Preparing Students for an AI-Powered Future: What the DOL's AI Literacy Framework Means for K-12

The federal government is signaling urgency, and educators need to pay attention. On February 13, 2026, the U.S. Department of Labor's Employment and Training Administration released Training and Employment Notice No. 07-25 (TEN 07-25), which includes the most detailed federal guidance yet on what AI literacy means and how it should be delivered. The attached AI Literacy Framework lays out five foundational content areas and seven delivery principles that will shape how AI education is designed, funded, and evaluated across the United States.

While the framework is technically aimed at the workforce development system, its implications for K-12 education are profound. Students who graduate without understanding how to use, evaluate, and think critically about AI tools will be at a serious disadvantage in the labor market that this framework is preparing for. If you are a teacher, administrator, curriculum designer, or parent, this document is essential reading.

What Is TEN 07-25?

A Training and Employment Notice (TEN) is a formal communication from the DOL's Employment and Training Administration that provides guidance, resources, and best practices to the public workforce system. Unlike regulations or mandates, TENs offer voluntary guidance to help states, local workforce boards, training providers, and educational institutions design better programs.

TEN 07-25 was released by Assistant Secretary for Employment and Training Henry Mack, Ed.D. and Chief Innovation Officer Taylor Stockton. The accompanying AI Literacy Framework provides a structured approach to understanding what AI literacy actually means in practical terms and how to deliver it effectively across industries, roles, and learning environments.

"The Department of Labor is committed to making sure all American workers are able to share in the prosperity that AI will create for our economy."

-- Secretary of Labor Lori Chavez-DeRemer

The framework is designed to be flexible enough to apply across industries and job roles while remaining specific enough to guide meaningful program design. It builds on a growing foundation of federal AI education policy, including Executive Order 14277 on Advancing Artificial Intelligence Education for American Youth, the DOL's America's Talent Strategy, TEGL 03-25 on using WIOA funds for AI skill development, and the Department of Education's Dear Colleague Letter from July 2025.

The Five Foundational Content Areas

The framework organizes AI literacy into five interconnected content areas. Together, they describe the full arc of competent AI use: understanding what AI is, knowing where it applies, directing it skillfully, evaluating what it produces, and using it responsibly. These are not abstract categories. Each one maps to specific, observable skills that workers and students need to develop.

1. Understand AI Principles

Before anyone can use AI effectively, they need to understand what it actually is and how it works. This content area covers the foundational concepts: how AI systems recognize patterns and generate outputs, the difference between training and inference, the capabilities and limitations of current AI tools, why AI produces probabilistic outputs rather than definitive answers, the phenomenon of hallucinations, and the critical importance of human oversight. The framework emphasizes that every AI system reflects human design choices about data, goals, and parameters, and that AI works across modalities including text, images, and audio.

2. Explore AI Uses

AI is not one tool; it is an expanding ecosystem of capabilities. This area focuses on helping learners recognize the range of real-world AI applications: productivity tools for drafting documents and automating routine tasks, information support systems for analyzing data and research, creative assistance for generating visual, written, and audio content, task-specific applications tailored to particular industries, and decision-support systems that help professionals weigh options and outcomes. The framework stresses that exposure should vary by industry and role, helping learners see how AI fits into their specific context.

3. Direct AI Effectively

This is where AI literacy moves from understanding to action. Directing AI effectively means knowing how to communicate with AI tools to get useful results. The framework identifies key skills including contextual framing (providing background and purpose), clear instruction structure and prompting techniques, supplying relevant input data and examples, iterating on results to improve quality, and recognizing how vague or poorly structured prompts lead to poor outputs. Critically, the framework treats prompting as a communication skill, not merely a technical one.

4. Evaluate AI Outputs

Generating an AI output is only half the process. The other half, and arguably the more important half, is knowing what to do with it. This content area covers verifying factual accuracy against trusted sources, assessing completeness and identifying what is missing, spotting logical gaps and inconsistencies, evaluating whether the output aligns with the user's original intent, and applying human judgment and domain expertise to decide whether to use, revise, or discard what AI produces. The core principle is clear: workers and students must remain in control. The human's role is curatorial, exercising judgment at every stage.

5. Use AI Responsibly

Responsible use is not an afterthought in this framework; it is a core component of AI literacy. As AI tools become more embedded in daily workflows, users must understand the boundaries of appropriate use. This area includes protecting sensitive and confidential information, following workplace and institutional policies, avoiding misuse such as plagiarism and impersonation, managing risk in high-stakes settings where AI errors could have serious consequences, and maintaining personal accountability for outcomes. The framework is explicit: regardless of what AI generates, the human user is responsible for how that output is applied.

The Seven Delivery Principles

The framework does not just describe what to teach. It provides detailed guidance on how to teach it. The seven delivery principles are designed to ensure that AI literacy programs are effective, inclusive, and sustainable across different contexts.

1. Enable Experiential Learning

People learn AI by doing, not by reading about it. Programs should embed hands-on practice with real AI tools into authentic tasks such as writing, research, data analysis, and creative projects. The framework calls for progressive difficulty and live feedback, moving learners from guided exploration to independent application. For K-12 educators, this means that slide decks and lectures about AI are not enough. Students need to interact with AI tools directly, with appropriate scaffolding and supervision.

2. Embed Learning in Context

AI literacy sticks when it is tied to a learner's actual work or field of study. This principle calls for using industry-specific examples, aligning content with occupational tasks, and integrating AI literacy into existing career and technical education (CTE) curricula and apprenticeship programs. In a K-12 setting, this means teaching AI within science class, social studies, English, art, and every other subject area rather than treating it as a standalone technology elective.

3. Build Complementary Human Skills

This may be the most important principle in the entire framework. AI tools are amplifiers of human input. The quality of what AI produces depends heavily on the skills, knowledge, and judgment of the person using it. The framework identifies five areas of complementary human skills that should be developed alongside AI literacy:

• Critical thinking -- the ability to interrogate, test, and evaluate AI outputs using logic and evidence
• Creativity -- applying aesthetic judgment, purpose, and originality to AI-generated raw material
• Communication -- revising AI drafts for tone, clarity, persuasiveness, and audience, and structuring prompts effectively
• Values-based decision-making -- navigating ambiguous situations where legal, organizational, or personal values are at stake
• Domain expertise -- deep subject-matter knowledge that dramatically increases AI's usefulness to the individual

The insight here is powerful: these human skills are what make AI useful rather than misleading, and what make people valuable rather than replaceable.

4. Address Prerequisites to AI Literacy

AI literacy does not exist in a vacuum. Learners need foundational digital literacy skills, access to devices, reliable internet connectivity, and basic comfort with technology before they can engage meaningfully with AI tools. The framework calls on program designers to assess and address these prerequisites, ensuring that gaps in basic digital access and skills do not become barriers to AI literacy. For schools, this means equity is not optional. Districts must ensure that all students, regardless of socioeconomic background, have the infrastructure needed to participate.

5. Create Pathways for Continued Learning

AI literacy is not a one-time certification. The framework envisions stackable progressions that move learners from foundational AI awareness toward deeper proficiency, including advanced tracks for those who want to build AI systems, pursue entrepreneurship, or develop specialized expertise. For K-12, this means thinking in terms of learning progressions from elementary exposure through middle school application to high school mastery, with clear connections to postsecondary and career pathways.

6. Prepare Enabling Roles

A program is only as strong as the people delivering it. This principle focuses on training the trainers: managers, mentors, instructional coaches, and peer champions who will support AI literacy across organizations and schools. The framework advocates for train-the-trainer models that build internal capacity rather than relying on outside experts. For school districts, this means investing in professional development that empowers teachers and instructional leaders to become confident AI educators themselves.

7. Design for Agility

AI evolves faster than traditional curricula. A lesson plan written in September may reference tools or capabilities that have fundamentally changed by January. The framework calls for modular content, feedback-driven revision, and regular updates so that programs remain current and relevant. This principle is a direct challenge to the way most schools develop curriculum, and it demands a shift toward more flexible, iterative approaches to instructional design.

The Broader Policy Context

TEN 07-25 does not exist in isolation. It is one piece of a rapidly accelerating federal push to embed AI literacy across American education and workforce systems. The policy landscape includes:

• Executive Order 14277 (April 2025) -- Created the White House Task Force on AI Education, directed agencies to promote AI literacy in K-12 and postsecondary education, launched the Presidential AI Challenge, and called for expanding AI-focused registered apprenticeships and dual-enrollment courses.
• Department of Education Dear Colleague Letter (July 2025) -- Encouraged schools and higher education institutions to integrate AI education into curricula and provided guidance on responsible classroom use of AI tools.
• TEGL 03-25 (August 2025) -- Authorized the use of Workforce Innovation and Opportunity Act (WIOA) funds for AI skill development, opening a significant federal funding stream for AI literacy programs.
• America's Talent Strategy (August 2025) -- A joint publication by the Departments of Labor, Commerce, and Education that established a comprehensive vision for building the nation's AI-ready workforce.

Together, these actions form a coherent and accelerating federal strategy. The direction is unmistakable: the federal government considers AI literacy to be a national priority on par with traditional reading, writing, and mathematics.

What This Means for K-12 Educators

Although the AI Literacy Framework is primarily aimed at the workforce development system, every element of it has direct implications for K-12 education. Here is what educators and administrators should take away:

The five content areas are a curriculum blueprint. Schools designing AI literacy programs no longer need to guess at what to include. The framework provides a clear, federally-endorsed structure: teach students what AI is, where it is used, how to direct it, how to evaluate its outputs, and how to use it responsibly. These five areas can be mapped onto existing subject areas across grade levels.

Human skills are not separate from AI skills. The framework's emphasis on critical thinking, creativity, communication, values-based decision-making, and domain expertise validates what great educators have always known: teaching students to think well is the most future-proof investment a school can make. AI makes these skills more important, not less.

Hands-on practice is non-negotiable. The experiential learning principle makes clear that AI literacy cannot be delivered through lectures and readings alone. Students need structured opportunities to work with AI tools, make mistakes, iterate, and build genuine competence. Schools that ban AI tools entirely are not just missing an opportunity; they are leaving students unprepared.

Equity must be addressed head-on. The prerequisites principle is a direct call to action for districts with digital access gaps. AI literacy programs that only reach students with home internet and personal devices will deepen existing inequities rather than close them.

The framework is voluntary today, but the direction is clear. Federal policy moves in stages: voluntary guidance, then incentivized adoption through funding streams like WIOA, then eventually standardized expectations. Schools that align with this framework now will be positioned for funding opportunities and will avoid the scramble of reactive compliance later.

"To build the next great American talent pipeline, we must equip all students with the skills necessary to address tomorrow's challenges."

-- Secretary of Education Linda McMahon

Start Now, Not Later

The AI Literacy Framework is a clear signal. The federal government has defined what AI literacy means, described how it should be taught, and opened funding pathways to support it. The schools that move first will serve their students best.

You do not need to wait for your state, district, or administration to issue a mandate. The framework is a resource, and it is available now. Start by auditing your current curriculum against the five content areas. Identify where AI literacy fits naturally into existing courses. Invest in professional development so your teachers feel confident. And build programs that emphasize the human skills that make AI a tool for empowerment rather than replacement.

Evolve AI Institute offers free, standards-aligned AI literacy lesson plans designed for K-12 classrooms. Our 14-lesson curriculum covers foundational AI concepts, hands-on activities, ethical reasoning, and real-world applications, aligned with CSTA standards and now with the DOL framework. Whether you need a single introductory lesson or a comprehensive semester-long program, the resources are ready for you.

For schools and districts seeking deeper support, including custom curriculum development, professional development workshops, and strategic planning for AI integration, schedule a free consultation with our team. We help educators move from awareness to action, one classroom at a time.