If AI Does the Entry-Level Work, Where Do Future Leaders Come From?

Alexandra Levit on what a degree still buys

NervNowThe recent Gallup data shows workers with degrees are now more downbeat about finding good work than workers without them, a turn from the old order. What is behind that, and is it a passing mood or a lasting repricing of what a degree buys?

It’s definitely not a passing mood but a structural shift I’ve been watching for a few decades. Everyone is asking: Where and when do you actually need a degree to do X, Y, or Z? Can you get a certification instead? A microcredential? The degree’s monopoly on signaling competence has been eroding for a long time, and given what it costs to get one, workers are understandably pessimistic about a degree’s ability to guarantee a bright financial future.

NervNowAI can now handle much of the analytical work a degree used to vouch for. Does that hollow out the credential itself, or change what employers need it paired with before they trust it?

Credentials aren’t going away, and their relevance still depends on the industry. But I’d argue that in addition to a credential, every human worker needs pre-industrial skills like creativity, curiosity, ethical judgment, problem-solving, learning agility, and interpersonal communication. A degree can’t certify those and employers need to get much better at validating them. Also, while AI may take over certain routine, repeatable tasks, nothing replaces human oversight at every juncture of a business process. So both schools and employers need to improve how they teach this oversight capability.

NervNowFor a company weighing whether to drop degree requirements, what is the upside, and what goes wrong when employers do it without something to assess skills in the degree’s place?

The upside of having access to wider talent pools is certainly greater than the downside of risking your employee might not be as competent as a degree implies. And that competence is up for debate. Ideally, high-quality talent should be assessed through past projects, AI-driven assessments, simulations, and peer reviews. However, you shouldn’t drop a degree requirement without skills-based assessments in place to close the gap.

NervNowWhite-collar employment overall has kept growing in recent years, even as early-career workers in AI-exposed roles have lost ground. How do you read that split, and where does a career begin when the bottom rung is the part being automated?

According to recent research I conducted with SAP SuccessFactors, we are seeing a six percent decrease in early talent employment since 2022, while the number of applicants per entry-level opening has doubled over five years. This is partially due to AI, and partially due to leaders generally wanting to do more with less. But when we don’t take care of our young workers in the form of valuable, hands-on experience today, they cannot develop such that they’re in a position to run our organizations in the future.

NervNowAs the tools keep advancing, which human capabilities hold their value, and what should education set out to teach on purpose instead of leaving it to a first job that may not be there?

I mostly answered this already, but I always come back to creativity, curiosity, ethical judgment, problem-solving, learning agility, and interpersonal communication. We have to remember that the audience for most AI-driven output is human. LLMs do not generate new ideas on their own, and they don’t know if their output is creative, or accurate, or contextually relevant. Since the mid-2000s, I’ve discussed the need for a human in the loop wherever technology is inserted into a traditionally human-driven process. Higher education can advance all these skills, but we need a change of model.

NervNowIf we set the technology aside for a moment, what does experience earned before graduation give a young worker that a classroom degree cannot?

Earlier, real-world work experiences help students test their interests and make better decisions before investing more time and money in postsecondary education. But beyond self-discovery, high-quality work-based learning builds the human attributes and work-ready skills that employers say our young people sorely lack (discipline, self-awareness, professional context, etc.). A traditional classroom has its place, but the limitations of its format mean it can’t be the only source of learning.

Stephanie Loeck on what employers screen for now

NervNowFrom where you sit with employers, does the pessimism among degree-holders match what hiring managers are doing in practice, or has the anxiety run ahead of what they are deciding?

Anxiety around the value of a degree and what that may or may not translate to in the job market has been building for a long time. Despite many efforts, there continues to be a skills mismatch between what educational institutions are producing and what employers need. Specifically, employers value real-world experience more than theoretical knowledge, and that seems to be especially true with the proliferation of AI. Work-based learning that allows students to apply and demonstrate their knowledge, skills, and abilities in real-world projects, alongside or in place of a degree, is one way that students can mitigate the risk of getting caught in that gap.

NervNowWhat are employers in your network screening for now that a transcript cannot tell them, and have you seen any of them drop degree requirements outright?

Beyond a transcript, demonstrations of competency are increasingly important in hiring. This might come in the form of a performance task that is part of the interview process, or in additional evidence like a digital portfolio of previous work or an industry-recognized credential that validates what someone can do. High-quality work-based learning is a pathway for students to gain this experience prior to applying for jobs. Notably, work-based learning experiences also help provide real-world examples of a student’s capabilities that can be referenced in an interview to help set them apart from other entry-level talent.

NervNowWhen software does the entry-level tasks new hires once learned on, what are employers telling you they expect a young worker to walk in already able to do? What concrete change have you seen them make in the past year?

Employers value durable skills like communication, creativity, critical thinking, and leadership. Ultimately, these are the professional and human competencies that help young workers take initiative, integrate into teams, learn on the job, and effectively adapt as technology rapidly changes. Compared to technical skills, these are also the skills that are hardest to teach. Most employers prefer to onboard young workers with their proprietary technologies and processes rather than spend time coaching them toward these skillsets. Importantly, as AI takes over much of this work, durable skills have an even greater premium in the market.

NervNowIf companies pull back on entry-level hiring because AI now does that work, where do their mid-level and senior people come from in five years? What are the smartest employers doing so they do not hollow out their own pipeline?

At GPS Ed, we spend a lot of time helping employers understand “the funnel to their funnel” within their talent strategy. Since training and skill development take time, how are you being proactive to ensure enough students are entering the early stages of the funnel through career awareness and exploration, activities like projects or mentoring, rather than entry-level jobs, to convert into the specific hires you will need down the line? The employers who ‘get it’ leverage a thoughtful combination of external work-based learning and internal training to meet their needs efficiently. You don’t necessarily have to hire someone full-time to expose them to your company’s culture or job opportunities.

NervNowHow does a work-based learning placement have to be rebuilt when the routine work it used to teach is now done by AI? What do you make sure a placement still puts into a student?

GPS Ed defines high-quality work-based learning as “authentic learning that helps a student develop the aspiration, abilities, and agency to succeed in the world of work.” At its core, it’s about helping a student build meaningful relationships and reflect on their experiences to move confidently toward the next step in their career. AI is changing how work will get done, but humans will still need to oversee the technology and work alongside it. The most effective way for companies to develop that skillset across the current and future workforce is to encourage the relationship-building that allows for shared learning, mentoring, and accelerated transformation.

NervNowFor an organization starting one of these pipelines from scratch, what are the first practical steps, and what is the mistake that ends these programs in their first year?

The GPS Ed Approach is a six-part framework that helps organizations design, implement, and grow work-based learning programs. Specifically, it walks you through defining the why, who, what, how, so what, and now what of a high-quality program built around your unique needs. With that in mind, it’s critical to develop a common vision for your program that is shared across key internal and external stakeholders, like potential school partners or community groups. Since this work can be complex, we’d recommend starting small with a pilot program, then iterating and growing from there. One of the biggest mistakes people make is aiming for something too big, too quickly. This either keeps people from ever getting off the ground or failing to meet everyone’s expectations upon initial delivery, causing a critical partner to drop out and putting the program’s longevity at risk.

Stephanie Reisner on the first rung

NervNowYou launched what became GPS Ed in 2000, long before AI was a hiring factor. Of everything you have watched change in work-based learning over 25 years, what has AI shifted in the last two that the prior 23 did not?

Over the past 25 years, we’ve seen major shifts in technology, economic cycles, and workforce needs. What feels different about AI is the speed at which it’s changing expectations for work itself.

Previous changes tended to affect industries over time. AI is reshaping tasks, workflows, and skill requirements almost in real time. Employers are still hiring people, but they’re rethinking which tasks require human effort and which can be automated or augmented. That creates a moving target for both educators and workforce leaders.

What hasn’t changed is the value of experience and durable skills. In fact, I would argue that AI makes work-based learning even more important. When information is available instantly and routine tasks can be automated, employers place greater value on judgment, communication, problem-solving, adaptability, and the ability to apply knowledge in real-world situations.

The students who will thrive are not the ones who simply know the right answers. They’re the ones who know how to work with people, navigate ambiguity, use technology effectively, and continue learning as work evolves. Those are skills best developed through authentic workplace experiences.

NervNowGPS Ed has worked with hundreds of employers and placed more than 10,000 students. As AI takes on the routine entry-level work new hires used to learn through, what are those employers now asking of a placement that they were not asking five years ago?

Five years ago, many employers were primarily looking for students who could complete assigned tasks and learn established processes. Today, we’re hearing more emphasis on adaptability, curiosity, communication, and the ability to learn continuously.

Employers understand that technical tools will continue to change. What they’re looking for are young people who can ask good questions, solve problems, work collaboratively, and use emerging technologies responsibly and effectively.

We’re also seeing increased interest in students who can connect classroom learning to real-world challenges. Employers want individuals who can think critically, evaluate information, and contribute ideas, not just complete a checklist of tasks.

In many ways, AI is elevating the importance of the very skills that work-based learning helps develop. The workplace is becoming more technology-enabled, but it’s also placing a premium on the human capabilities that technology cannot easily replicate.

NervNowYou scaled from a single employer pilot to national reach. For regions watching AI reshape entry-level work and wanting to build these pipelines quickly, what is the one thing AI cannot speed up?

Relationships.

AI can help us analyze data, streamline processes, and improve efficiency. What it cannot do is build the trust required for effective work-based learning systems.

Strong talent pipelines are created when educators, employers, families, community organizations, and students work together toward a shared goal. Those relationships take time, communication, and a commitment to understanding each other’s needs and challenges.

The communities making the most progress are not necessarily the ones with the most advanced technology. They’re the ones that have built strong partnerships and a culture of collaboration.

Technology can accelerate many aspects of the work. It cannot replace the human relationships that make these systems sustainable and successful long term.

NervNowThe book frames work-based learning as the answer to a youth employment crisis. With AI now removing many of the entry-level jobs young people used to start in, does that make the case more urgent, and what happens to a generation that cannot find a first rung?

It absolutely makes the case more urgent.

For generations, young people gained experience through entry-level jobs that allowed them to learn workplace expectations, develop professional skills, and begin building networks. If those opportunities become less accessible, we have to be intentional about creating new pathways into the workforce.

The greatest risk isn’t that AI replaces all jobs. The greatest risk is that young people struggle to get the experience that helps them become employable in the first place.

That’s why work-based learning matters. It provides students with meaningful opportunities to apply their learning, develop durable skills, build relationships with mentors, and understand how work actually happens. Those experiences become increasingly important as the labor market evolves.

If we allow a generation to lose access to that first rung, we risk creating a wider disconnect between education and employment. But if we invest in high-quality work-based learning, we can give young people what they’ve always needed: a chance to gain experience, contribute value, and see a future for themselves in the workforce.

The future of work may look different, but the need for a first opportunity is more important than ever!