This spring, tech executives began warning that artificial intelligence (AI) is making entry-level office jobs obsolete. These positions, traditionally seen as training grounds for advanced skills and networks, are now at risk. Headlines have since highlighted that AI could disrupt white-collar jobs such as software developers, particularly for younger workers. Other analysts predict that low-wage service workers may ultimately be the most severely impacted over time. However, the reality is more complex than entry-level jobs simply disappearing overnight. While some predictions emphasize large-scale displacement, others argue that employers are more likely to retrain workers rather than lay them off as they integrate AI into the workplace. This suggests that AI may augment rather than fully replace human workers.
Regardless of whether AI ultimately transforms, augments, or replaces jobs in the future, young Americans are already grappling with uncertainty as they face major career and education decisions. Those with more connections and better access to information may benefit most, potentially widening existing opportunity gaps as early-career roles and other opportunities for gaining work experience become scarcer. This piece highlights critical insights from interviews with state and community leaders about how to strategically address these opportunity gaps.
State and local leaders are under added pressure to marshal scarce and siloed resources effectively to help youth build skills and find their first job, especially amidst federal budget cuts. This work will likely become more urgent as AI disruptions unfold. The gains from AI may not be evenly distributed, and uncertainty alone is reshaping how young people think about their futures. While AI may dominate headlines, the real barriers to youth economic mobility are long-standing challenges such as unequal access to information to navigate career options and a lack of early, hands-on work experience. These barriers have become more urgent to solve due to AI uncertainty.
There is no magic bullet for youth economic mobility, but there are clear strategies for future-proofing skill development in an AI-augmented workplace. Young people still need fundamental supports, including a rich array of services. Success requires diverse skill-building (occupational, essential, and foundational), career navigation support, meeting basic needs, and personalized attention through mentorship and coaching. For youth ages 16 to 24, who often deal with the aftermath of trying and failing, it is critical to restore a sense of self-confidence and use their learning experiences to overcome imposter syndrome.
Hands-on, experiential learning is emphasized through apprenticeships, internships, and sectoral training that offer real workplace experience starting as early as middle and high school. These work-based learning programs embed youth with mentors and peer networks that provide lasting social capital. Employers, community colleges, and high schools have collaborated on such initiatives, providing youth with paid hands-on learning, mentoring, scholarships, college credit, and certificates of completion.
Human-centered navigation is crucial because AI cannot replace the power of a mentor. Humans can help individuals unlock access to information and provide guidance by cutting across a fragmented system of social services, education programs, and career opportunities. Successful regions are building sophisticated partnerships that center youth needs, align funding streams, and share data across organizations. This collaborative approach ensures that youth receive the support they need to succeed.
Rather than individual programs competing across fragmented silos, successful regions are building collaborative ecosystems. These ecosystems focus on youth needs, align funding streams, and share data across organizations. For example, leaders in Austin, Texas, formed an “infrastructure academy” to provide individualized support and services such as child care. The city council approved funding to use a “follow the person” model, directing individuals to services based on their specific needs.
Funders and decision-makers should focus on long-standing gaps, not just AI impacts. Instead of trying to predict AI’s specific labor market effects through new programs or more pilots, they should invest in helping state and local innovators build evergreen, demand-driven, ecosystem-level support and infrastructure. This includes strategically co-investing in ecosystems, addressing navigation gaps, connecting program innovators with their counterparts working on digital transformation, and building ecosystem-wide capacity through technical assistance, rapid-cycle learning, peer networks, and backbone organizations.
AI will continue to transform the nature of work, but innovators are not waiting for those changes to unfold. They are building adaptive, human-centered systems that prepare young people for uncertainty by equipping them with information, skills, networks, and resilience to navigate whatever the future holds. Success requires moving beyond “individual operator silos” and toward “sophisticated regional ecosystems that center youth needs.” In an age of AI anxiety, collaborative, adaptive responses are needed rather than rigid, single-program solutions. State and local leaders are already pointing the way, and now their momentum needs to be accelerated.
