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.
"Explore AI Uses" is the second foundational content area of the DOL AI Literacy Framework (TEN 07-25). It calls for exposing workers to real workplace AI applications, productivity drafting, information support, creative assistance, task-specific automation, and decision support, so they build judgment about when and how to apply AI, and where human input remains essential.
Last verified against the DOL source: August 20, 2026. What changed
Score your program on these five checkpointsWhat the framework says
Paraphrased: a core element of AI literacy is understanding how AI is being used across real-world workplace settings. Workers benefit from exposure to practical applications showing how AI tools "support tasks, augment decision-making, and streamline workstreams." Because use varies by industry, occupation, and context, "exploration builds familiarity and judgment."
The five example content areas:
- 2.1
Productivity tools
Using AI to draft written documents, create draft presentation outlines, or analyze reports, allowing workers to move more efficiently through common tasks in a workflow.
- 2.2
Information support
Leveraging AI to answer questions, surface relevant background information, or create learning content tailored to specific workplace needs.
- 2.3
Creative assistance
Generating initial drafts of marketing copy, naming ideas, graphic options, or other creative assets that workers can then refine and improve.
- 2.4
Task-specific applications
Applying AI to solve targeted problems such as writing code snippets, transcribing audio, automating data entry, or organizing complex schedules.
- 2.5
Decision-support systems
Using AI tools to generate recommendations, risk assessments, or forecasts that help inform and augment human decision-making.
Reproduced from the public framework text under 17 U.S.C. section 105. Read the source on dol.gov.
What it means in practice
This area is about range with judgment. A literate worker has personally tried AI on at least one task from most of these categories and has felt the difference between where AI shines (first drafts, transcription, summarization) and where it needs tight supervision (decision support, anything customer-facing). The framework's repeated phrase, "where human input remains essential", is the point: exploration is calibration. Workers who have only ever used AI to draft emails have a flattened sense of both the opportunity and the risk.
How programs fail this provision
Two failure modes. First, single-use-case training: the whole course is prompting a chatbot to write text, so learners never see data analysis, transcription, or decision support, and drastically under-estimate the tool's scope. Second, demo-only exposure: learners watch a presenter explore instead of exploring themselves, which violates Delivery Principle 1 (experiential learning) at the same time. Inspection question: how many distinct application categories did each learner personally try?
The five checkpoints this provision scores on
Learners practice using AI for productivity tasks: drafting documents, creating presentation outlines, or analyzing reports.
Framework marker: Productivity tools
Learners practice using AI for information support: answering questions, surfacing background material, or creating tailored learning content.
Framework marker: Information support
Learners practice using AI for creative assistance: first drafts of copy, naming ideas, or graphic options that humans then refine.
Framework marker: Creative assistance
Learners see task-specific AI applications relevant to their field (e.g., code snippets, transcription, data-entry automation, schedule organization).
Framework marker: Task-specific applications
Learners are exposed to AI decision-support uses (recommendations, risk assessments, forecasts) framed as informing, not replacing, human decisions.
Framework marker: Decision-support systems
How GAGE addresses it
In AI Literacy and Professional Conduct, this provision sits in Practical AI Workflow Design and Prompt Engineering and Agentic AI and Workforce Integration. Every topic in the program ends in a mastery assessment, and the teach-back gate asks the learner to explain the material back in their own words before it counts as understood, which is the difference between a program that covers a checkpoint and one that can evidence it.
Module titles come from the program registry, so this cannot drift away from what the program contains. GAGE is a private company: the program is built to the DOL framework, and DOL neither certifies nor endorses it or any other program.
Questions about this provision
Is "Explore AI Uses" about specific products (ChatGPT, Copilot, etc.)?
The framework is tool-agnostic, it describes categories of application (productivity, information support, creative, task-specific, decision support), not brands, which keeps programs current as products change.
Why pair exploration with "where human input remains essential"?
Because the framework's goal is judgment, not enthusiasm: workers should finish this area able to say not just "AI can do this" but "AI should do this, supervised, and here's why."
Does your program actually meet this provision?
Answer the five checkpoints above and the other 55, and get a dated report that scores your program provision by provision. Free, and your answers stay in your browser.
What this means for job seekers
TEN 07-25 for Job Seekers: AI Literacy Is Now a Hiring Signal
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.
Last verified against the DOL source: August 20, 2026. What changed