Labor Department Shows Employers How to Boost AI Literacy for Workers: Your Guide to New Training Framework

The Department of Labor just released a comprehensive AI Literacy Framework providing employers with a roadmap for training workers to use artificial intelligence technology responsibly and effectively. The February 13 framework marks the Trump administration’s latest effort to prepare American workers for an AI-driven economy, emphasizing that “every worker will need baseline AI literacy skills to succeed, regardless of industry or occupation.” While the framework doesn’t create any new legal requirements, it signals DOL’s expectations for how employers should approach AI training – and offers practical guidance for organizations looking to upskill their workforce. Here’s an overview and steps you should take.

DOL’s AI Literacy Plan

The framework, which you can read in full here, builds on the Trump Administration’s AI Action Plan released in July 2025. Both prioritize worker training and upskilling. It defines AI literacy as “a foundational set of competencies that enable individuals to use and evaluate AI technologies responsibly, with a primary focus on generative AI.”

Absent from this framework is any discussion of worker protections, discrimination safeguards, or new regulatory requirements. This marks a departure from the Biden administration’s approach, which emphasized AI guardrails alongside worker training.

Foundational Concepts

The DOL framework starts by identifying five core competencies it believes every worker should develop.

1. Understand AI Principles

Workers need to understand how AI operates, not technical mastery, but enough to use AI confidently. This includes understanding that AI identifies statistical patterns (not “thinking”), can produce incorrect outputs (“hallucinations”), and reflects human design decisions.

2. Explore AI Uses

Workers should understand practical applications across workplace settings: using AI to draft documents, analyze reports, answer questions, generate creative assets, or support decision-making. DOL emphasizes that AI use varies by industry and context.

3. Direct AI Effectively

Because AI depends heavily on user input, workers must learn how to provide clear instructions, include necessary context, and iterate to improve results. This includes prompt techniques, supplying relevant data, and avoiding vague requests.

4. Evaluate AI Outputs

Workers need skills to assess whether AI-generated outputs are accurate, complete, and appropriate. This includes verifying facts, spotting logical errors, and applying human judgment rather than treating AI as a final authority.

5. Use AI Responsibly

Workers must understand the boundaries of appropriate use: protecting sensitive information, following workplace policies, avoiding misuse, and maintaining accountability for AI-assisted work.

The 7 Delivery Principles for Employers

The framework also offers seven principles for how employers should deliver AI training.

1. Enable Experiential Learning

Training works best through hands-on use, not abstract reading. Employers should embed AI tools into real work tasks, provide interactive exercises, and allow trial-and-error learning.

2. Embed Learning in Context

Training should be relevant to workers’ jobs and industries. The training should also use industry-specific examples, align with actual workflows, and integrate AI literacy into existing training programs rather than creating standalone courses.

3. Build Complementary Human Skills

The guidance notes that AI amplifies human capabilities, it doesn’t replace them. Training should demonstrate how AI enhances critical thinking, creativity, and communication, emphasizing that AI’s value depends on human judgment.

4. Address Prerequisites to AI Literacy

Some workers may lack digital literacy, device access, or broadband connectivity. Employers should identify and address these barriers, ensuring all employees can engage with training.

5. Create Pathways for Continued Learning

Foundational AI literacy is just the starting point. Employers will want to provide clear routes for workers to deepen skills, pursue specialized training, or transition into AI-related roles.

6. Prepare Leadership to Lead

Train managers, coaches, and team leaders separately. Each leadership position will need skills to guide others, integrate AI into operations, and support workplace adoption.

7. Design for Agility

AI evolves rapidly. Companies should build training systems that can be updated regularly, use modular content that can be refreshed, and incorporate feedback to stay current.

What Employers Should Do Now

Interested in adopting the DOL’s new framework? Here’s where to begin:

Assess Current State of AI Use

Identify where workers are already using AI tools (officially or unofficially). Survey employees about AI adoption, review workflows where AI could add value, and determine which roles need AI literacy most urgently.

Recognize and Address Employee Relations Hurdles to AI Use

Recognize and address any emotional resistance that employees may experience in the face of integration in the workplace linked to fear of job loss, loss of identity, or diminished value. Provide clear communication about how AI is intended to enhance productivity, reduce administrative burden, and support (not replace) human judgment.

Develop or Update AI Training Programs

Use DOL’s framework as a starting point to build training that fits your industry and workforce. Focus on hands-on practice with tools workers will actually use, not abstract AI concepts. Integrate training into existing onboarding and upskilling programs rather than creating standalone courses.

Create Clear AI Use Policies

If you haven’t already, establish guidelines for appropriate AI use in your workplace. Address data protection, output verification requirements, prohibited uses, and accountability standards. Make sure workers understand the boundaries before they encounter problems.

Train Managers and Team Leaders First

Equip leadership with AI literacy before rolling out broader training. They need to understand AI capabilities, guide team adoption, address worker concerns, and model appropriate use. Managers who resist or misunderstand AI will undermine workforce training efforts.

Build Pathways Beyond Basic Literacy

Think about progression: Who needs advanced AI skills? Which roles might evolve significantly due to AI? How can high performers develop deeper AI proficiency? Create clear next steps for workers who master foundational skills.

Partner with External Resources

Consider leveraging state workforce development programs, community colleges, or industry associations for AI training. Many organizations signed the White House pledge to provide free AI education resources. DOL intends to help connect employers with these offerings.

Conclusion

We’ll continue monitoring DOL guidance on AI and workforce development. Make sure you’re subscribed to Fisher Phillips’ Insight System to get updates delivered to your inbox. If you have questions about AI training programs, workplace AI policies, or compliance with employment laws in AI-enabled workplaces, contact your FP attorney, the authors of this Insight, or any member of our or our AI, Data, and Analytics Practice Group.