AI is absorbing the tasks that once defined entry-level work, and the data on what comes next is grim: 66% of hiring managers say most recent hires are not fully prepared for their roles, citing a lack of experience as the main reason. That figure, drawn from Cengage's Graduate Employability Report, lands as the traditional first rung of the career ladder — junior analyst, paralegal, junior developer, marketing coordinator — is being automated, compressed, or eliminated outright across white-collar industries.
The internship pipeline, long the workaround, is also shrinking. In 2023, roughly 4.6 million students who wanted internships could not secure one. Yet 87% of employed graduates credit an internship with helping them land their job, and more than half of those without one say its absence hurt their prospects. Two pathways into professional work are narrowing at the same time.
Cengage frames the result as a widening experience gap. With AI rewriting what junior employees actually do day-to-day, employers are reluctant to hire candidates who have only completed coursework, and students are graduating without the on-the-job exposure that used to come automatically in the first year of work. As Cengage put it, "the traditional bridge between education and employment is beginning to erode."
Key facts
- 0166% of hiring managers say most recent hires are not fully prepared for their roles, mainly due to lack of experience.
- 024.6 million students who wanted internships could not secure one in 2023, per Cengage's Graduate Employability Report.
- 0387% of employed graduates say internships helped them land their job; more than half without one say it hurt their prospects.
- 0497% of Northeastern co-op students are employed or in grad school within nine months of graduating; 58% get offers from a prior co-op employer.
- 0579% of Gen Z say on-the-job learning during post-secondary education is important.
Students see it too. Among graduates who feel unprepared for entry-level roles, 56% say they lacked job-specific skills. And 79% of Gen Z say it is important to have on-the-job learning experience during their post-secondary education — a clear signal that the cohort entering the workforce is asking for the experiential component to come earlier, inside the degree, not after it.
“Northeastern's co-op program reports 97% of students are employed or in graduate school within nine months of graduating, and 58% receive offers from a prior co-op employer.”— Jaeden Schafer
Cengage's argument is that workforce readiness has to be built into the curriculum rather than bolted on. That means immersive simulations, VR and AR tools that mirror real workplace scenarios, and project-based coursework where students solve actual business problems. As automation takes over procedural tasks, employers increasingly value judgment, adaptability, communication, and problem-solving — skills that develop through practice, not lectures.
Closer ties with employers are the second prescription. Cengage argues that "static degree programs alone cannot adapt quickly enough to keep pace with technological change without deeper employer collaboration," and points to co-ops and apprenticeships as the structural fix. The reasoning is mechanical: employers know what tools are in production this quarter; universities know what was in production three years ago.
Northeastern's co-op program is the case study Cengage cites. 97% of its students are employed or in graduate school within nine months of graduating, and 58% receive job offers from a previous co-op employer. The model converts the internship lottery into a guaranteed work-experience track embedded in the degree itself, with employers underwriting access to talent earlier in the funnel.
The third lever is measurement. Cengage argues institutions should track employment outcomes and career progression as core metrics of program quality, not as marketing afterthoughts — turning the question of whether a graduate can actually do the work into something universities are accountable for. That is a significant cultural shift for higher education, which has historically measured completion rather than placement.
The harder problem is scale. Northeastern's co-op model is decades old and resource-intensive, requiring a full-time employer-relations apparatus that most colleges do not have. Replicating 97% placement across thousands of less-selective institutions, with smaller employer networks and tighter budgets, is not a curriculum tweak — it is an operating-model change. And the policy infrastructure to fund apprenticeships at scale in the United States remains thin compared with European peers.
Cengage concedes the lift: "The traditional degree model was never designed to fully replace real-world experience," and preparing the next generation of workers "must be a shared effort across educators, employers, and policymakers." In other words, no single actor can close the gap alone, and the timeline on which AI is rewriting entry-level work is shorter than the timeline on which universities typically reform.
The market implication for AI companies is worth naming directly. The same labs whose products are compressing the junior tier — automating first-draft code, first-draft memos, first-draft research — are also the natural buyers of the experiential-learning layer that has to replace it. Expect a wave of AI-native simulation platforms, agent-based training environments, and employer-funded apprenticeship tooling to land in higher education over the next 24 months, because the alternative is a generation of graduates that the employers building these models cannot themselves hire.
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