Common Questions

What are STARs and why are their jobs at risk from AI?

STARs (Skilled Through Alternative Routes) are roughly 70 million US workers without four-year degrees. Research found 11 million of them work in gateway jobs in the highest AI-exposure occupational categories, making them especially vulnerable to displacement.Source: background

How many US workers don't have college degrees and could be replaced by AI?

Opportunity@Work estimates roughly two thirds of the US workforce (about 70 million people) are STARs who gained skills without four-year degrees. Of those, 11 million work in the most AI-exposed gateway occupations.Source: background

Can workers without degrees retrain for new AI jobs?

Opportunity@Work argues that degree requirements on new AI-era roles create a structural barrier: STARs displaced from gateway jobs often cannot access the adjacent knowledge-work positions because of credential screens, even if they have the underlying skills.Source: background

Background

STARs (Skilled Through Alternative Routes) is a term coined by Opportunity@Work to describe an estimated 70 million US workers who developed their skills through military service, community college, trade apprenticeships, or sustained on-the-job training rather than completing a four-year university degree. The concept challenges the assumption that a bachelor's degree is a reliable proxy for workplace competency, arguing that degree-based hiring screens exclude a large share of the capable workforce and concentrate economic mobility among the credentialled.

The AI displacement debate gave the STARs framework new urgency. Research published by Opportunity@Work with Brookings and the Hamilton Project found 11 million gateway jobs in the highest AI-exposure occupational categories are held predominantly by STARs. These roles, which previously offered non-degree workers a route into the middle class, are now simultaneously threatened by AI substitution and shielded from displaced workers by the degree requirements of adjacent knowledge-work roles. The finding positions STARs as the group most likely to face displacement without a retraining ladder.

STARs represent a structural feature of the US labour market: Opportunity@Work estimates that two thirds of the US workforce qualifies, disproportionately Black, Latino, and rural. The ILO and World Bank's 2026 joint study on AI exposure found women globally face nearly double the AI job risk of men, a finding that intersects with the STARs distribution; female-dominated clerical and administrative roles are both high-exposure and often held by workers without degrees.