The five foundational content areas
What a program built to the DOL AI Literacy Framework teaches. Each area below opens onto its own page: the framework text, what it means in practice, how programs fail it, and the five checkpoints it scores on.
The DOL AI Literacy Framework names five foundational content areas: Understand AI Principles, Explore AI Uses, Direct AI Effectively, Evaluate AI Outputs, and Use AI Responsibly. Together they are what a voluntary AI literacy program should teach, and each carries five example content areas in the official text, published in full below.
Last verified against the DOL source: August 20, 2026. What changed
Understand AI Principles
A clear grasp of what AI is and how it works, not technical mastery, but the vocabulary and mental models needed to understand how today's AI tools operate. This foundation demystifies AI, supports more confident and accurate use, and enables workers to apply, prompt, and evaluate AI systems effectively across workplace scenarios.
- Pattern recognition and probabilistic outputs
- Capabilities and modalities
- Training and inference
- Hallucinations and accuracy limits
- Human design and oversight
Explore AI Uses
Understanding how AI is being used across real-world workplace settings. Exposure to practical applications that support tasks, augment decision-making, and streamline workstreams builds familiarity and judgment, helping workers recognize when and how to apply AI effectively and where human input remains essential. AI use varies widely by industry, occupation, and context.
- Productivity tools
- Information support
- Creative assistance
- Task-specific applications
- Decision-support systems
Direct AI Effectively
Interacting with AI systems in ways that produce useful and relevant results. Because most AI tools depend heavily on the input they receive, users must learn to provide clear instructions, include necessary context, and iterate strategically. This does not require coding skills, it requires a mental model for framing prompts, sharing information, and improving responses.
- Contextual framing
- Prompting techniques
- Supplying relevant input data
- Iterating on outputs
- Avoiding vague or misleading prompts
Evaluate AI Outputs
Assessing the quality and usefulness of AI-generated outputs. While AI can accelerate work and surface helpful insights, results require thoughtful review. Workers must evaluate whether an output is accurate, complete, and appropriate, applying their own knowledge and judgment so AI is used as a support tool, not a final authority.
- Verifying factual accuracy
- Assessing completeness and clarity
- Spotting gaps or logical errors
- Aligning with strategic intent
- Applying human judgment
Use AI Responsibly
Responsible use is a core component of AI literacy, not an advanced topic. Workers must understand the boundaries of appropriate use: recognizing the limits of AI authority, protecting sensitive data, complying with workplace or legal requirements, and maintaining accountability for outcomes.
- Protecting sensitive information
- Following workplace policies and rules
- Avoiding misuse or harm
- Managing context-specific risks
- Maintaining accountability
GAGE (Global Academy of Generative-AI Education) is a private education company, not affiliated with or endorsed by the U.S. Department of Labor. DOL does not certify or endorse training programs. Framework summaries are drawn from the public TEN 07-25 document. Read TEN 07-25 on dol.gov. Last verified: August 20, 2026.