Job training needs new financing, not new debt |
Job training needs new financing, not new debt
Artificial intelligence is accelerating a labor-market challenge that America has never solved well: how to help workers move into better jobs without asking them to shoulder all the risk of getting there.
Policymakers and employers all say that skills matter. But too often, the burden of acquiring those skills falls on workers least able to bear it. A worker seeking a better-paying job in health care, advanced manufacturing, information technology, or the skilled trades may find a strong training program. But the program costs money and requires time away from work. The worker may need childcare, transportation, coaching, or income support to complete the course. And there is no guarantee that it will lead to a job that justifies the cost.
Employers face a similar challenge. Businesses need well-trained workers now, but many hesitate to pay to train people who may not succeed in the program or leave before the investment pays off.
That is America’s workforce financing problem: workers need training, but too often they must upskill or reskill with money they do not have, time they cannot spare, and debt they cannot afford.
Public investment in workforce development remains inadequate, well below what other industrialized nations provide. Even with the new Workforce Pell program’s expansion of eligibility for grants at certain short-term programs, major gaps remain, especially for nondegree or noncredit programs and for costs beyond tuition.
As we explore in a new Social Finance Institute paper, outcomes-based repayment models can help address that gap. But only if they are used carefully.
In these arrangements, instead of workers or businesses shouldering the full cost of training upfront, a third-party funder pays first. Repayment happens later, and only if the training delivers agreed-upon results, such as higher earnings or improved employee retention. Funders can include government, philanthropy, or........