The Federal Government Steps into the AI Classroom
Artificial intelligence has moved from the margins of education policy to its center. In July 2025, the U.S. Department of Education (ED) released new guidance and a proposed supplemental grant priority that together mark the government's most explicit statement yet on how schools and universities should engage with AI. What began as measured guidance has since evolved into a comprehensive federal strategy that touches every level of American education, from elementary classrooms to research universities.
The announcement, accompanied by a detailed Dear Colleague Letter and a Federal Register notice outlining a proposed priority for future grant competitions, doesn't come from a think tank or tech company. It comes from the highest policy levels of American education, signaling that AI is no longer an experimental technology but a central concern of federal education policy.
Understanding what has happened since July requires looking at multiple, interconnected policy streams: the Department of Education's guidance on responsible AI use, the White House's comprehensive AI Action Plan, new executive orders reshaping federal AI procurement and development, and a controversial higher education initiative that has sparked intense debate about the proper role of federal oversight. Together, these developments paint a picture of a government attempting to navigate competing priorities, innovation and caution, national competitiveness and educational equity, and technological advancement and institutional autonomy.
A Government Beginning to Define the Role of AI
The Department's July guidance told schools something they've been waiting to hear: federal funds may be used for responsible applications of AI. This includes high-quality instructional materials that adapt to student needs, AI-supported tutoring, and intelligent advising systems that help learners navigate college and career pathways.
"AI tools can support, but never replace, the role of teachers." Dear Colleague Letter, p. 3
The letter is careful to add limits. It insists on educator oversight, transparency in decision-making processes, and strict adherence to privacy laws such as FERPA. The guidance acknowledges that AI raises complex ethical and privacy questions, and emphasizes that "transparency, explainability, and fairness" must guide any deployment.
At the same time, ED's proposed Supplemental Priority on Artificial Intelligence seeks to influence the future direction of grant funding. Secretary Linda McMahon announced AI as her fourth grantmaking priority, encouraging projects that teach AI literacy, expand computer-science education, and integrate AI into teaching and operations "to improve student learning outcomes and reduce administrative burden."
This initial guidance represents a balancing act. On one hand, it opens doors for districts and institutions to experiment with AI tools using federal funds. On the other, it establishes guardrails meant to ensure that innovation doesn't come at the expense of student privacy, teacher autonomy, or educational quality.
A Broader Policy Context: The AI Action Plan
The July guidance was just the beginning. On July 23, 2025, the White House released "Winning the Race: America's AI Action Plan," a comprehensive 28-page document containing more than 90 policy recommendations. The plan represents the administration's vision for ensuring the United States remains at the forefront of AI research, development, and deployment.
The AI Action Plan is organized around three pillars, each with major implications for education:
Pillar One: Accelerate AI Innovation. This pillar focuses on removing regulatory barriers and increasing federal investment in AI research and development. It emphasizes a "try first" culture and calls for expanding AI literacy and skills development across the American workforce. The plan encourages bringing together public, private, and academic stakeholders to accelerate AI adoption. Notably, it advocates developing open-source, open-weight foundation models, accepting certain risks in exchange for faster innovation and broader accessibility.
Pillar Two: Build American AI Infrastructure. The second pillar addresses the physical and digital infrastructure needed to support AI development. This includes streamlining permitting processes for data centers and semiconductor manufacturing facilities, developing an advanced power grid, and investing in a workforce capable of building, operating, and maintaining this infrastructure. For educational institutions, this signals potential opportunities for partnerships and workforce development programs.
Pillar Three: Lead in International AI Diplomacy and Security. The third pillar aims to drive global adoption of American AI systems, computing hardware, and standards. The plan emphasizes exporting the full U.S. AI technology stack—hardware, software, and models—to allies while denying adversaries access to advanced AI technology through export controls.
Accompanying the AI Action Plan were three executive orders that operationalize key aspects of the strategy. The first, "Preventing Woke AI in the Federal Government," requires all federal agencies to procure only large language models that adhere to what the order calls "Unbiased AI Principles": truth-seeking and ideological neutrality. The Office of Management and Budget was directed to issue implementation guidance within 120 days.
The second executive order, "Accelerating Federal Permitting of Data Center Infrastructure," directs agencies to streamline permitting processes for large-scale data centers and related infrastructure. The third, "Promoting the Export of the American AI Technology Stack," establishes the American AI Exports Program to promote global deployment of U.S. AI technology packages.
These policies reflect a government attempting to position the United States for what it sees as a critical competition for global AI leadership, with education playing a central role in workforce preparation and innovation.
The Implementation Gap: What Research Tells Us
While federal policy has moved quickly, implementation on the ground tells a more complex story. A September 2025 RAND Corporation study, drawing on nationally representative surveys of K-12 teachers, school leaders, district leaders, students, and parents, reveals significant gaps between AI adoption and institutional readiness.
The research found that AI use has increased dramatically. As of spring 2025, 54 percent of students and 53 percent of English language arts, math, and science teachers reported using AI for school—increases of more than 15 percentage points compared with the previous year. High school students reported higher usage rates than middle school students, and a progressively higher percentage of elementary, middle, and high school teachers reported using AI during the school year.
However, the infrastructure necessary to facilitate this swift adoption has not kept pace. Only 35 percent of district leaders reported providing students with training on AI use. Over 80 percent of students said that teachers did not explicitly teach them how to use AI for schoolwork. Just 45 percent of principals reported having school or district policies or guidance on AI use, and only 34 percent of teachers reported having rules related to academic integrity and AI.
This gap has consequences. Half of the students surveyed said they worry about being falsely accused of using AI to cheat. 61% of parents, 48% of middle schoolers, and 55% of high schoolers agreed that greater use of AI will harm students' critical-thinking skills. Interestingly, only 22 percent of district leaders shared this concern, suggesting a significant perception gap between administrators and the families they serve.
The RAND researchers recommend that trusted sources, such as states, provide regularly updated guidance on effective AI policies and training. They emphasize that training should explain how to use AI to complement, not supplant, learning, and that schools need clear definitions of what constitutes cheating with AI. Notably, they caution against overlooking elementary schools, where almost half of teachers are experimenting with AI and where foundational skills and habits are formed.
The Higher Education Dimension: A Controversial Compact
While K-12 schools grapple with implementation challenges, higher education faces a different set of pressures. On October 1, 2025, the White House sent letters to nine universities, including Vanderbilt, Dartmouth, Penn, USC, MIT, Brown, UVA, and the University of Arizona, inviting them to enter a "Compact for Academic Excellence in Higher Education."
The compact offers preferential federal funding and other benefits in exchange for institutions agreeing to a wide-ranging set of commitments. These include freezing tuition for five years, requiring standardized test scores for admissions, limiting international undergraduate enrollment to 15 percent of the student body, committing to institutional neutrality on political matters, and taking steps to address grade inflation.
The proposal also includes provisions related to admissions and hiring practices, definitions of sex and gender, and requirements to shut down departments deemed to "punish, belittle" or "spark violence against conservative ideas." The Justice Department would enforce the compact's terms, with significant penalties for noncompliance, including loss of benefits, clawback of federal funds, and requirements to return private donations.
The compact has proven controversial. As of late October 2025, seven of the nine universities have declined the offer. In rejection letters, university leaders cited concerns about academic freedom, institutional autonomy, and the feasibility of implementing certain requirements. Former Senator Lamar Alexander, a Tennessee Republican and Vanderbilt trustee, wrote in a Wall Street Journal op-ed that the compact represents federal overreach comparable to previous attempts to impose uniform national standards on K-12 schools.
The American Council on Education and 35 other organizations issued a joint statement warning that "the compact's prescriptions threaten to undermine the very qualities that make our system exceptional." While acknowledging that "higher education has room for improvement," the organizations argued that "the compact is a step in the wrong direction."
The compact's connection to AI policy may not be immediately obvious, but it's significant. Universities are major centers of AI research and development. They train the workforce that will build and deploy AI systems. And they grapple with questions about how AI should be used in teaching, research, and administration. The compact's emphasis on ideological neutrality and its requirements around institutional governance intersect with ongoing debates about how universities should approach AI ethics, bias in AI systems, and the role of technology in academic life.
Making Sense of Competing Priorities
What emerges from these developments is a federal government attempting to navigate multiple, sometimes competing priorities. On one hand, there's a clear push for rapid AI innovation and adoption, driven by concerns about global competitiveness and economic growth. The AI Action Plan's emphasis on removing regulatory barriers, accelerating infrastructure development, and promoting American AI exports reflects this priority.
On the other hand, there's recognition that AI poses real challenges for education. The Department of Education's July guidance emphasizes responsible implementation, educator oversight, and privacy protection. The concerns raised by students and parents in the RAND study about critical thinking and false accusations of cheating are real and deserve attention.
The tension between these priorities is perhaps most visible in the debate over open-source AI models. The AI Action Plan embraces open-source and open-weight models as a way to accelerate innovation and ensure broad access to AI capabilities. This approach has significant benefits: it allows researchers, educators, and entrepreneurs to build on existing models without prohibitive costs, and it prevents any single company from controlling access to foundational AI technology.
However, open models also raise concerns. They can be freely downloaded and adapted by anyone, making them potentially useful for harmful purposes. They're harder to control once released. And they may make it more difficult to implement safety measures or prevent misuse. The administration's decision to embrace openness represents a calculated trade-off, prioritizing innovation and accessibility over certain forms of control.
State-Level Responses and the Regulatory Landscape
Federal policy doesn't exist in a vacuum. In the first half of 2025, 38 states adopted more than 100 AI-related laws, according to the National Conference of State Legislatures. This flurry of state-level activity reflects both the urgency of AI-related challenges and the absence, until recently, of clear federal guidance.
State approaches vary widely. California passed the Transparency in Frontier Artificial Intelligence Act, establishing disclosure requirements for advanced AI systems. Over 20 states have addressed the challenge of students using AI for academic dishonesty, with some implementing smartphone bans in classrooms as a partial response. More than half of states have issued AI guidelines for teaching and learning, though most are voluntary and provide similar recommendations about balancing AI use with skill development.
This patchwork of state regulations creates both opportunities and challenges. States can serve as laboratories of democracy, experimenting with different approaches and learning from each other's experiences. However, the lack of uniformity can create confusion, particularly for educational technology companies trying to serve multiple markets and for institutions operating across state lines.
The Senate's failure to pass a ten-year moratorium on state AI regulations in May 2025 suggests that this patchwork will persist for the foreseeable future. Educational leaders will need to navigate not just federal guidance but also state-specific requirements, adding another layer of complexity to AI implementation decisions.
What This Moment Asks of Us, the Educators
The developments since July 2025 represent a significant shift in how the federal government approaches AI in education. What was once largely left to individual institutions and market forces is now the subject of explicit federal policy and significant government investment.
This shift creates both opportunities and responsibilities. The opportunity is to leverage federal support and guidance to implement AI in ways that genuinely improve learning outcomes, expand access to high-quality education, and prepare students for a workforce where AI literacy will be essential. The responsibility is to do so thoughtfully, with attention to equity, privacy, academic integrity, and the preservation of what makes education fundamentally human.
Several questions deserve ongoing attention:
How do we balance innovation with caution? The rapid pace of AI development creates pressure to move quickly, but the RAND study's findings about implementation gaps suggest that speed without preparation can create problems. Finding the right balance will require ongoing dialogue between policymakers, educators, researchers, and families.
How do we ensure equitable access? AI tools and the infrastructure to support them are not evenly distributed. Without intentional effort, AI could exacerbate existing educational inequities rather than address them. Federal policy should be evaluated not just on whether it promotes innovation, but on whether it ensures that all students and institutions can benefit.
How do we preserve human elements of education? AI can personalize instruction, provide immediate feedback, and handle certain administrative tasks more efficiently than humans. But it cannot replace the relationships, mentorship, and human judgment that are central to education. As AI becomes more prevalent, protecting space for these human elements becomes more important, not less.
How do we navigate the relationship between federal policy and institutional autonomy? The compact controversy highlights tensions between federal priorities and institutional self-governance. These tensions aren't new, but AI may intensify them. Finding ways to pursue legitimate federal interests while respecting the autonomy that allows institutions to innovate and serve their communities will be an ongoing challenge.
How do we keep pace with technological change? AI is advancing rapidly. Policies and practices that make sense today may be obsolete in a year or two. Building adaptive capacity, the ability to learn, adjust, and evolve, may be more important than getting every decision right the first time.
The deeper question is not whether Washington supports AI in education, but how learning itself must evolve when intelligence is no longer uniquely human. The challenge for educators is to keep the center of learning human even as its edges become increasingly artificial.
If federal policy can help create the space and the funding to do that work responsibly, supporting innovation while protecting core values, encouraging experimentation while learning from mistakes, and promoting access while ensuring quality, then this moment could be one of the most consequential in modern American education.
References
1.U.S. Department of Education Press Release, July 22, 2025
2.Dear Colleague Letter on Artificial Intelligence, July 2025
3.Federal Register Notice, July 21, 2025
4.White House Proclamation on AI Education, April 2025
5.Secretary McMahon's Supplemental Grant Priorities, 2025
6.Winning the Race: America's AI Action Plan, July 23, 2025
7.The Opportunities and Risks of Trump's AI Action Plan | Council on Foreign Relations
8.AI Use in Schools Is Quickly Increasing but Guidance Lags Behind | RAND Corporation
9.5 Things to Know About Trump's Higher Ed Compact | Inside Higher Ed
10.How Trump's Department of Education Is Upending Public Schools | ProPublica
11.Educating a Future Workforce That Will Match AI Disruption | World Economic Forum
12.AI Will Transform The Workplace. Will Education Keep Up? | Forbes
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