AI in a skills-first labor market

How AI can advance a skills-first labor market

With the right approach, it can help tear the paper ceiling

Artificial intelligence (AI) is transforming how people work, learn, and connect with opportunity.

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AI can be a powerful force for economic mobility—but only if it’s designed and used with intention.

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Without care, AI could reinforce the very barriers that keep millions of workers Skilled Through Alternative Routes (STARs) from higher-wage jobs.

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Technology may help solve the problem – but it was also part of the cause.

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AI is "amplified intention"

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AI is only as fair as the assumptions and data behind it – and it will amplify historically unfair practices unless we intentionally design them not to do so. If hiring algorithms are built to favor degrees, they will “screen out” STARs by default. But if they are built to recognize and match skills, AI can “screen in” millions of qualified candidates who have been overlooked.

A skills-first approach to AI can:

Parse skills from experience

by analyzing resumes, work histories, and portfolios for demonstrated capabilities — regardless of formal credentials.

Match candidates to roles by skills equivalency

rather than exact job titles or degree requirements.

Reduce bias in early screening

by focusing on skills signals instead of subjective educational proxies.

Identify pathways for growth

by mapping adjacent skills and emerging opportunities so workers can navigate the labor market more effectively.

When designed for inclusion, AI doesn’t just make hiring faster — it makes hiring fairer.

AI plays a role on both sides of the labor market

For STARs supplying talent, AI can expand visibility into opportunities, highlight transferable skills, and recommend tailored pathways to higher-wage work. It can also serve as a “co-pilot” to help workers learn faster (skills velocity) and adapt more easily to new demands (skills agility).

For employers in demand of talent, AI can make it easier to assess skills at scale, improve candidate-job fit, and shorten time-to-hire. That means better matches, higher retention, and stronger, more diverse talent pipelines.

Guidelines for Building an AI-Driven, Skills-First Future

To ensure AI benefits STARs, we must:

— avoiding legacy data and assumptions that reflect past bias.

— including employers, policymakers, and tech platforms — to create shared skills taxonomies and hiring practices that value all talent.

— tracking whether AI-enabled tools are truly expanding opportunity for STARs, not narrowing it.

If you can do the job, you should get the job

And AI should help make that happen.

AI is not a silver bullet. Dismantling decades of exclusion will take years of work. But with more than 70 million STARs in the U.S. workforce, the payoff for building AI that values all skills is too great to ignore.

Learn more about this topic in Brookings by Opportunity@Work’s Founder and CEO, Byron Auguste, and Chief Impact Officer, Papia Debroy.