The Workforce of the Future Act of 2025 directs federal agencies to analyze how artificial intelligence will reshape jobs and to scale public supports that prepare people to develop and work alongside AI. It pairs a government-led analysis of data gaps, at-risk industries, and skills needs with targeted grant programs to expand emerging-technology education and to retrain workers in occupations most affected by AI.
The bill is explicitly organized around equity and durable capacity: it directs engagement with community colleges, minority-serving institutions, labor organizations, and industry, and requires evidence-building and evaluation to inform future federal investments. Compliance officers, workforce planners, and education leaders will want to note the bill’s data and reporting expectations, the allowable uses of grant funds, and the emphasis on worker participation in program design.
At a Glance
What It Does
The bill requires a joint interagency study (Labor, Commerce, Education) to identify data needs, industries most affected by AI, vulnerable demographics, and skills gaps, and it creates two federal grant streams: one run by the Department of Education to expand K–12 and postsecondary emerging-technology education, and one run by the Department of Labor to fund retraining for workers most impacted by AI.
Who It Affects
K–12 districts, community and technical colleges, minority-serving institutions (including Tribal Colleges and Universities), labor organizations, State workforce agencies, and employers in industries projected to adopt AI rapidly. The bill also affects third-party evaluators and federal program offices tasked with administering grants and collecting data.
Why It Matters
It combines near-term research (to fill workforce data gaps) with programmatic investment aimed at both pipeline (students and teachers) and incumbent workers—shaping how public funds will be used to direct training, credentialing, and industry engagement in the AI transition.
More articles like this one.
A weekly email with all the latest developments on this topic.
What This Bill Actually Does
The bill requires the Secretary of Labor, the Secretary of Commerce, and the Secretary of Education to produce a short interim analysis and a fuller final analysis on AI’s workforce impacts, then an update a few years later. Those reports must map data availability (and private ownership), identify industries and occupations likely to see the biggest AI adoption, analyze job-quality effects, and recommend how to expand training and make credentials accessible and low-cost.
The agencies must solicit input from a broad set of stakeholders—schools, labor organizations, industry, National Labs, and federal R&D offices—through public meetings or roundtables.
Title II creates two grant programs. The Department of Education program funds expansion of emerging and advanced technology education in K–12 and postsecondary institutions and separately funds teacher development and recruitment.
The Education grants are awarded to a broad set of eligible entities—State and local education agencies, community and technical colleges, minority-serving institutions, labor organizations, and workforce agencies—and may be given to consortia. Grant awards last 3–5 years; the DOE program splits available funds evenly between direct program expansion (classroom access, materials, teacher PD) and teacher recruitment/retention strategies.
The program limits equipment purchases to no more than 15 percent of an award and allows the Department to reserve a small portion for national technical assistance and evaluation.The Department of Labor program targets incumbent workers: specifically, individuals with a high school diploma or equivalent who are employed in industries projected to see the most AI growth, or who were involuntarily separated within a recent period and are UI-eligible. Labor grants fund training, skill certification, continuing education, and programs intended to place participants into higher-skilled, higher-wage roles.
The Secretary of Labor must prioritize applicants that include labor organizations representing workers in affected industries.Both programs require third-party evaluations to build an evidence base and test scalability. Grantees must report at least twice a year; DOE grantees report student and participation data disaggregated by race, ethnicity, gender, and free and reduced-price lunch eligibility, while DOL grantees report participant demographics.
Five years after the first grants are made, Education and Labor must send Congress a report with recommendations for expansion based on grantee data and evaluations.
The Five Things You Need to Know
The interagency study must produce an interim report within 6 months of enactment, a final report within 1 year, and an updated reassessment within 3 years of the final report.
The Department of Education program is authorized at $160 million for FY2026 and divides grant funds evenly between direct expansion of emerging-technology education and teacher development/recruitment efforts.
The Department of Labor program is authorized at $90 million for FY2026 and gives priority to grant applications that include labor organizations representing workers in industries projected to have the most AI growth.
Grants under both programs run 3–5 years, allow consortia applications, and impose limits and national-reserve provisions: DOE may use no more than 15% of any grant to buy equipment and may reserve up to 2.5% of program funds for national technical assistance/evaluation.
Grantees must report at least twice annually with disaggregated participant data; third‑party evaluations must assess program scalability and, for Labor grants, the impact of worker engagement on training outcomes.
Section-by-Section Breakdown
Every bill we cover gets an analysis of its key sections.
Sense of Congress on AI and work
This section lists Congress’ view that AI can both disrupt and create jobs and that policymakers should identify data, industries, worker characteristics, and skills needed for an AI-enabled economy. Practically, the provision frames the bill’s equity focus—directing later sections to prioritize access and training for populations and communities likely to be affected.
Title I definitions
Provides cross-references to existing federal definitions (AI per the National AI Initiative Act, community colleges, minority-serving institutions, labor organization, etc.). This keeps the bill’s coverage tightly linked to long‑standing statutory categories, which matters for determining eligible participants and partner institutions.
Joint interagency AI workforce reports and required content
Mandates that Labor, Commerce, and Education jointly prepare interim, final, and follow-up reports, and specifies a long list of required analyses: workforce data needs and ownership, industry and occupation projections, demographic vulnerability, skills gaps, models for delivery, and recommendations on data sharing, credentialing, and employer engagement. The Secretary of Labor may sign an MOU with Commerce and Education to coordinate. Mechanically, this section creates a tight research-to-policy loop: agencies must collect stakeholder input (schools, labor, industry, National Academies, OSTP/NSF, etc.) and produce actionable recommendations to guide grant-making.
Findings and Title II definitions
Findings set up the bill’s rationale (projected tech job growth, unfilled computing jobs, inequitable access), while the definitions in Title II expand what counts as 'emerging and advanced technology education' (from computational thinking and programming to AI and quantum computing) and specify eligible entities. The breadth of the definition makes the program flexible but also raises implementation questions about curriculum scope and credential recognition.
DOE grants to expand education and recruit teachers
Authorizes competitive grants to eligible entities (including consortia). The Secretary must award funds so that half support direct program expansion (classroom access, curricula, teacher training, mentoring) and half support teacher development/recruitment (loan repayment, tuition reimbursement, PD). Grants run 3–5 years; equipment purchases are capped at 15% per grant; up to 2.5% of program funds may be reserved for national technical assistance, evaluation, and dissemination. The Secretary must consider the joint report’s findings and barriers faced by specific demographic groups when awarding funds, and may require continuous evaluation and sustainability plans from grantees.
DOL grants for incumbent worker training
Requires the Secretary of Labor to award grants focused on workers 'most impacted' by AI—those employed in industries projected to see the largest AI adoption or recently involuntarily separated and UI-eligible. Grants fund training, certifications, continuing education, and programs designed to move participants into higher-skilled, higher-wage roles. Priority is given to applications that include labor organizations; grantees must describe worker engagement in program design and how job-quality and wage issues are being addressed.
Reporting by grantees and federal follow-up
Requires grantees to submit reports at least twice per year with disaggregated participant data (DOE reports include student free/reduced lunch status; both agencies require race/ethnicity/gender breakdowns). Five years after the first grant award, Education and Labor jointly must report to Congress with recommendations on program expansion, using grantee performance data and third-party evaluations.
Amendment to Education Sciences Reform Act
Adds a new reporting item to federal education research priorities: the prevalence of emerging and advanced technology education in elementary and secondary schools and student competency levels. That change embeds AI/tech education metrics into the federal evidence infrastructure, which could influence future research funding and accountability measures.
This bill is one of many.
Codify tracks hundreds of bills on Education across all five countries.
Explore Education in Codify Search →Who Benefits and Who Bears the Cost
Every bill creates winners and losers. Here's who stands to gain and who bears the cost.
Who Benefits
- Community colleges and technical colleges — these institutions are named as eligible recipients and potential regional hubs for scalable skills training, access to grant funds, and partnerships with industry and labor organizations.
- Students in underserved K–12 schools — DOE grants prioritize expanding access to emerging-technology curricula, professional development for teachers, and supports intended to reduce STEAM enrollment and achievement gaps for minorities, girls, and low-income students.
- Incumbent workers in high‑AI-adoption industries — the DOL program targets workers with a high-school diploma (or equivalent) in occupations projected to face the biggest AI impact, giving them access to certifications and pathways to higher-skilled, higher‑wage jobs.
- Labor organizations — the bill explicitly includes labor organizations as eligible applicants and gives them priority under the DOL grants, formalizing a role for worker representation in program design and training delivery.
- Employers and industry — stand to gain a better pipeline of workers with AI-adjacent skills and a structured mechanism to engage with educators and trainers on curriculum relevance and credentialing.
Who Bears the Cost
- Federal agencies (Education, Labor, Commerce) — must resource the interagency study, coordinate stakeholder engagement, administer new competitive grant streams, and implement monitoring and third‑party evaluation obligations.
- School districts and smaller institutions — while eligible for grants, they must plan for sustainability after grant periods end and meet reporting and evaluation requirements; the need to demonstrate sustainability can strain districts with limited capacity or matching funds.
- Taxpayers — programs are authorized at specific FY2026 levels, creating new fiscal commitments that may require ongoing appropriations to sustain beyond initial grants and evaluations.
- Private data holders and industry — the report asks for assessment of privately owned workforce data and options to expand public access; although the bill stops short of compulsory data transfers, private entities may face pressure to share data or enter public-private collaborations.
- Employers in tight-margin sectors — may be asked to engage with curricula, offer internships or hiring commitments, or participate in upskilling partnerships, imposing time and resource costs even where direct financial contributions are not required by the statute.
Key Issues
The Core Tension
The central dilemma is between speed and scale on one hand—rapidly funding training and curricular expansion to meet an accelerating AI transition—and quality, equity, and sustainability on the other: ensuring programs genuinely raise job quality and reach underserved communities without creating short-lived pilots, reinforcing local capacity gaps, or privileging proprietary data and industry-defined credentials over public, portable standards.
The bill packs an ambitious research agenda and two complementary grant programs, but it leaves several implementation gaps that create trade-offs. The interagency report requires mapping privately owned workforce data and recommending ways to expand access, yet the bill does not create clear legal mechanisms to compel data sharing or resolve privacy/proprietary concerns—leaving agencies to negotiate voluntary arrangements or recommend future legislation.
That gap could limit the study’s ability to produce nationally representative, linkable data sets for rigorous labor-market analysis.
Programmatic tensions also arise. The Education grants’ broad definition of 'emerging and advanced technology education' gives local implementers flexibility but raises questions about curricular scope and transferability of credentials.
The Labor grants prioritize workers in industries 'projected' to see AI growth; how those industries are identified and updated will determine who receives funds. Sustainability is another open question: grants run 3–5 years and require sustainability plans, but the bill does not provide follow-on funding pathways or specific expectations for local match, which risks having well-designed pilots fade once federal dollars stop.
Try it yourself.
Ask a question in plain English, or pick a topic below. Results in seconds.