National Workforce Transition Fund Act of 2026
- Sponsor
- Sen. Warner, Mark R. [D-VA]
- Committees
- Finance Committee (primary)
- Last action
- Jul 21, 2026
Bottom line
The bill creates a new federal framework and dedicated funding stream to help American workers and employers adapt to the economic shifts driven by artificial intelligence and emerging technologies.
What it actually does
This bill establishes a National Workforce Transition Board and a National Workforce Transition Fund to address labor market disruptions caused by artificial intelligence and emerging technology. It amends the Workforce Innovation and Opportunity Act to create new programs for worker training, education, and employer grants, funded by revenue generated from changes to the Internal Revenue Code that exempt AI data centers from bonus depreciation and apply specific depreciation rules to leased AI data centers. The bill also mandates modernization of labor market information systems.
Proponents argue
Supporters argue that this bill is a proactive and necessary step to prepare the American workforce for the future, ensuring that workers are not left behind by rapid technological advancements. They contend that the dedicated funding mechanism, tied to AI infrastructure, provides a sustainable and targeted approach to support training, education, and responsible employer transitions, while also improving critical labor market data.
Opponents contend
Critics may argue that the tax changes on AI data centers could disincentivize investment in critical AI infrastructure within the United States, potentially hindering technological advancement and competitiveness. Concerns might also be raised about the administrative complexity of the new board and fund, or whether the programs will effectively reach the most impacted workers and lead to measurable, stable employment outcomes.
The bill is moderately complex, requiring careful reading due to its amendments to existing law and the introduction of new tax provisions. An informed reader would need adequate time to fully grasp its implications.
Sec. 2, Title III, Sec. 303
Establishment of National Workforce Transition Board
This provision establishes a National Workforce Transition Board within the Department of Labor, headed by the Secretaries of Labor, Education, and Commerce. The Board will include representatives from business, labor, and government/education. Its primary function is to develop an annual national strategy, including a workforce impact assessment, forecasts of skill requirements, and recommendations for federal workforce development plans and grantmaking priorities related to AI and emerging technology.
Supporters argue
Supporters argue that a dedicated, tripartite board is essential to provide expert guidance and a coordinated national strategy for addressing the complex and evolving challenges of AI-driven workforce transitions, ensuring diverse perspectives are considered.
Critics contend
Critics might suggest that adding another federal board could lead to bureaucratic inefficiencies or that its recommendations might not be sufficiently responsive to rapid technological changes, potentially duplicating efforts of existing agencies.
Tradeoffs
The provision balances the need for expert, multi-stakeholder input with the potential for administrative overhead and the challenge of maintaining agility in a fast-changing technological landscape.
Sec. 2, Title III, Sec. 304
Establishment of National Workforce Transition Fund
This section establishes the National Workforce Transition Fund within the U.S. Treasury. The Secretary of the Treasury is designated as the trustee, responsible for investing portions of the Fund not immediately needed. The Fund will receive annual transfers from the general fund of the Treasury, equal to the increase in revenue generated by the bill's tax amendments related to AI data centers. Amounts in the Fund are to be used exclusively for activities outlined in the bill, subject to appropriation acts.
Sec. 2, Title III, Sec. 305(a)
Permissible Activities and Priority Populations for Fund Use
This section outlines the permissible uses of the National Workforce Transition Fund, including modernizing labor market information systems, assisting workers in transitioning to stable employment, supporting employers in worker retention/redeployment, and funding pilot programs. It mandates that priority for these activities be given to workers experiencing or facing employment loss or labor market disruption, particularly those receiving unemployment compensation, dislocated workers, or those in occupations exposed to technological change.
Sec. 2, Title III, Sec. 305(b)
Workforce Data and Labor Market Information Systems Modernization
This provision authorizes the Secretary of Labor to use Fund amounts to strengthen federal and state labor market information (LMI) systems. This includes identifying where AI-driven disruption occurs, which workers are affected, and the effectiveness of public interventions. It allocates $3 million for a study to identify data gaps, recommend improvements (e.g., integrating AI questions into surveys, linking cross-agency data), and assess state efforts to modernize unemployment insurance wage data systems. Following the study, funds will be allocated for modernization activities like measuring occupational AI exposure and tracking worker outcomes.
Sec. 2, Title III, Sec. 305(c)
Worker Transition Assistance and Other Services
This section authorizes the use of Fund amounts for projects and services to help workers transition into stable employment. This includes grants to local areas for individual training accounts (ITAs), grants to states for education and training leading to credentials in in-demand sectors (with a worker cost-share), and sectoral workforce partnership grants to create or expand partnerships that assist workers with career pathways. It also allows for the provision of supportive services like housing, child care, and transportation.
Sec. 2, Title III, Sec. 305(d)
Employer Retention, Redeployment, or Transitioning Grants
This provision allows the Secretary to use Fund amounts for grants to states and local boards, who then make subgrants to employers. These subgrants support employers in retaining, redeploying, or responsibly transitioning workers whose jobs are materially affected by AI or emerging technology. To receive a subgrant, employers must submit a workforce transition plan and enter into a 'workforce transition compact' with the Secretary, which includes targets for retention/redeployment, worker consultation procedures, wage/benefit standards for redeployed workers, reporting requirements, and procedures for recovering misused funds.
Sec. 3(a)
Exempting AI Data Centers from Bonus Depreciation
This provision amends Section 168(k) of the Internal Revenue Code of 1986 to exclude 'any property used in an AI data center' from eligibility for bonus depreciation. An 'AI data center' is defined as a structure or group of structures dedicated to IT and network telecommunications equipment (including at least one graphics processing unit) for data storage, processing, and transport services, where at least 20% of its use is for developing or operating artificial intelligence.
Sec. 3(c)
Transfer to National Workforce Transition Fund
This provision mandates that the Secretary of the Treasury annually transfer an amount equal to the increase in revenue resulting from the AI data center tax amendments (subsections (a) and (b) of Section 3) to the National Workforce Transition Fund. This transfer mechanism is set to terminate five years after the date of enactment of the Act.
Sec. 4
Termination of Authorities
This section establishes a sunset clause for the key provisions of the Act. The authority for the AI data center bonus depreciation exemption (Section 3) and the workforce development activities (Section 2 and its amendments to WIOA) will terminate five years after the date of enactment. This includes the National Workforce Transition Board and Fund.
The definition of an 'AI data center' for tax purposes includes specific technical criteria, such as containing 'not less than 1 graphics processing unit' and having 'at least 20 percent of which is used for developing or operating artificial intelligence'.
Sec. 3(a)(2)(A)
Why it matters:This is standard legislative practice for tax code amendments, where specific definitions are often nested within the relevant sections of the Internal Revenue Code. However, the technical nature of the definition is crucial for determining which entities are subject to the tax changes.
Case for: Supporters would argue that precise technical definitions are necessary to ensure the tax provision is accurately applied to its intended targets, preventing unintended consequences or loopholes for entities not primarily engaged in AI development or operation.
Case against: Critics might argue that such highly technical definitions could be challenging for the IRS to administer and enforce, potentially leading to disputes over classification. The '20 percent' threshold could also be seen as arbitrary or difficult to measure in practice.
Estimated impact: This definition directly determines the scope of the tax revenue generated for the National Workforce Transition Fund, impacting potentially billions of dollars in investment in AI infrastructure.
Workers are explicitly not required to prove that artificial intelligence or emerging technology was the sole or primary cause for their labor market disruption to receive support. Instead, eligibility for priority populations is determined using labor market indicators such as unemployment insurance claims, wage records, and occupational employment trends.
Sec. 2, Title III, Sec. 305(a)(2)(B)
Why it matters:This is a substantively important detail for program accessibility, designed to simplify the application process for workers. Its placement is logical within the eligibility criteria, but its significance for reducing individual burden could be missed.
Case for: Proponents would argue that this provision is vital for making the programs accessible and effective, as proving a direct causal link to AI for individual job loss is often impossible. Relying on broader labor market indicators makes the system more administrable and worker-friendly.
Case against: Critics might argue that without a direct causal link, the programs risk supporting workers whose displacement is not primarily AI-related, potentially diluting the fund's intended purpose and reducing its efficiency in addressing specific AI impacts.
Estimated impact: This provision significantly broadens the pool of potentially eligible workers, impacting the reach and cost of all worker-facing programs funded by the Act.
For education and training grants provided to students or incumbent workers for credentials in in-demand sectors, the bill requires participants to pay one-third of the program cost upon enrollment and an additional one-third if they do not complete the program.
Sec. 2, Title III, Sec. 305(c)(3)(E)
Why it matters:This is a critical detail for the financial accessibility of the program and is a common feature in grant programs to ensure participant commitment. Its placement is logical within the specific grant program's rules.
Case for: Proponents would argue that this cost-sharing mechanism encourages participant commitment and ensures that public funds are invested in individuals who are serious about completing their training, thereby maximizing the return on investment for taxpayer dollars.
Case against: Critics might contend that requiring an upfront payment and an additional penalty for non-completion could create a significant financial barrier for low-income workers, who are often among the most vulnerable to AI-driven displacement, potentially undermining the bill's goal of supporting these populations.
Estimated impact: This provision could significantly impact the participation rates of lower-income individuals in the education and training grant programs, potentially shifting the demographic of beneficiaries.