Raimondo: AI Will Create Jobs, but Warns of First Layoff Wave

What Raimondo Said

Former U.S. Commerce Secretary Gina Raimondo said she expects artificial intelligence to create jobs over the long run, but she is more concerned about the layoffs that could arrive first, according to a CNBC report published September 29, 2026.

The report frames her view as a timing problem rather than a verdict on whether AI is good or bad for employment. No one knows what AI will mean for jobs long-term, the report notes, but without proper planning the layoffs are likely to hit before any of the new roles materialize.

That distinction matters for American workers and households because it separates two very different questions. The first is whether AI eventually expands the economy enough to generate new kinds of work. The second is what happens to the people whose current jobs are displaced during the transition, before those new roles exist or before workers have the skills to fill them.

Raimondo, who led the Commerce Department during the Biden administration, is not presented in the report as predicting a specific number of job losses or naming particular industries. Her warning is about sequencing: the disruption may come first, and the replacement jobs may come later.

Why the Timing Problem Is the Hard Part

Economists have long observed that technological change tends to destroy some jobs while creating others, but the two processes rarely move at the same speed. A factory that installs automation may need fewer workers on the line within months, while the new roles that automation supports, such as technicians, data analysts or logistics coordinators, may take years to appear and may require different skills or different locations.

That gap is what makes the transition painful even when the long-run outcome is positive. A worker who loses a job in the first wave cannot wait several years for the second wave to arrive. Mortgage payments, rent, health insurance and child care are monthly obligations, not long-run averages.

For American readers, the practical effect is that the near-term risk is concentrated in specific occupations and regions rather than spread evenly across the economy. Roles built around routine cognitive tasks, such as certain back-office functions, basic customer support and some entry-level analytical work, are frequently cited in public debate as being exposed to automation. The CNBC report does not specify which jobs Raimondo has in mind, and she is not quoted making a sector-by-sector forecast.

What the report does convey is that planning matters. If employers, policymakers and training programs prepare in advance, the transition can be smoother. If they do not, the layoffs arrive as a shock to workers who have no bridge to the next job.

What This Means for Workers and Households

The most immediate implication is about personal financial resilience. When layoffs cluster in a short period, affected workers face a tighter job market at exactly the moment they need to find new work. Emergency savings, severance terms, unemployment insurance eligibility and the portability of health coverage all become more important than they are in a steady labor market.

For households, that argues for understanding what benefits are actually available before they are needed. Unemployment insurance is administered by states, and eligibility rules, weekly benefit amounts and duration vary widely. Severance is a matter of company policy or negotiation, not a legal guarantee in most cases. Health coverage after a job loss typically depends on whether the worker can continue an employer plan through COBRA, qualify for a marketplace plan or join a spouse's plan.

None of these mechanisms are new, but a faster wave of displacement would test them at scale. State unemployment systems were strained during the pandemic-era layoffs, and a sudden surge in claims would put similar pressure on processing times and call centers.

There is also a skills dimension. If the new jobs AI creates require different training than the old ones, then the speed of retraining programs, community college enrollment and employer-funded upskilling becomes a bottleneck. A worker who needs a two-year credential to move into a growing field faces a much longer gap than one who needs a few weeks of software training.

The Policy Questions in the Background

The report places Raimondo's comments in the context of an unresolved national debate. Lawmakers, regulators and employers have not settled on a common approach to AI-driven workforce change. Proposals that surface in public discussion include expanded retraining funding, tax treatment of automation, disclosure requirements for large layoffs and changes to unemployment insurance formulas. The CNBC report does not attribute any specific proposal to Raimondo, and it does not describe legislation moving through Congress.

What it does capture is a former senior official arguing that the long-run case for AI and the short-run case for worker protection are not in conflict. Both can be true at once: the technology may expand employment over time, and the first wave of displacement may still be severe.

That framing is notable because much of the public conversation about AI and jobs tends to split into two camps. One camp emphasizes eventual job creation and treats displacement as a manageable side effect. The other emphasizes job destruction and treats the long-run gains as speculative. Raimondo's position, as reported, sits between them: she accepts the long-run case but treats the transition as the part that requires deliberate preparation.

What to Watch

For American readers tracking this issue, several observable signals matter more than any single forecast. The pace of announced layoffs at large employers, particularly when companies cite automation or efficiency rather than weak demand, is one. The volume of new job postings that explicitly require AI-related skills is another, because it indicates whether the replacement roles are actually appearing.

State unemployment claim data and the duration of unemployment spells show whether displaced workers are finding new positions quickly or getting stuck. Enrollment trends in short-term training programs and community college certificate courses indicate whether workers are preparing for the transition or waiting it out.

None of these indicators resolves the long-run question. They do show whether the sequencing problem Raimondo describes is playing out as she fears, with layoffs arriving before the new jobs do.

The report does not include a forecast from Raimondo about the size or timing of any layoff wave, and it does not state that any particular company has announced cuts. Her point, as reported, is about preparation: the long-term outcome may be favorable, but the near-term path depends on decisions made before the disruption arrives.

Source: CNBC Top News

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