When the Bulova watch factory in Providence, R.I., closed in the 1980s, my father faced an abrupt end to his 30-year career. Like many American manufacturers, Bulova moved its production overseas, chasing the cheaper labor that new free-trade agreements made so irresistible. At 56, my father was a casualty of a new economic rulebook stapled to an old work force model. There were no effective public or private initiatives to help him or millions of other Americans transition to new jobs in the new economy, leaving many American cities hollowed out and helping produce the politics of division that plague us today.
This story isn’t just my memoir; it’s history we’re about to repeat. Artificial intelligence is transforming work faster than our work force is adapting. Millions of Americans — from white to blue collar, entry level to executive — may soon find themselves jobless and without prospects. Leaders across the political spectrum and the private sector tell me this crisis is coming and there’s no obvious solution.
I refuse to accept that an unemployment crisis is inevitable. The answer, however, isn’t to slow down A.I. innovation and leave ourselves less competitive and less prepared. Nor is generic “re-skilling” that pushes people into completely new roles and industries. Instead, we should build a modern transition system with better data to predict job losses and new forms of support to help workers transition between jobs.
What we need is a new grand bargain between the public and private sectors — one in which employers are held responsible for defining skills essential to the A.I. economy and for creating pathways into jobs, and the government invests in the training, incentives and safety nets that help workers move quickly into them. The private sector has always been better positioned to see which new jobs are emerging, which skills matter and how quickly demand will shift. So this new bargain should start with businesses taking the lead and providing real-time, A.I.-powered insights into hiring plans, technology adoption and skill needs.
This can start with tearing down the wall between the business and education communities. I saw this firsthand as secretary of commerce when implementing the CHIPS Act, which put billions of dollars toward semiconductor development and production. Working intensively with TSMC, the Taiwanese chipmaker, my team learned new chip plants were stymied by talent gaps in tool maintenance, electrical engineering and pipe fitting. TSMC used these findings to lobby states, employers and schools like Maricopa Community College to build accelerated certificate programs to train people to fill these specific talent gaps.
The future of higher education should be modular, and employers must be active partners in shaping what gets taught. The country needs to shift focus from long and expensive degrees that risk obsolescence before completion toward short, affordable job-linked credits that offer on-ramps between education and work. People should be encouraged to pursue credentials that can stand alone or be stacked over time into degrees, bringing people back to campus over the arc of their lives. A midcareer accountant displaced by A.I. doesn’t need another master’s degree. Instead, she may be better off with a four-month credential and temporary wage insurance that bridges any pay gap and incentivizes her to accept a new role sooner.
The funding model for higher education must change, too. Public investment should hold schools to measurable labor market results, not just enrollments. Texas offers a working example: Community colleges that award credentials in high-demand fields receive greater state funding. If we take this approach, we’ll quickly see a survival of the fittest emerge: Innovative programs that meet labor market needs will be rewarded, while underperformers will shutter.
When it comes to employer-led training, the country needs a modern apprenticeship system that allows workers to earn while they learn, which many European countries have embraced. Workers in fields persistently plagued by talent shortages or undergoing rapid technological change need this. A manufacturing apprentice, for example, could earn a paycheck operating equipment in a factory while learning blueprint reading from a senior technician and taking classes.
But to make all this happen at scale, the private sector must be incentivized to do it. That may mean employer tax credits tied to on-the-job training. States could pilot tax code reforms that reward worker retention and entry-level hiring, penalize layoffs and encourage companies to reinvest A.I.-driven savings into the creation of jobs. This isn’t corporate charity; it’s strategic necessity.
Skeptics will argue that we’ve tried work force reform before and it hasn’t worked. That the landscape for work force development is littered with underperforming, small-scale training initiatives. They aren’t wrong. But history shows that real change comes in times of crisis. After World War II, the G.I. Bill and land grant universities sent millions of veterans to school while public research funding seeded advancements in manufacturing, aerospace, semiconductors and computing. Decades later, the financial crisis and Covid sparked new growth industries with millions of new jobs in clean energy, fintech and health care.
A.I.-driven mass unemployment is a potential crisis on the horizon. This country cannot withstand the kind of economic shock I see coming. Without solutions, America’s anxiety will become rage — and political backlash will follow, targeting companies that make A.I., businesses that deploy it and politicians who back it. A new grand bargain between the public and private sectors can help us meet this moment. I know we have the ingenuity to do it. What’s missing now is the collective will.
Gina Raimondo was the secretary of commerce under the Biden administration and the 75th governor of Rhode Island.
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