The U.S. Department of Labor’s Employment and Training Administration published a national AI Literacy Framework on February 13, 2026, through Training and Employment Notice 07-25. It establishes five foundational content areas and seven delivery principles to guide how employers, schools, workforce boards, and training providers build AI literacy programs. The framework is voluntary and does not impose new regulatory requirements on companies or workers.
Why Did the Department of Labor Release an AI Literacy Framework?
The framework responds to a straightforward problem: AI is reshaping how work gets done across virtually every sector, and the country lacks a shared vocabulary or common structure for training workers to use it. Before this release, AI literacy efforts across the United States operated in largely fragmented fashion. Community colleges developed their own curricula, private bootcamps marketed proprietary programs, and state workforce agencies ran pilot projects that rarely scaled.
The federal framework is intended to bring coherence to these efforts without stifling local innovation. Rather than mandate a specific curriculum, it offers a structured set of principles that states, employers, and educators can adapt to their own contexts.
The timing reflects genuine urgency. A 2025 McKinsey Global Institute report estimated that generative AI could automate tasks accounting for up to 30% of hours currently worked in the United States. Labor officials, however, believe the fear of mass displacement is overstated, arguing that many employers are keeping the same number of employees but doing more with AI rather than reducing headcount. The framework reflects that view: its focus is on augmenting workers, not replacing them.
What Are the Five Foundational Content Areas?
The five foundational content areas cover understanding the basics of how AI works, exploring AI applications and use cases, prompting AI effectively, evaluating AI outputs for accuracy and relevance, and managing AI responsibly through safe and secure usage practices.
Each area addresses a distinct gap in how most workers currently encounter AI tools:
Understanding how AI works moves beyond surface-level familiarity. Workers learn core concepts, capabilities, and limitations so they can engage with AI systems critically rather than just operationally.
Exploring AI applications helps workers recognize which tools are relevant to their roles and industries, and how those tools can complement rather than displace human expertise.
Prompting AI effectively is the practical skill of providing AI systems with the right context to generate useful, accurate outputs. As generative AI becomes embedded in daily workflows, the ability to direct AI well is becoming a baseline job skill.
Evaluating AI outputs trains workers to assess what AI produces for completeness, accuracy, and appropriateness before acting on it. This is the check against overreliance.
Managing AI responsibly covers safe and secure usage, including cybersecurity practices, recognizing the limits of AI authority, protecting sensitive data, and complying with legal and workplace requirements. Responsible use of AI is treated as a core component of literacy, not an advanced topic.
What Are the Seven Delivery Principles?
The seven delivery principles are enabling experiential learning, building complementary human skills, creating pathways for continued learning, designing for agility, embedding learning in context, addressing prerequisites to AI literacy, and preparing enabling roles.
Several of these principles carry particular weight for employers designing internal training programs:
Enabling experiential learning prioritizes hands-on practice over passive instruction. Workers learn AI literacy most effectively by using AI tools in realistic scenarios, not by reading about them.
Building complementary human skills is a deliberate counterweight to the assumption that AI training should focus entirely on technical skills. The framework treats critical thinking, judgment, communication, and ethical reasoning as skills that AI augments rather than replaces, and that therefore need to be developed alongside AI proficiency.
Designing for agility acknowledges that AI capabilities are changing faster than any fixed curriculum can track. Programs built on this principle are structured to update continuously rather than become outdated within months of launch.
Addressing prerequisites to AI literacy recognizes that not all workers start from the same baseline. Digital literacy, language access, and basic technology familiarity are prerequisites that must be addressed before AI-specific training can be effective.
Approximately 77% of organizations were actively working on AI governance as of 2025, according to IAPP research, suggesting that workforce AI readiness is now a board-level concern, not just an HR program. The delivery principles in this framework give companies a structure for translating that concern into practice.
Is the Framework Mandatory for Employers?
No. The framework does not impose any new requirements on either companies or workers and instead offers a voluntary playbook for AI literacy. The Department of Labor’s approach reflects the current administration’s preference for guidance over regulation on AI workforce issues.
That said, the framework carries real policy weight. It advances the White House AI Action Plan released in July 2025 and America’s Talent Strategy, issued jointly by the Departments of Labor, Commerce, and Education in August 2025. Those documents establish AI literacy as a national workforce development priority. The framework also follows August 2025 guidance encouraging states and localities to use Workforce Innovation and Opportunity Act funds and governor’s reserve monies for AI skills development.
For companies, the practical significance is this: federal workforce funding is now flowing toward AI literacy, and state workforce boards, community colleges, and apprenticeship programs are being directed to align their training investments with this framework. Employers who engage with it now are better positioned to access those resources and to influence how training programs serving their industries are designed.
How Does This Framework Fit Into the Broader Federal AI Workforce Strategy?
The DOL framework is one component of a coordinated federal effort. It complements the Department of Education’s July 2025 guidance on AI in schools, the White House AI Action Plan, and the AI Workforce Research Hub established by the Trump administration to study how AI is reshaping labor market demand.
Labor officials describe foundational AI literacy as the first priority in a broader progression, not the entire answer. The framework is designed to serve as a baseline from which workers can progress to deeper, role-specific AI skills. Partnering with regional employers is identified as a key step for training providers seeking to understand which AI tools are most relevant to local labor markets.
The framework will continue to evolve. The Employment and Training Administration welcomes stakeholder feedback on effective AI literacy implementation, barriers to success, and opportunities for additional guidance. Companies and training providers can participate through aiworkforce@dol.gov.
What Should Companies Do With This Framework?
For privacy, compliance, and HR professionals, the framework provides a practical starting point for building or benchmarking internal AI literacy programs. Several applications are worth considering immediately:
The five foundational content areas map directly onto the skills gaps most organizations are trying to close: employees who know how to prompt AI effectively, who can evaluate its outputs critically, and who understand responsible use requirements are better equipped to work within existing governance structures.
The delivery principles offer a quality check for existing programs. If your current AI training does not include experiential learning, does not address prerequisites for workers with limited digital backgrounds, or lacks a pathway for continued development as tools evolve, those are addressable gaps.
The voluntary nature of the framework is also an asset. Because it is non-prescriptive, it can serve as a credible reference point in conversations with regulators, auditors, or insurers about your organization’s approach to AI workforce readiness, without locking you into a curriculum that may not fit your context.
Frequently Asked Questions
When was the DOL AI Literacy Framework published? February 13, 2026, through Training and Employment Notice 07-25 issued by the Employment and Training Administration.
Does the framework apply to private-sector employers? It applies as voluntary guidance. Private employers are not required to adopt it, but it is designed to be adaptable across industries, roles, and learning environments.
What are the five foundational content areas? Understanding how AI works, exploring AI uses, prompting AI effectively, evaluating AI outputs, and managing AI responsibly.
What are the seven delivery principles? Enabling experiential learning, building complementary human skills, creating pathways for continued learning, designing for agility, embedding learning in context, addressing prerequisites to AI literacy, and preparing enabling roles.
Can organizations access WIOA funding to build AI literacy programs aligned with this framework? Yes. Guidance issued in August 2025 encouraged states and localities to use Workforce Innovation and Opportunity Act funds for AI skills development, and the framework is intended to guide how those programs are designed.
Where can stakeholders provide feedback? Through aiworkforce@dol.gov. The ETA has indicated the framework will continue to evolve based on input from employers, training providers, state and local agencies, and education stakeholders.
