Reforms to the Workforce Innovation and Opportunity Act Could Help Workers Displaced by AI

“If I lose my job because of AI, what’s next?”

It’s a question that may come to define the United States 2026 midterm elections. The fact there’s no clear answer is a big problem. Americans will understandably oppose continued AI development if it seems like they’re the ones bearing the costs for a brighter future that seems like it’s always a day away.

In response, some politicians and stakeholders are promising to stall or even stop AI. This represents a short-sighted, if understandable, solution. While such policies might preserve some of today's jobs, the relief would be finite—AI progress will likely soon make human labor in those roles economically unviable by comparison. Ultimately, this defensive posture would stifle the very innovation needed to spur new professions and markets, sacrificing long-term opportunity for a short-lived gain. For instance, such efforts may hamper the innovative uses of AI by small businesses that could lead to improved products, novel jobs, and even entirely new markets.

The better response is to provide Americans with a roadmap to economic security and meaningful work. A few simple reforms to the Workforce Innovation and Opportunity Act (WIOA) should be a part of that preferable answer.

The WIOA, enacted in 2014, aims to streamline, coordinate, and improve the nation’s workforce development programs. This is no easy task. A complex state-by-state approach is partially to blame. Each state has a diverse approach to upskilling and retaining workers and is home to a wide range of different programs that may be eligible for WIOA funds. Another source of difficulty comes from the complexity of the task itself: how best to prepare workers for the jobs of the future is more of an art, than a science. Workforce development initiatives have mixed records of success. Finally, there’s also the problem of finding the right mix of reporting requirements to hold programs accountable while also not drowning them in paperwork that diverts time and resources from their core mission. Though the Act brought about improvements on many of these shortcomings, it is in need of a few changes to become fit for its purpose in the age of AI.

Three changes could make the WIOA a far more reliable source of the skills training required to help displaced Americans find their next opportunity. First, the majority of WIOA funds must go toward meaningful skill development, rather than administrative tasks. Even a quick glance at the “reporting requirements” page of the WIOA will make this clear. There are dozens of forms with dozens more data fields and an even longer set of complex instructions and definitions. It’s time to consolidate what information programs must gather and share so that they can focus more resources on the work that truly matters.

Second, workforce programs should be assessed on their long-term track record instead of short-term metrics. Programs are currently evaluated on how participants are doing a year after they complete their training. This creates a problematic incentive for programs to nudge workers into the first job, rather than what may be a better long-term alternative. A preferable approach would align program incentives with the interests of participants and the public generally: securing long-term, meaningful employment for displaced workers.

Third, programs that fall short of clear metrics and otherwise fail to show the capacity to offer innovative and effective training should be promptly made ineligible for federal funds; relatedly, programs that show real promise should receive additional support to expand their operations. By increasing the tie between program performance and federal funds, programs will have a greater incentive to continue to improve their offerings. The net result will be more innovative and effective programs that are tailored to an evolving, skills-based economy.

Some critics—namely, Senator Bernie Sanders—may point to other solutions, like a "robot tax," to fund a social safety net by penalizing companies that automate. But this approach treats innovation as a problem to be managed rather than an opportunity to be seized. Punishing companies for adopting new, productivity-enhancing tools is ultimately counterproductive. It creates a powerful disincentive to innovate, effectively slowing the economic engine we need to create new wealth and new opportunities in the first place. The goal must be to invest in human capability, not to tax technological progress.

The anxiety Americans feel about AI is real and demands a substantive answer to the question of "what's next." Instead of trying to stall or tax our way out of the future, we must make a credible, nationwide commitment to investing in our own workforce's capacity to adapt. This is the only way to build a future where technological progress and human prosperity advance together.