Artificial intelligence (AI) is rapidly automating many of the tasks that once defined entry-level roles, contributing to a decline in demand for some positions while reshaping the responsibilities and skill sets required for others. In the process, the traditional bridge between education and employment is beginning to erode. In fact, 66% of hiring managers say most recent hires are not fully prepared for their roles, mainly due to a lack of experience.

But even before AI, other opportunities that historically played a vital role in connecting education and employment were disappearing. In 2023, nearly 4.6 million students who wanted internships could not secure one. Yet 87% of employed graduates say internships helped them land their job, while more than half of those without an internship believe it hurt their job prospects, according to our Cengage’s Graduate Employability Report.

As internships become harder to access and AI reshapes entry-level jobs, the result is a widening experience gap, leaving new workforce entrants without opportunities to apply what they have learned in real-world settings.

Colleges Must Redesign How Experience Is Delivered

At its core, the goal of education is to prepare individuals for employment and advancement. But as AI alters the nature of entry-level work, institutions can no longer assume students will gain practical experience after graduation. Increasingly, workforce readiness must be embedded directly into the educational experience itself.

Students themselves are signaling this need. More than half (56%) of graduates who feel unprepared for entry-level roles say they lacked job-specific skills, while 79% of Gen Z believe it’s important to have on-the-job learning experience during their post-secondary education. By leaning into seizing this opportunity to help close the emerging experience gap, institutions will not only educate students but ensure they are prepared for today’s workforce. Here’s how institutions can best accomplish this:

1. Embed experience directly into the curriculum 

Experiential learning must be built into the core of higher education, not treated as an add-on. That can take many forms, from immersive simulations and virtual or augmented reality tools that mirror real workplace scenarios to project-based learning that allows students to solve real business challenges as part of their coursework. As automation takes over more procedural and repetitive tasks, employers increasingly value skills such as judgment, adaptability, communication and problem-solving – capabilities best developed through hands-on experiences. Additionally, when real-world application is integrated into the curriculum, every student, not just a select few, graduates with the needed hands-on experience.

2. Build deeper partnerships with employers

Closer alignment with employers is critical to ensuring education keeps pace with workforce needs. Employers bring a real-time understanding of in-demand skills and evolving industry trends — insight that is invaluable for both educators and learners. This becomes especially important as AI accelerates how quickly workplace tools, workflows, and expectations evolve. Static degree programs alone cannot adapt quickly enough to keep pace with technological change without deeper employer collaboration.

These partnerships should also extend into structured programs such as co-ops and apprenticeships, creating a reliable pipeline of opportunities for students to build hands-on experience as part of their education. For example, Northeastern’s co-op program reports that 97% of students are employed or in graduate school within nine months of graduating, and 58% receive job offers from a previous co-op employer.

For employers, these programs provide earlier access to emerging talent while helping ensure graduates enter the workforce with job-ready skills. For students entering AI-disrupted industries, these experiences are becoming even more valuable because they expose students to how professionals actually work alongside emerging technologies in real-world environments.

3. Redefine how outcomes are measured

In many ways, AI is forcing higher education to confront a fundamental question: not simply whether students completed a program, but whether institutions truly prepared them for the realities of modern work.

Answering that question requires institutions to focus more closely on the outcomes that matter most — how well learners are prepared to enter and grow in the workforce. By tracking employment outcomes and career progression, institutions can gain clearer insight into their strengths and where gaps remain, creating a more informed path to continuously improve workforce readiness and close the experience gap. Ultimately, success is not only defined by what happens in the classroom, but by what happens after learners leave it.

AI is forcing a fundamental rethink of how workers gain experience, build confidence and transition into professional life. If entry-level work no longer functions as the training ground it once was, higher education has a critical role to play in helping fill the gap — but it cannot solve this challenge in isolation.

The traditional degree model was never designed to fully replace real-world experience, and expecting it to do so now is unrealistic. Preparing the next generation of workers must be a shared effort across educators, employers, and policymakers. That means policymakers expanding access to high-quality, workforce-aligned learning opportunities and employers investing more deeply in early-career development and partnerships with institutions.

The question is no longer whether AI will reshape the first rung of the career ladder. It already is. The real challenge is ensuring the next generation still has a way to climb.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.