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Wisconsin has spent decades building one of the country’s strongest apprenticeship cultures.
In 2025, the state reached record Registered Apprenticeship participation, with 18,524 apprentices across more than 3,095 employers. Youth Apprenticeship also reached record scale, enrolling 11,344 high school juniors and seniors and partnering with 7,447 employers.
Now Wisconsin needs to apply that same learn-by-doing discipline to the artificial intelligence transition.
Stanford Digital Economy Lab’s August employment update found that employment among U.S. workers ages 22-25 in highly AI-exposed occupations is about 19% below where it would be if it had kept pace with similarly aged workers in less-exposed occupations. The comparable measure was 15% at the July 2025 data vintage. The adjustment is appearing mainly through reduced hiring, especially where AI automates tasks people previously performed.
That matters because entry-level work is not just cheap labor. It is the training ground where people learn how an organization actually operates.
A junior analyst becomes valuable by seeing why a clean spreadsheet can still produce a bad decision. A new claims employee learns which apparently routine case contains the one fact that changes everything. A beginning marketer learns that a polished message can still be wrong for the audience. Those lessons come from repetitions, exceptions and coaching.
If AI performs the first-pass work and the employer simply eliminates the beginner, Wisconsin gets an efficiency gain today and a capability problem later.
The state should encourage an apprenticeship dividend for AI adoption. Employers that save meaningful labor time through AI should reinvest a defined share of those savings into structured learning for newer workers. That can mean mentor hours, supervised exception cases, verification rotations, paid internships or registered apprenticeship slots in occupations that have not traditionally used apprenticeship language.
Wisconsin already has the machinery to support this. Its 2026-2028 Youth Apprenticeship grant program is designed to sustain and expand work-based learning partnerships among schools, employers, colleges, workforce boards and other local organizations. The state is also directing workforce funding toward advanced manufacturing and AI through WisTRAIN, including training for human-AI collaboration.
What is missing is a measurement standard for the human side of the investment.
Employers should track time to independent competence alongside time saved. How long does it take a new worker to verify an AI-generated answer, catch an exception, explain the trade-offs and make a sound decision without close supervision? If that clock slows down even as the productivity dashboard improves, the organization is consuming its own future talent.
Wisconsin’s apprenticeship tradition offers a better path. Use AI to remove repetitive preparation, then move beginners more quickly into the work that requires judgment. Give experienced workers explicit coaching responsibilities. Make the workplace an extension of the classroom, just as the Youth Apprenticeship program already does.
AI productivity should not mean a thinner career ladder. In Wisconsin, it should fund a faster one.
Gleb Tsipursky, Ph.D., is a behavioral scientist, CEO of Disaster Avoidance Experts and author of “The Psychology of AI Adoption at Work: From Resistance to Results.” He lives in Columbus, Ohio.
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Guest opinion: Wisconsin should make an AI productivity fund apprenticeship is a post from Wisconsin Watch, a non-profit investigative news site covering Wisconsin since 2009. Please consider making a contribution to support our journalism.
