The Next Era of Apprenticeship

Merry Ramirez grew up in Silicon Valley, surrounded by some of the world’s most innovative companies. But finding her own place in that economy was another matter. 

When her family had to return to Mexico, she finished high school and studied engineering for a few semesters in college. But when she returned to California, work and supporting her family took precedence. She worked in a cafeteria at Meta and later as a barista at a medical technology company. She had ambition, technical interests, and some college education. What she lacked was a pathway into the industry around her. 

That changed when she learned about Foothill College’s semiconductor apprenticeship. The program combined college coursework with paid, hands-on training at a semiconductor company. Ramirez completed the apprenticeship and secured a permanent position at Infinera, a telecommunications technology manufacturer. 

Her story illustrates a challenge facing millions of Americans: how do people gain the experience employers demand when they cannot get the jobs that provide it? 

Artificial intelligence is making that question increasingly urgent, but a potential solution lies with one of our oldest training systems: Registered Apprenticeship.  

The Experience Paradox in an AI Economy 

AI is changing the relationship between education, experience, and employment. 

For generations, entry-level jobs provided the first rung of a career ladder. New employees learned by observing experienced colleagues, completing routine assignments, making mistakes, and gradually assuming greater responsibility. 

Today, AI can perform a growing share of those routine tasks. The technology promises enormous productivity gains, but it also raises a difficult question: If machines perform more of the work through which people traditionally develop expertise, where will the next generation acquire that expertise? 

Research from Stanford’s Digital Economy Lab offers an early warning. Its August 2026 analysis found that employment among workers ages 22 to 25 in highly AI-exposed occupations was 19% below where it would have been had it kept pace with less-exposed occupations. The researchers found no evidence of widespread economy-wide displacement, but the relative decline among younger workers was striking. 

Meanwhile, other industries face a different challenge. According to JFF’s State of America’s Skilled Trades, employers will need to fill approximately 1.7 million skilled-trades openings annually, driven by growth and the retirement of experienced workers. 

These pressures point to the same underlying need: America must become much better at connecting learning with real work. 

That is why apprenticeship deserves renewed attention. 

When Work Counts Toward a Degree 

For too long, America has maintained a divide between academic learning and learning through work. 

A student completing a college course receives academic credit. An apprentice may spend thousands of hours mastering complex technical skills, often through rigorous instruction and supervised practice, yet find that this learning does not translate into progress toward a college degree. 

That separation makes little sense for workers, employers, or the economy. 

Imagine a different system. 

A young person enters a pre-apprenticeship program, develops foundational skills, and moves into paid employment as a registered apprentice. The related classroom instruction carries college credit. Competencies demonstrated through supervised work are evaluated for additional credit through Credit for Prior Learning. Those credits accumulate toward a certificate, associate degree, or, where available, an applied bachelor’s degree. 

The apprentice earns wages, gains experience, develops professional relationships, and advances toward a college credential simultaneously. 

And the pathway remains open. Years later, that worker can return to college, build on existing credits, and prepare for the next stage of a career. 

This is the promise of apprenticeship-to-degree. 

JFF’s research on youth apprenticeship in Chicago underscores the importance of connecting work-based learning to transferable postsecondary credit. When apprenticeships are integrated with educational pathways, they can create opportunities for continued advancement rather than ending with a single occupational qualification. 

Achieving this at scale requires colleges and apprenticeship sponsors to align competencies with curricula, develop consistent credit-awarding practices, and create pathways that students can navigate across institutions. 

It also requires a shift in how we think about higher education. 

College should recognize learning wherever it occurs, while maintaining rigorous standards for demonstrating what students know and can do. 

AI Can Help Build the System and Transform the Learning 

Artificial intelligence introduces another opportunity. 

We should think about AI in two ways: as a tool for building apprenticeship infrastructure and as a technology apprentices must learn to use responsibly. 

First, AI could help colleges and apprenticeship sponsors map occupational competencies to existing courses, identify where workplace learning meets academic standards, and streamline the documentation required for Credit for Prior Learning. 

Work that currently requires extensive manual review could become more efficient, allowing faculty and subject-matter experts to focus on validating learning and maintaining academic quality. 

Imagine an apprentice completing a registered program in advanced manufacturing. A digital record captures the competencies demonstrated through supervised work. AI-assisted tools help identify how those competencies align with college coursework. Faculty review the evidence and determine appropriate credit. The apprentice can then see a clear pathway toward the next credential. 

Second, AI should become part of the apprenticeship learning experience itself. 

A health care apprentice might learn to use AI-supported documentation tools while developing clinical judgment and patient communication. A manufacturing apprentice might work with AI-enabled quality-control systems. An information technology apprentice might learn to design, evaluate, and supervise AI agents. 

In each case, the apprentice learns to work with emerging technology in the environment where it will actually be used. 

This matters because employers will increasingly need workers who can combine technological fluency with experience, sound judgment, and responsibility. 

AI can help accelerate the recognition of learning. Apprenticeship can help ensure that learning remains grounded in human experience. 

The Next Chapter of American Higher Education 

Merry Ramirez’s apprenticeship opened a door into semiconductor manufacturing. But her ambitions extend further. She hopes to continue her education and eventually move into an engineering role. 

That aspiration captures the opportunity before us. 

An apprenticeship should provide a strong beginning without becoming an educational endpoint. 

For the worker, it should mean wages today and opportunities tomorrow. For employers, it should mean access to talent prepared for the realities of modern work. For colleges, it should mean bringing academic learning and workplace experience into a coherent educational pathway. 

And for the nation, it offers a way to rebuild the connection between education and economic mobility at a moment when AI is reshaping both. 

We have spent decades debating whether young people should pursue college or a career. 

It is time to move beyond that false choice. 

The future of higher education is about making it possible to pursue both, together, throughout a lifetime. 

That is the promise of apprenticeship. And that is the infrastructure we must now build.