Address Prerequisites to AI Literacy
AI literacy efforts can only succeed if learners have the foundational tools and access needed to engage, digital literacy skills, device access, or broadband connectivity. Programs should proactively identify and address these barriers so participants have what they need to complete training and apply AI tools confidently in daily work.
"Address Prerequisites to AI Literacy" is the fourth delivery principle of the DOL AI Literacy Framework (TEN 07-25). It requires programs to proactively remove barriers to participation, digital literacy gaps, device access, and broadband connectivity, through readiness diagnostics, refreshers, access options, low-bandwidth materials, and flexible pacing.
Last verified against the DOL source: August 20, 2026. What changed
Score your program on these five checkpointsWhat the framework says
Paraphrased: AI literacy efforts "can only be successful if learners have the foundational tools and access needed to engage with training", digital literacy skills, device access, broadband connectivity. "Programs should proactively identify and address these barriers," treating prerequisites "as integral to program design."
The five example delivery approaches:
- 4.1
Evaluate baseline readiness
Starting with simple diagnostics to evaluate whether participants have the digital familiarity needed to begin using AI tools effectively, and to identify any barriers.
- 4.2
Integrate digital literacy skills
Offering light-touch refreshers or resources on digital literacy skills for participants who need to brush up on device use, app navigation, or browser tools.
- 4.3
Consider options for access support
Where device or broadband gaps exist, exploring practical solutions such as public computer labs, mobile-first content, or asynchronous formats.
- 4.4
Consider bandwidth flexibility
Considering training materials that are compatible with low-bandwidth environments and mobile devices where feasible.
- 4.5
Acknowledge different starting points
Building delivery models that accommodate a range of skill levels and learning speeds without assuming prior experience.
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 principle is the equity load-bearing wall of the framework, and it has hard engineering implications: if your AI literacy course requires a laptop, fast broadband, and fluent browser skills, you have filtered out exactly the frontline and rural workers the public workforce system exists to serve. Note the technical markers, mobile-first content, low-bandwidth compatibility, asynchronous formats. These are platform requirements, not sentiments. For workforce boards and districts, this principle is also the procurement lens: a vendor whose platform fails on a Chromebook over a weak connection fails Principle 4.
How programs fail this provision
Assumption failure: the course assumes prior digital fluency, starts at "open your ChatGPT account," and loses the bottom third of the cohort in week one, then reports completion rates without asking who never started. Second failure: video-heavy delivery that is unwatchable on a data plan. Inspection question: what does your program do for a learner with a phone, a data cap, and no home broadband?
The five checkpoints this provision scores on
The program starts with a simple diagnostic of participants' digital familiarity and barriers.
Framework marker: Evaluate baseline readiness
Light-touch digital-literacy refreshers (device use, app navigation, browser tools) are available to participants who need them.
Framework marker: Integrate digital literacy skills
Device or broadband gaps are addressed with practical options (public computer labs, mobile-first content, asynchronous formats).
Framework marker: Consider options for access support
Training materials work in low-bandwidth environments and on mobile devices where feasible.
Framework marker: Consider bandwidth flexibility
Delivery accommodates a range of skill levels and learning speeds without assuming prior experience.
Framework marker: Acknowledge different starting points
How GAGE addresses it
In AI Literacy and Professional Conduct, this provision sits in Your AI Learning Companion and Digital Foundations. 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
Why do prerequisites belong in an AI framework at all?
Because DOL addresses the *public* workforce system: without digital literacy, devices, and connectivity, AI literacy training never reaches the workers it targets. The framework treats access as "integral to program design."
Is digital literacy part of AI literacy?
Under the framework it is a prerequisite to be identified and addressed, programs are told to evaluate readiness and offer refreshers rather than assume fluency.
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 state & local agencies
TEN 07-25 for State & Local Agencies: AI Literacy Across the Public Workforce System
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