With 'The American AI Action Plan', we're officially in a global race for AI Readiness

The U.S. government is emphasizing speed, American competitiveness and workforce readiness. But 'winning' will require going broader than teaching students to use AI tools.

Last week, the Administration published a 26-page document titled “The American AI Action Plan.” In accordance with the executive order in January on “Removing Barriers to American Leadership in AI,” the Action Plan outlines more than 90 federal policy actions across innovation, infrastructure, security, and education.

At a high level, there are two clear priorities for actions that the White House aims to take in the coming weeks and months: speed and competitiveness. The Plan thus couches U.S. AI strategy in the stark, zero-sum terms of “winning the AI race.”

There’s a lot to unpack. The Plan touches on semiconductor manufacturing, scientific research, interoperability, AI adoption in government, combating synthetic media, and geopolitical strategy (especially with respect to countering China)—to name just some of the issues covered. If you are reading this, however, chances are that you are primarily interested in the implications for education, and so I’ve partnered with Christian Pinedo, who leads aiEDU’s policy and advocacy work, to put together an analysis that focuses on the implications for the K-12 system.

Steps forward from last month’s executive order

In April, I wrote about the executive order on “Advancing Artificial Intelligence Education for American Youth.” That EO focused on AI literacy and established AI education as a federal priority, with several important tenets that align with aiEDU and other advocates’ recommendations: AI Readiness for all students, capacity building for educators, integration of AI literacy into core subjects, alignment to future workforce skills, and mobilization of the K-12 ecosystem. It was a valuable call to action that created air cover for civil society, philanthropy, and the private sector. But I was not the only commentator to note that the broad actions laid out are a “starting gun, not the finish line.”

In the weeks that followed, aiEDU and the EdSAFE AI Alliance co-hosted several dozen leading organizations working at the intersection of AI and K-12 education to write a Blueprint for AI Education. Upon our read of the American AI Action Plan, it’s encouraging to see several important areas of alignment.

Here are some prominent examples (AI Action Plan in bold, with corresponding Blueprint recommendations italicized).

Action Plan: Prioritize AI skill development as a core objective, including career and technical education (CTE), workforce training, apprenticeships (p. 6)

• Blueprint: Embed AI literacy into CTE, dual-enrollment, work-based learning, and apprenticeships (p.15)

Action Plan: Establish the AI Workforce Research Hub under DOL to evaluate AI’s labor‑market impact (p. 6)

• Blueprint: Urges a national network of “AI Workforce Hubs” to generate labor‑market intelligence and guide policy (p. 14)

Action Plan: Issue guidance clarifying that many AI‑literacy and AI‑skill programs may qualify as educational assistance under IRC §132 (p. 6)

• Blueprint: Recommends using the tax code so employers can reimburse workers tax‑free for AI up‑skilling (p. 9)

Action Plan: Partner with state and local governments to create industry‑driven training programs for priority AI infrastructure occupations (p. 17)

• Blueprint : Proposes “AI Learning Hubs” linking K‑12, higher‑ed, workforce boards, and employers to deliver demand‑driven training (p. 8)

Action Plan: Provide guidance to state & local CTE systems … expand Registered Apprenticeships in AI‑critical occupations (p. 17)

• Blueprint: Pushes for refreshed CTE curricula and a nationwide scale‑up of AI‑aligned registered apprenticeships (p. 15)

For those of us working to make AI Readiness a reality in schools and classrooms across the country, it matters that federal language is beginning to reflect the real-world needs we’ve long advocated for.

While the Action Plan isn’t solely focused on education, it’s some of the most explicit language ever released by the federal government about the importance of AI Readiness, which we define as AI literacy along with complementary skills such as critical thinking, problem solving, and collaboration.

The geopolitics of education: AI Readiness as a national strategic priority

To understand why AI education is now a matter of national urgency, we have to look at the broader geopolitical stage. The thrust of America’s AI Action Plan is not focused on education, but rather, as written at the top of page one: the “race to achieve global dominance in artificial intelligence.”

The Plan goes on to say, “Whoever has the largest AI ecosystem will set global AI standards and reap broad economic and military benefits. Just like we won the space race, it is imperative that the United States and its allies win this race…Winning the AI race will usher in a new golden age of human flourishing, economic competitiveness, and national security for the American people.”

It’s worth examining how we arrived at such stark rhetoric. It has been a long time coming, and China looms large.

In 2017, the National Security Council had publicly labeled China a “strategic competitor,” ending a four-decade experiment in warmer relations that had until then aimed to bring China into the international order through economic cooperation. Subsequent trade and technology clashes featured tariffs, Huawei’s addition to the Entity List (an official list of foreign companies that are believed to be a threat to U.S. national security interests), and export controls on semiconductors.

The Biden Administration largely maintained that course. Just six days into President Biden’s term, press secretary Jen Psaki framed U.S.-China ties as “a serious competition…and a defining feature of the 21st century.” Trump-era tariffs remained in place, Huawei stayed on the Entity List, and in 2021 Biden told Congress that “we’re in competition with China and other countries to win the 21st Century.” In 2022 the Department of Commerce unveiled rules aimed to choke off China’s access to cutting edge GPUs being used to train frontier LLMs.

Then came the public debut of large language models (LLMs) with OpenAI’s release of ChatGPT on November 30, 2022. What had been a policy debate among elites became a kitchen-table issue. Overnight, large-language models became a barometer of national prowess: American lawmakers cited ChatGPT’s viral success as proof that an open U.S. ecosystem can leapfrog state-directed rivals, while Chinese regulators accelerated their own “generative AI” rules to guide domestic champions.

Amidst heating competition, China has treated AI education as a full-spectrum national priority. As far back as 2017, the country published a “New Generation AI Development Plan” that put talent pipelines and education on par with chip development and innovation. In 2018, China’s Ministry of Education (MOE) issued the “Artificial Intelligence Innovation Action Plan for Institutions of Higher Education,” seeding new AI institutes at 35 universities. Today, more than 626 Chinese colleges now offer AI-related majors. The plan also instructs schools to “introduce AI into elementary and middle-school education” and build a multi-level AI education system ladders from K-12 to vocational and university tracks, paired with a public platform that popularizes AI among youth and the broader public. The plan also launched teacher outreach programs, including the development of pre-service courses and professional development resources so that every teacher can deliver “intelligent education.”

In March 2025, the MOE announced that AI will be embedded “into teaching efforts, textbooks and the school curriculum” across all grades, saying the goal is to “cultivate the basic abilities of teachers and students…[and] shape the core competitiveness of innovative talents.” A companion directive makes AI literacy compulsory nationwide from Grade 1 starting in September of this year. Every student must receive at least eight hours of AI instruction per year, progressing toward building simple algorithms and reason about AI ethics.

Earlier this month, China launched short-form “micro-majors” and 2,600 certificates to let non-CS students layer AI skills onto traditional degrees. And just this weekend, China released another “Action Plan,” this time pushing for global governance of AI (no doubt aimed at highlighting the void left by US retrenchment on AI governance and regulation; we’d guess it’s more performative than substantive).

Collectively, these moves illustrate Beijing’s deliberate strategy to tightly align educational policy with overarching national strategic ambitions. Unlike the decentralized educational landscape in the United States, China’s centralized model allows rapid, uniform implementation of reforms. Yet, despite its operational efficiency, China’s system faces inherent challenges in fostering innovation, independent thought, creative risk-taking, and collaborative problem-solving—qualities critical for sustained technological leadership.

Within this geopolitical context, the American AI Action Plan is a clear signal from the U.S. government about its intent to meet China’s comprehensive, top-down approach with our own strategy and vision for the future.

Game on.

Opening the Aperture to AI Readiness

Clearly, China’s comprehensive, top-down model demonstrates what a rapid, nationwide rollout of AI education can look like. But precisely because the U.S. educational system is decentralized, our path forward must look different. Rather than mirroring China’s approach, we have an opportunity—and indeed, a responsibility—to broaden our lens beyond narrow workforce metrics and instead embrace a more holistic vision of AI Readiness.

AI Readiness isn’t just about employability. It’s about helping young people navigate a world where AI is shaping how they learn, connect, form relationships, consume media, and make sense of what's real. Across the country, students are already engaging with AI in deeply personal ways—using AI chatbots for emotional support, encountering algorithmically curated news and content, and experimenting with generative tools in their creative lives. These experiences aren't confined to classrooms. They're woven into students’ social lives, their civic awareness, and their digital identities.

Parents and educators are seeing this firsthand: students forming attachments to AI-powered companions, navigating misinformation shaped by opaque algorithms, and struggling to parse what’s generated, what’s manipulated, and what’s true. If we teach AI Readiness only as a technical or career skill, we’ll miss the terrain students are already walking through.

That’s why AI education must be developmentally grounded, contextually literate, and civically engaged. It should help students reflect on how technology is influencing their thinking and well-being. It should frame AI not just as a tool to use, but as a system to understand and shape.

If we fail to widen the aperture of AI Readiness, we risk designing education systems that may check every policy and tech box, but miss the very real, human experiences of students navigating identity, belonging, and truth in an AI-saturated world. The point isn’t to teach every student to be a prompt engineer. The point is to give them the agency, context, and support to be human in an AI-powered world.

“AI Readiness” is the only way America can win this race

A broader mandate for AI Readiness beyond proficiency in the use of AI is critical to America competing on the global stage.

Even if our political environment were de-polarized, and there was a massive influx of federal funding for education (instead of broad cuts), the U.S. loses in a head to head drag race. We can’t out-credential China, nor win on hours of prompt engineering training. Beijing is already scaling that playbook with the efficiency that Washington can’t (and shouldn’t) replicate.

The only way we can win is by doubling down on the ingredients of American ingenuity and innovation that China’s top-down model chronically struggles to cultivate: critical thinking, creative problem solving, collaboration and agency. The U.S. “wins” not by out-scaling China, but by building systems that reflect democratic values, pluralism, and ingenuity.

Speed matters; but in education, speed without strategy leads to churn. What’s urgent isn’t just how fast we move, but whether we’re moving toward systems that honor student agency, educator expertise, and long-term trust. The Administration’s Plan puts a stopwatch on federal agencies; states will feel the pressure to keep pace. Yet racing to mandate “AI Everywhere” courses risks producing checkbox competencies that expire with the next model upgrade. Instead, federal guidance and grant programs should reward initiatives that demonstrate gains not just in AI literacy, but in critical thinking and durable skills. The kind of outcomes whose value persists even as specific tools become obsolete.

China’s current surge is largely about distributing AI software across sectors (“AI + finance,” “AI + manufacturing,” etc.). Useful, but merely learning to operate those tools is table stakes. The U.S. should frame AI as an amplifier of uniquely human advantages: curiosity, narrative reasoning, ethical judgment. As the Teach AI & OECD’s 2025 AI literacy framework puts it: we must prepare students not just to use AI, but to question, critique, and govern it.

Our education system is messy, yes—but that heterogeneity is a feature when it comes to experimentation. In part with help from aiEDU, States like Ohio, Colorado, Michigan and California are rolling out a range of statewide, regional, and local AI initiatives that will help us identify the most effective approaches to systems change.

Moving from Plan to Practice: States and districts hold the pen

The decentralization of our education system poses a huge challenge to the success of the AI Action Plan. The real work will happen in state education agencies, school districts, and individual classrooms. The blueprint that aiEDU co-wrote offers guidance about what this can look like. It involves aligning competencies across core subjects, instructional resources, robust professional development, state and district AI Readiness strategies and implementation plans, and a massive influx of philanthropic support to drive public-private partnerships.

The AI Action Plan creates the conditions for this, not in the form of new federal funding, but rather from braided streams across the Department of Labor, National Science Foundation, Department of Commerce, and Department of Education. This will require education leaders to collaborate across sectors in new ways. Workforce boards and chambers of commerce need to coordinate with school districts and state departments of education. Labor economists and economic development experts need to plug into workstreams to overhaul high quality instructional materials (HQIM). At the same time, most districts are managing this with shrinking budgets, overextended staff, and competing priorities. Any implementation strategy has to meet them where they are. Not with a checklist, but with a support system.None of this is new, but what’s changed is this kind of coordination is no longer a nice-to-have; it’s a prerequisite.

Just before the Action Plan’s release, the U.S. Department of Education issued a Dear Colleague letter outlining how existing formula and discretionary grants can support AI-related activities. From AI-driven tutoring tools to educator professional development and curriculum development, the letter gives states and districts permission and encouragement to integrate AI into their ESSA and IDEA-aligned work.

At the same time, we need to center on educators’ voices to define success. Frameworks like our AI Readiness Framework are useful precisely because they balance technical fluency with ethical reasoning, student agency, and equity. These are not soft metrics, they are the scaffolding for long-term sustainability—and more importantly, they reflect the existing motivations of individual teachers and education leaders who may be new to AI, but have long understood the importance of critical thinking and durable skills.

Public-private partnerships are necessary, but not neutral

A core strategy of the AI Action Plan is the cultivation of private sector and civil society initiatives to drive this work forward. In June, the White House announced the “Pledge to America’s Youth,” with more than 60 companies and nonprofits committing to support AI education through resources, training, software, and funding.

To be sure, industry has a critical role to play over the coming months and years—not just to help inform career pipelines but to direct funding to maintain the momentum. But we should also be careful about overly relying on corporations lest AI education become hyper-focused on AI tooling. AI Readiness isn’t just about using AI tools. It touches everything from core curriculum to teacher PD. It’s about systems change, and that’s why philanthropy has such an important role to play.

A recent deal between NVIDIA and the State of Oregon is instructive. In April, Governor Tina Kotek and Executive Director of the state’s Higher Education Coordinating Commission signed an MOU with the company to expand access to AI opportunities in colleges and schools. The partnership quickly drew a litany of concerns about the incentives behind the initiative, which calls for “integrating AI technologies into [the state’s] higher education, research, and economic frameworks,” and leverage “NVIDIA’s resources, such as its Deep Learning Institute (DLI), to create robust learning pathways for students, professionals, and mid-career individuals.”

NVIDIA’s Deep Learning Institute is the company’s certification platform, and while it provides genuinely valuable training, it is strategically designed to advance NVIDIA’s core business objectives by fostering an ecosystem around the company’s software stack, driving hardware sales, and creating a moat by establishing its programming models (especially CIDA) as the industry standard.

NVIDIA can no doubt add value to Oregon’s AI education strategy, but it should not be the cornerstone. Educators and education leaders—not vendors—should be the ones who shape school transformation for the age of AI. Still, even the best partnerships won’t change the fact that many school systems are at capacity. Leaders need more than permission—they need a path. For some districts, AI Readiness might start in a career and technical education program; for others, it might begin with teacher PD or a media literacy unit. What matters is not uniform rollout, but coordinated, values-driven entry points.

Philanthropy, especially from organizations who do not have a direct stake in any one AI product or tool, are much better placed to advance this work. That’s why our work with the Ohio Lt. Governor and Ohio Department of Education & Workforce—which was backed by a mix of local funding from traditional companies like J.M. Smucker, national foundations like the Patrick J. McGovern Foundation, and significant state funding—has garnered broad stakeholder buy-in from schools, districts, regional service centers, development agencies, education nonprofits, and state policymakers.

From building momentum to building a movement

Between the executive order on AI literacy and the Action Plan, the stage is now set. We have momentum, visibility, and national alignment on the importance of AI education—not just as something fundamental to ensuring that all students have the opportunity to thrive, but also as an effort at the center of U.S. national security. And as with any major system change, community voice must be at the table. Families and students aren’t just recipients of AI Readiness, they’re co-creators. They’ll determine whether this work builds trust or deepens resistance. There’s something for everyone, and this is genuinely one of the few issues that resonates across party and geography. Whether you’re a venture capitalist in Silicon Valley, or a coil bobbins manufacturer in Cleveland, AI Readiness matters.

Now that we find ourselves in the zeitgeist, and the implementation phase of the work, we will face a test of values:

• Are we centering students’ best interests in designing or redesigning education systems?

• Are we giving educators on the front lines the support and resources they need?

• Are we building for scale and impact, or just for press ops and ribbon cutting ceremonies?

• Are we preparing students to become AI users, or to leverage their own human advantage and lead us into the future?

Big ideas can’t by themselves change complex human systems. People do. And they require steady, principled, collaborative work.

Let’s start by ensuring that every state has an AI Readiness strategy by 2026. Not just a press release. A real plan—resourced, grounded in local context, and accountable to students and educators alike.

We don’t have a moment to lose.