Key Takeaways

  • RAISE US is rolling out new wage insurance, retraining, and transition models with backing from OpenAI, Anthropic, Amazon and Microsoft
  • Market indicators show rapid shifts in hiring patterns, particularly for early-career and creative roles
  • Analysts point to a rising need for large-scale reskilling as AI adoption accelerates across sectors

Workers in the United States are staring down a labor market that feels different from even a few years ago. AI adoption is rising inside enterprises, and the shift is beginning to show up in hiring patterns, layoffs, and state policy debates. Into this moment steps RAISE US, a nonprofit founded by Gina Raimondo and Eric Holcomb, with substantial backing from OpenAI, Anthropic, Amazon and Microsoft. The group's mission is straightforward on paper, though challenging in practice: design and test programs that help workers whose jobs are being reshaped or displaced by AI.

Part of what spurred the organization's formation is the gap between technological ambition and human transition. Raimondo put it plainly, noting that the country has a technology strategy for AI leadership but lacks a real people strategy. Her argument resonates because the numbers behind workforce disruption are stacking up. Analysts have been tracking this for several years, and the trendlines suggest extensive workforce reconfiguration ahead. For example, Gartner expects that by 2028, 75% of enterprises will move from pilot experiments to operationalizing AI. That shift tends to alter roles, workflows, and talent pipelines.

Amazon and Microsoft both emphasized their history of supporting workforce programs, even as they cited AI transformation when explaining recent headcount reductions. Amazon cut 14,000 jobs last fall. Microsoft eliminated around 9,000 roles last July and has been offering buyouts to others. Corporate responses reveal a short-term tension, as organizations invest in technology that enables automation while also funding a nonprofit meant to help those affected by that same automation.

Independent research has highlighted the scale of potential displacement. McKinsey estimates that generative AI could automate 60% to 70% of activity in some occupations by 2030, affecting up to 30% of work hours across the U.S. economy. The World Economic Forum has suggested that 44% of workers' skills will be disrupted by technology within the next five years, and half the workforce may need reskilling or upskilling by 2027. These figures are directional, but they illustrate why both public and private leaders are pushing transition strategies.

RAISE US is testing several options that policy researchers have debated for years. Wage insurance is one example. It aims to buffer the income drop that often occurs when a worker must take a lower-paying job during a transition. Short-time compensation is another. Instead of laying off employees, companies reduce hours and use partial wage support to maintain stability while retraining occurs. States like Arkansas, Maryland, Utah and Connecticut have signed on as early pilot partners. The group has already secured more than $500 million in commitments with a target of reaching $1 billion.

Signals from the job market provide a mixed picture. According to employment data from SignalFire, tech hiring overall is down 25% compared to pre-pandemic 2019 levels on a trailing twelve-month basis. Yet engineering roles have held up better, dropping only 11% at major tech firms and rising 7% at startups. Designers and marketers have faced sharper contractions, with hiring down 48% and 36% respectively at large companies. These figures highlight a disparity in which roles see stability as AI systems advance, and which require rapid reinvention.

One worrying trend sits with new graduates. Only about 8% of new hires at major tech companies today have one year or less of experience, down from 22% in 2016. At startups, that share has fallen from roughly 15% a decade ago to 3% today. Investors warn that cutting early-career pipelines to shore up balance sheets could create a leadership gap over the next decade. It is a reminder that workforce transitions are not only about displaced workers but also about future talent development.

Industry standards and public frameworks are starting to shape how organizations approach the risks and responsibilities of AI deployment. Tools like the NIST AI Risk Management Framework and the OECD AI Principles encourage companies to consider human impact, equity, and accountability. These guidelines are not mandates, but they influence corporate strategy, procurement decisions, and regulatory thinking. As enterprises scale AI systems, alignment with these frameworks becomes more visible, partly because stakeholders are asking pointed questions about fairness and safety.

AI deployment fundamentally shifts the economics of entire business functions. It alters job design and necessitates changes to education and training systems. RAISE US aims to build a bridge across this transition.

For large enterprises, this initiative offers a testing ground for models that eventually become part of mainstream workforce strategy. For states, it provides a structured way to try programs that have existed in theory but rarely at scale. For workers, the outcome will depend on execution. Wage insurance and guided retraining can help, yet adoption depends on political support and employer participation. With the federal minimum wage still at its lowest real value in 77 years, according to the announcement, some workers may view these programs with skepticism.

The nonprofit's formation signals that industry leaders recognize the broader implications of their technology. The challenge now is turning recognition into sustained action while the labor market recalibrates. Whether RAISE US becomes a blueprint for national policy or an isolated experiment will depend on how quickly the pilots demonstrate results and whether companies continue to back workforce transition efforts even as automation accelerates.