AI and the Workforce

AI is already reshaping our economy. In 2025 alone, AI attracted hundreds of billions in private investment in the U.S.—far more than in any other country¹—and American firms are leading in key measures of innovation² and productivity.³

AI’s impact on business and society will be significant and multifaceted—unlocking extraordinary opportunity while introducing risks at a pace and scale that could overwhelm existing policy responses. As companies move quickly to adopt and deploy these technologies, several areas require more intentional action from both business and government:

• National security and geopolitical competition, including from China
• Economic transformation and workforce disruption
• Information integrity and increased mis/disinformation
• Government capacity and policy effectiveness

This paper focuses on workforce impacts, recognizing that a broader set of policy and industry responses will be essential to address the full range of challenges AI presents. The scale of disruption is significant: recent research suggests 43% of U.S. jobs⁴ could be transformed or redesigned, with up to 30% of all work⁵ potentially automated fully. 40% of workers⁶ fear losing their jobs to AI—and some companies have cited new AI capabilities in announcing large-scale layoffs.⁷

We are likely entering a period of faster job turnover, shifting skill requirements, and wider wage disparities. While economy-wide change may unfold over years, firms can adopt AI quickly and cheaply, creating abrupt disruptions within specific industries and occupations. Labor markets have historically adapted to technological change over time—but not without dislocation.

Policymakers have yet to mount a coordinated response. Few have articulated a workforce strategy fit for a rapidly evolving economy, and fewer still have sought to address AI’s broader effects on our security, information ecosystem, and societal health. Today’s workforce system consists of fragmented programs largely designed for cyclical downturns, not sustained structural change. Workers face barriers to acquiring new skills, navigating career transitions, and maintaining access to benefits. Employers often underinvest in training, especially when returns are uncertain.

As AI reshapes skill demand, the economy’s ability to translate productivity gains into broadly shared wage growth will depend on how quickly workers can move into new roles. Without a more adaptive workforce strategy, the U.S. risks slower growth, wider inequality, and a loss of public confidence in both markets and technology.

Leadership Now supports a forward-looking workforce strategy that accounts for the rapid development and deployment of AI over the coming decade. We are guided by three principles:

AI holds the potential to make our economy more competitive and productive: creating better jobs, expanding economic mobility, lowering costs in health care and education, and improving government services. Realizing those gains requires policy frameworks that are ambitious, adaptive, and achievable.

Leadership Now supports bipartisan reforms that modernize benefits and tax incentives, invest in training and workforce transitions, and position government as an effective deployer of AI. These are a starting point—as the technology evolves, more must be done to mount a nimble, timely, and effective response.

I. Modernize Benefits, the Safety Net, and Tax Incentives

• Create portable benefits and update the safety net. Establish a framework enabling workers to maintain health insurance, retirement savings, and other essential benefits across jobs, employers, and sectors. Update unemployment insurance eligibility and benefit duration to reflect the realities of career transitions, retraining, and non-traditional employment.
• Explore tax reforms that support labor. Our tax system currently favors investments in capital over labor. Policymakers should explore reforms that support hiring and employment while still encouraging productive investment—including incentives for companies to reinvest AI-driven productivity gains into workforce development and job creation.
• Encourage broad-based ownership. Explore tax incentives and regulatory frameworks that encourage companies to establish or expand employee stock ownership plans (ESOPs), profit-sharing, and other mechanisms that give workers a direct stake in gains from innovation.

II. Invest in Successful Workforce Transitions

• Expand outcomes-based workforce training. Too many workforce training programs have failed to deliver. We need rigorous evidence on which investments lift wages and place workers in lasting careers—and then we must accelerate pathways to high-ROI technical certifications and credential-bearing programs aligned to real employer demand.
• Incentivize company-provided training. Support tax credits for companies that invest in training and reskilling, accessible to businesses of all sizes. Expand apprenticeship and “earn while you learn” programs, and explore replicating co-op programs for entry-level workers.
• Modernize community colleges and credential programs. Overhaul accreditation standards to focus on career outcomes. Create short-cycle, stackable credentials that ladder into degrees, with stronger employer co-design requirements and funding tied to completion and wage outcomes. Consider tax-advantaged lifelong learning accounts that workers can fund over time and draw on throughout their careers.
• Expand national service as a career onramp. With entry-level job postings⁸ declining and AI disproportionately affecting junior⁹ workers, policymakers should explore expanding national service programs in high-need fields like health care, energy, and education—aligned with modernized credentialing and public-private partnerships.

III. Improve Government Delivery

• Deploy AI to improve government services. Use AI to reduce costs and expand access to critical services, including health care enrollment, tax filing, benefits navigation, and permitting. Government can model transparency in AI deployment by publicly documenting how AI is used, what safeguards are in place, and how affected workers are supported.
• Partner with industry to collect workforce data. Federal and state governments should work with employers to collect and publish real-time data on AI adoption, emerging skill needs, and workforce impact—giving both the public and private sectors the clarity needed to assess what’s working.

We must pair support for innovation with workforce programs that create better jobs, improve training and transitions, and empower workers to share in AI’s gains. Together, these policies can ensure the U.S. remains the world’s strongest economy—and that American workers are among its greatest beneficiaries.

The following bipartisan efforts align with our position that the U.S. must advance AI innovation while modernizing the safety net, enabling workforce transitions, and improving government delivery: