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The Industry-Driven Skills Training Fund is DOL's vehicle for pushing federal workforce dollars directly at employer-defined training needs, and artificial intelligence sits at the top of its priority industry list - the solicitation language names occupations essential to the buildout of AI infrastructure and information technology including AI, alongside advanced manufacturing, skilled trades, energy and healthcare.
It is authorized under WIOA Section 169(c) and the American Competitiveness and Workforce Improvement Act, which is why it can move faster and with more employer discretion than formula workforce funding.
The applicant is the State Workforce Agency, not the employer and not the training provider, which is the structural fact most AI training vendors miss: the route in is to be named as a partner in a state's application, not to apply directly. Round one put approximately USD 86,000,000 across 14 states with individual awards between USD 3,000,000 and USD 8,000,000.
DOL announced a second round with substantially the same priority industries in July 2026. The reimbursement model is outcome-based - states are partially reimbursed for actual per-employee training costs after training occurs - so proposals need a credible completion and placement measurement plan, and partners need working capital to front the training.
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Or search similar grants →According to the current listing, eligibility includes: Applications are submitted by State Workforce Agencies. Employers in the priority high-growth sectors participate as partners rather than as direct applicants, and training providers including community colleges and private AI training vendors typically enter through a state's employer partnership rather than by applying themselves. Training may cover both current employees and newly hired workers. Priority industries include artificial intelligence infrastructure, information technology including AI, digital infrastructure and data-related technologies, plus advanced manufacturing, skilled trades, energy and healthcare. The authorizing statutes are WIOA Section 169(c) and the American Competitiveness and Workforce Improvement Act. Round one made approximately USD 86,000,000 in awards to 14 states, ranging from USD 3,000,000 to USD 8,000,000 each. A second round with similar priority industries was announced in July 2026. Funding operates as outcome-based partial reimbursement of actual training costs per employee, which means states and their partners must be able to finance training before reimbursement. Deadlines are set per funding round and are not continuous. Applicants must confirm the current round's Funding Opportunity Announcement on the DOL ETA site and grants.gov for eligibility, allowable costs, reimbursement rates, matching expectations and closing dates before preparing a submission. Confirm the full requirements in the official notice before applying.
The current listing shows the first round of the Industry-Driven Skills Training Fund awarded approximately USD 86,000,000 across 14 states, with individual state awards ranging from USD 3,000,000 (Wyoming) to USD 8,000,000 (Connecticut, Michigan and Idaho). amount_min of 3,000,000 and amount_max of 8,000,000 are the observed floor and ceiling of actual round-one awards, not a published solicitation range. Funding is disbursed as outcome-based partial reimbursement of actual training costs per employee rather than as a conventional cost-reimbursement grant, so cash flow works differently from most ETA awards. Verify award ceilings, matching requirements, and allowable costs in the official notice.
U.S. Department of Labor Industry-Driven Skills Training Fund for Artificial Intelligence Infrastructure and Emerging Technology Workforce Training is funded by U.S. Department of Labor (DOL), Employment and Training Administration (ETA). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
Violence Against Women Discretionary Grants for Indian Tribal Governments is sponsored by Department of Justice. To increase tribal capacity to respond to violent crimes against Indian women, and to develop and strengthen victim services in cases involving violent crimes against Indian women. This listing is currently active. Program number: 16.587. Last updated on 2024-11-26.
The NSF CISE Future Computing Research (Future CoRe) program supports research in computing and communication foundations, intelligent systems, and network systems. The program funds innovative research that advances the frontiers of computing including artificial intelligence, machine learning, computer vision, natural language processing, and robotics. This is one of NSF's largest computing research programs with $280 million in total budget. Projects can address fundamental computing challenges, novel AI architectures, scalable intelligent systems, and next-generation network infrastructure.
DOL's second round of Industry-Driven Skills Training Fund grants closes August 17, 2026: roughly $40 million, about 10 awards, an $8 million ceiling, and an eligibility list restricted to State Workforce Agencies. The real opportunity is downstream, where the money converts into employer reimbursements. Here is how the architecture works, what Round 1 revealed, and how employers, community colleges, and workforce nonprofits should position for the money once it lands.
Read articleThe DOL Industry-Driven Skills Training Fund is distributing $30 million across 14 states for employer-led workforce training in advanced manufacturing, AI, and skilled trades. Employer applications open mid-2026.
Read articleOn July 1, 2026, federal Pell grants became available for short-term, non-degree training for the first time — a generational shift that changes the economics of workforce programs. Here is how Workforce Pell works, how the $65M SCC6 competitive grants fund the infrastructure to capture it, where it sits in DOL's $8B+ workforce ecosystem, and the strategy for colleges and training providers.
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