education, energy, labor, etc. and the director of NSF shall sit in. It also demands members to develop respective educational and training programs in their respective departments to advance AI’s connection to everyday life, as well as directing current available budgets and grants toward AI education.
State-Level Policy Characteristics
Compared to the turbulent federal-level atmosphere regarding generative AI education, state-level policymaking is relatively smooth. To begin with some basic descriptives, the earliest guidance was released in September 2023 (California), while the latest was updated in June 2025 (North Carolina). The average length of these guidance documents is 23 pages, with Hawaii being the shortest (2 pages) and Ohio the longest (81 pages). In terms of the publisher, 22 out of 25 documents were published by the respective Departments of Education, with the others coming from in-state university (Arizona), in-state NGO (Colorado), or the state government’s committee on education technology (Connecticut). Every document included wording that this guidance is for suggestive and recommendation purposes only, or serves as a toolkit or reference; it carries in no compulsory action or command by any means.
Further results related to the two themes (living document & intended audience) is now further explored. The majority of state-level documents declared itself to be highly amendable, adaptive, or, put succinctly in the words of North Carolina, a “living document”. For most states, they would publish newer versions of guidance; some would even include a version history with major changes. North Carolina went above and beyond. In January 2024 they released Version 1. As of June 2025 it is now at Version 14. An executive decision was made at Version 11 to change the document’s format from pdf to Google Docs. The state department’s website now headlines the Google Doc link which leads straight to the live and latest version, saving administrative work and district/school confusion.
In terms of the intended audience, 15 out of 25 states have explicitly stated their intended audience, the most frequent being the districts, and then teachers, and finally students & parents. Some documents are only directed to the districts (Alabama, Georgia, Oklahoma, Oregon, Wyoming), and some included both districts and teachers (Hawaii, Mississippi, Indiana), while some also included teachers and students (Colorado, Kentucky, Ohio, Washington, West Virginia, Wisconsin). As such, some states would rather keep the guidance “internal” by restricting the scope of communication, while others would prefer to involve a larger community. Regardless of that choice, districts lie at the heart of K-12 education operation.
State-Level Content Recommendations
The results based on the four themes (legal considerations, staged approach, entry requirements, and content verification) are presented below. On the legal side, while almost every state mentioned federal and state-level legal considerations such as FERPA and IDEA, only 11 states considered implementing age restrictions, while there is in fact already a federal law in place – COPPA. COPPA (in practice) bans websites/apps that collect personal identifiable data to provide service to minors under 13. This means that in general, grades 6/7 and below should not access generative AI tools at all to comply with COPPA regulations; only three states mentioned COPPA in their guidelines.
Staged approach refers to two ideas: first is in the general sense of whether generative AI is available to students. For example, North Carolina’s staged approach plans that students under 13 can “Learn about AI”, while after reaching 13 they can “Learn about AI + Learn with AI”. The other is in the specific sense of to what extent can students use AI to complete assignments. The classical model is Georgia’s “traffic light” model, seen below in Figure 1. For every task, the teacher should announce the “light” for this task. If it is a red light, then the use of GenAI of any kind is prohibited. If it is a green light, then GenAI can be used without restriction. If it is a yellow light, then GenAI can be used, but its scope is restricted, for example, outlining, brainstorming, feedback only.
Entry requirements refer to suggestive procurement regulations provided by these guidelines on considerations / qualifications before introducing generative AI platforms / services into district and schools, included in 14 out of 25 states. Although some specific names / companies are mentioned in these guidelines, the guidelines make it clear that this in no way constitutes an endorsement. For example, North Carolina provided a 10-page entry requirement appendix in its guidelines, which assesses a technology on six areas: effect of curriculum & instruction, user experience, digital barrier, data protection, use of technology, and budgeting.
Lastly, content verification is something that both applies to teachers and students. For teachers, this refers to the idea of “human-in-the-loop”, where contents generated by AI should never be directly pasted; a human expert must manually check the output at some point. 13 out of 25 states have made this explicit. On the student side, content verification includes an array of issues to regulate student use, including AI detection software and proper citation of AI outputs. 12 out of 25 states provided guidance on citing AI, with 4 states (Arizona, Georgia, North Carolina, Washington) also providing direct links to APA/MLA’s official guidance on citing AI work.
Scholarly Significance
This exploratory study has shown that a combination of policy reports and executive orders at the federal level drives AI education, with Biden and Trump taking opposite views on AI education. At the state-levels, only 25 states have developed a state-level AI education guidance document. The existing documents is contextualized in living documents, a viewpoint on the nature of AI education policy, while its intended audience its most importantly districts, followed by teachers, parents and students. Content wise, the state-level guidelines collectively mainly discussed legal considerations, staged approach, entry requirements, and content verification as pressing issues to direct AI education at the classroom and school level. Overall, this study underscores three areas of significance: first, this study addresses a significant gap of policy analysis that focuses exclusively on the U.S. and includes both the federal and state-level policy; second, this study is an excellent snapshot of the U.S. K-12 AI education policy as of mid-2025; third, for policymakers, this study can provide resourceful considerations if they were to develop/reiterate guidelines, or request/allocate new funds for their state.
References
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Appendix 1: Federal-Level Policy Documents
Origin | Year | Title |
Department of Education | 2023 | Artificial Intelligence and the Future of Teaching and Learning |
Department of Education | 2024 | Designing for Education with Artificial INtelligence: An Essential Guide for Developers |
White House | 2023 | Executive Order 14110 (Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence) |
White House | 2025 | Executive Order 14277 (Advancing Artificial Intelligence Education for American Youth) |
U.S. Congress | 2021 | Fiscal Year 2021 – 2022 Budget |
Appendix 2: State-Level Policy Documents
State | Year | Title |
AL | 2024 | Artificial Intelligence Policy Template for LEAs |
AZ | 2024 | Generative Artificial Intelligence in K-12 Education: Guidance for Arizona Schools and Districts – A Balanced Perspective |
CA | 2023 | Artificial Intelligence: Learning with AI, Learning about AI |
CO | 2024 | Guidance for Integrating Artificial Intelligence into Teaching & Learning |
CT | N/A | Guidance for Artificial Intelligence |
DL | 2024 | Generative Artificial Intelligence in the Classroom: Guidance |
GA | 2025 | Leveraging AI in the K-12 Setting: Ensuring the Ethical, Effective, and Secure Use of AI Tools and Systems in Georgia’s Schools |
HA | 2024 | Artificial Intelligence Guidance for Employees & Support |
IN | N/A | Artificial Intelligence Guidance |
KT | 2024 | Artificial Intelligence Guidance Brief |
LA | 2024 | Artificial Intelligence in Louisiana Schools: Guidance for K-12 Schools |
MN | 2024 | Guiding Principles for Artificial Intelligence in Education |
MS | 2024 | Artificial Intelligence: Guidance for K-12 Classrooms |
NJ | N/A | Artificial Intelligence |
NC | 2025 | North Carolina Generative AI Implementation Recommendations and Considerations for PK-13 Public Schools |
ND | N/A | North Dakota K-12 AI Guidance Framework |
OH | 2024 | AI Toolkit: Guidance and Resources to Advance AI Readiness in Ohio Schools |
OK | 2024 | Guidance and Considerations for Using Artificial Intelligence in Oklahoma K-12 Schools |
OR | 2025 | Generative Artificial Intelligence in K-12 Classrooms |
UT | 2024 | Artificial Intelligence Framework for Utah P-12 Education: Guidance on the Use of AI in Our Schools |
VA | 2024 | Guidelines for AI Integration Throughout Education in The Commonwealth of Virginia |
WA | 2024 | Human-Centered AI: Guidance for K-12 Public Schools |
WV | 2025 | Guidance, Considerations, and Intentions for the Use of Artificial Intelligence in West Virginia Schools |
WI | 2024 | Empowering Lifelong Learning: AI Guidance for Enhancing K-12 and Library Education |
WY | 2024 | Guidance for Wyoming School Districts on Developing Artificial Intelligence Use Policy |