This spring, tech executives began sounding the alarm that artificial intelligence (AI) was making entry-level office jobs, long relied on as training grounds for advanced skills and networking, obsolete. Since then, headlines have warned that AI will disrupt the bottom rungs of the career ladder, especially for younger workers, with white-collar jobs such as software developers likely to be the first to be disrupted by AI. Other analysts predict that over time, low-wage service workers could ultimately be the hardest hit.
But the situation is more complex than entry-level jobs disappearing overnight. Some forecasts emphasize large-scale layoffs, while others argue that as employers begin to use AI in the workplace, they will be more likely to reskill employees rather than fire them. In this way, AI may be more likely to augment human workers rather than completely replace them.
Whether AI transforms, augments, or replaces jobs in the future, young Americans are already facing important career and education decisions and trying to grapple with uncertainty. Those with more connections and easier access to information are likely to benefit most, and existing opportunity gaps can widen quickly, as can early career roles and other opportunities to gain work experience.
This article highlights key insights from interviews with state and community leaders about how to strategically address these opportunity gaps. We spoke with 21 state and local innovators from workforce agencies, community colleges, and training organizations about how they’re working across programs to build career paths for young people. This June, we distilled their insights to create “A Blueprint for Developing Economic Opportunity for All Youth,” published by the American Research Association.
Our research reveals that on top of AI disruption, state and local leaders are feeling additional pressure to better organize scarce and siled resources to help young people gain skills and find their first jobs amid federal budget cuts. As AI disruption evolves, this effort is likely to become even more urgent. The benefits from AI may not be evenly distributed, and uncertainty alone is changing the way young people think about their futures.
Young people still need basic career support
Interviews with state and local innovators reveal that while AI may dominate the headlines, the real barriers to youth economic mobility are not new problems posed by technology. Rather, there are long-standing challenges such as unequal access to information to inform career choices and lack of early practical work experience, barriers that the uncertainties of AI have made solving more urgent.
While there is no silver bullet for youth economic mobility, there are clear strategies for future-proofing skills development for an AI-enhanced workplace. Additionally, our research with state and local innovators seeking to support young people on their path to career success reveals that whether AI disrupts or transforms jobs, young people still need basic support, including:
Rich service.Success requires building a variety of skills (vocational, essential, and foundational), supporting career navigation, addressing basic needs, and providing individualized attention through mentorship and coaching.
Leaders at Per Scholas, which provides sector-specific training for technology careers, said it’s important to combine technical skills training with a wide range of other skills training and services, such as coaching, work readiness skills, social capital connections, transportation, childcare, and paid work experience to cover basic needs. For young people between the ages of 16 and 24, who often suffer from the aftermath of trying something and failing, it’s important to regain confidence and use learning experiences to overcome impostor syndrome.
Practical experiential learning.The innovators we spoke to emphasize apprenticeships, internships, and field-specific training that provide real-world work experience as early as middle school or high school. These work-based learning programs provide youth with a built-in network of mentors and peers, providing lasting social capital.
In Charleston, South Carolina, employers, Trident Technical College (a community college), and several high schools have collaborated on apprenticeships since 2014. Employer partners wanted to provide apprenticeships to high school students, which led to the creation of the Charleston Regional Youth Apprenticeship Program, one of the first regional youth apprenticeship initiatives in the nation. Youth apprentices receive paid hands-on learning and mentoring on the job, receive stipends for related mentoring, earn college credits, and receive a certificate of completion from the U.S. Department of Labor upon completion.
Human-centered navigation.AI cannot replace the power of mentoring. Humans can help individuals access information and provide guidance across fragmented systems such as social services, educational programs, and career opportunities.
In Denver, a collaborative network of partners began planning a sophisticated partnership model organized around the metaphor of climbing a mountain with the common goal of building regional wealth. Jason Jantz, a key leader in that effort and CEO of a community-based organization called CrossPurpose, identified three capabilities as necessary elements of a human-centered local ecosystem. “Negotiators” focused on policy-level and systems-level infrastructure. and a “navigator” that directs individuals to personalized resources across the organization. Of all these features, navigation was the most lacking. To address this gap, they work closely with individuals in ways that are tailored to their specific circumstances and support their success and financial mobility over a period of three to 10 years.
A collaborative ecosystem.Rather than individual programs competing across fragmented silos, successful districts build sophisticated partnerships that center youth needs, coordinate funding flows, and share data across organizations.
Recognizing the amount of infrastructure spending in the Austin, Texas region, leaders from the Labor Board, Chamber of Commerce, Mayor’s Office, and community college system all came together to create the “Infrastructure Academy.” City Council approved $5 million to use a “follow the person” funding model, where individuals are directed to services based on what they need, rather than a preset set of services. We found that for young people aged 16 to 24, it is important to start paid work-based learning early, but to combine it with services such as personalized navigation support and childcare.
Funders and decision makers need to focus on long-standing gaps, not just the impact on AI
Rather than trying to predict the specific labor market impacts of AI through new programs and further pilots, funders should invest in helping state and local innovators build evergreen, demand-driven, ecosystem-level support and infrastructure.
- strategically co-invest in the ecosystem;Expose youth to experiential learning in the workplace, not just a single program or grantee.
- Address navigation gapsAt every stage of the confusing transition from school to career.
- Connecting program innovatorsWith partners working on digital transformation through communities of practice.
- Build capacity across the ecosystemThrough technical assistance, fast cycle learning, peer networks, and backbone organizations.
AI will continue to transform the nature of work, but the innovators we spoke to aren’t waiting around for those changes to unfold. They are building adaptive, human-centered systems that are prepared for uncertainty itself by equipping young people with the information, skills, networks, and resilience to survive whatever the future holds.
As one local leader told us, success requires moving beyond “individual operator silos” to “sophisticated regional ecosystems centered around the needs of young people.” The era of AI anxiety requires a collaborative and adaptive response rather than a rigid single-program solution. State and local leaders have already set the tone, and now we need to accelerate that momentum.
