Want to Close the Skills Gap? Bring Learning Closer to Work
The World Economic Forum's Future of Jobs Report 2025 asked more than 1,000 employers, representing 14 million workers, what stands between them and the transformation they are trying to execute. Sixty-three percent named the same thing, and it wasn't capital or technology. It was the skills gap. Specifically, not having their employees ready for the work the future will require.
That number has been quoted in nearly every keynote I have heard this year. What gets quoted less is what employers intend to do about it. By 2030, 85% plan to prioritize upskilling their workforce. In response to AI specifically, 77% plan to upskill or reskill existing employees. I have rarely seen agreement that broad on any workforce question over my past two decades in higher education.
Yet the gap persists, year over year, across nearly every dataset I read. Whether employers believe in upskilling is settled. They clearly do. What we need to reconcile is why so much genuine intent keeps failing to reach the people who actually need the training.
When we look at the data through today's top use case — AI — a deeper insight emerges: Only 48% of workers agree that their organization provides sufficient time during work hours for AI skills development and nearly one-third of workers (28.3%) say their organization does not provide AI training at all. Beyond existing employees, 59% say they see no reason to hire someone who does not already bring a skills advantage.
The skills employers say they cannot find are increasingly the skills they expect employees and candidates to arrive with, fully formed, at their own expense.
What Conventional Wisdom Got Wrong About AI and the Future of Work
For most of the last decade, the loudest advice in the labor market was that technical ability was the priority. Learn to code. Get a technical or professional certification. That message dominated public conversation for years.
The latest technical skill in demand is AI. The market has now corrected, and I believe it has overcorrected in some ways. Open a professional feed and you will likely come across a claim that human, durable skills are the new moat and the last thing AI cannot replace. It has become its own cliché, and it repeats the original error in reverse.
Regardless of which skills are trending, the deeper problem is that fluency compounds where it already exists. People whose work puts them near these tools will use them daily, get better, and grow more confident about what the technology will do for their careers. Instead, people whose jobs keep them at a distance get none of that, and the gap widens over time.
This is why I resist the idea that AI is an inherently democratizing technology. It democratizes capability only for those already close enough to touch it. The World Economic Forum makes the same point when it notes that how these roles evolve carries direct consequences for economic mobility.
That is not a talent problem. It is a distribution problem, and distribution problems have solutions.
AI Is Redefining the Workforce
If access to AI skills is a distribution problem, the stakes will only grow as work changes. The World Economic Forum's projections broadly support it: 170 million roles created against 92 million roles displaced by 2030. That's a net increase of 78 million jobs, with roughly 39% of core skills changing along the way.
The caveat, however, is the person displaced from customer operations in Ohio is not the person hired into an AI governance role in Austin, and the distance between those two facts is measured in years, money, and time that most working adults cannot take away from a job and a family. If we expect workers to move into the jobs being created, we have to give them a realistic way to build the skills those jobs require.
Our own research at DeVry shows where that distance turns into a barrier. Nearly nine in 10 employers say they offer company-paid upskilling. By their own estimate, only about half of their workers use it. Something is failing between the benefit being offered and the adult with a full-time job, commute, and children who need care and attention.
The easy reading is that people are not motivated. However, I have spent more than two decades around adult learners, and I do not believe that for a moment.
The learners DeVry serves are enrolling in programs while holding down jobs and juggling several competing priorities. What they are short of is not will. It is capacity: the hour that is not already claimed by a shift, a commute, a child, or a second job.
Upskilling Fails When We Treat Learning as Separate from Work
Upskilling or reskilling is often framed as an individual responsibility: a matter of initiative, of staying current. But if employers need these skills, they have a stake in making sure workers have a realistic way to develop them.
That means developing technical and durable skills together and creating pathways that blend instruction with on-the-job application. We see this through our partnership with Microchip Technology in Arizona, where employees learn in cohorts while continuing to work and have opportunities to apply what they're learning on the job.
The lesson extends beyond one employer or industry. If the jobs of the future require different skills, creating those jobs is only half the equation. We also need realistic pathways for people to reach them.
The skills gap may be a talent challenge. Closing it is a distribution challenge. And employers and higher education need to solve it together.