Artificial intelligence is moving fast across industries, and honestly, it’s creating a real tension. On one hand, productivity is up; on the other, new grads might face a tougher job market than ever.
This blog takes a look at recent statements from industry leaders and some key labor stats. The goal? To get a sense of how AI adoption could shake up unemployment and underemployment for recent college graduates—and what that means for education, policy, and workforce planning.
AI adoption and the labor market signals
Bill McDermott, CEO of ServiceNow, didn’t mince words: he warned that AI adoption could dramatically raise unemployment for new college graduates. Software “agents” are already taking over loads of entry-level tasks.
He thinks this pace of change could push unemployment rates for grads into the mid-30s within just a few years, unless the workforce and education systems adapt. In late 2025, the Federal Reserve Bank of New York put the unemployment rate for recent grads at about 5.7%, with underemployment at 42.5%—the highest since 2020. That’s not a number you can just ignore.
Across all sorts of sectors, businesses are rolling out AI tools to crank up productivity and cut the need for human labor. Economists call it a productivity-first approach. Automation and AI let companies keep or even grow cash flow and revenue with fewer hires.
Demand and output can rise, but that doesn’t always mean more jobs. For new grads, it’s a weird spot: they’re up against software agents that can handle a lot of routine and even some cognitive tasks.
The role of AI agents in entry-level work
ServiceNow says it automated about 90% of customer service use cases that used to need humans. That’s a pretty huge shift.
When you look at customer service, data entry, or basic analysis, these AI tools can hammer through repetitive tasks with a speed and consistency that’s tough for people to match. For young workers, the old path from internship to entry-level job might be shrinking or changing shape.
That means new skill sets are in demand—ones that work with AI, not against it.
Industry responses and the balance between productivity and jobs
AI’s growth is clear, but so is the pressure to cut costs. Block just announced it’s planning to cut nearly half its workforce, blaming AI automation as a big reason.
Atlassian also disclosed about a 10% layoff, saying it would shift resources to scale up AI investments. That move rattled its stock, with investors worried about disruption.
Other tech leaders, like Alex Karp at Palantir and Andy Jassy at Amazon, have signaled plans to grow revenue while shrinking headcount in certain areas thanks to AI. They’re not just replacing people—they’re trying to use AI to change how work gets done and where humans fit in the mix.
Strategies of leadership in the AI era
From a strategy standpoint, execs seem to be running on two tracks. They’re investing in AI to unlock new revenue and streamline operations, but also shifting human talent toward higher-value work that’s tough to automate.
For new grads, it’s a clear sign: focus on skills that are hard for AI to copy—complex problem solving, nuanced communication, creative design, and collaboration across fields. Human judgment still matters, maybe more than ever.
Implications for education, policy, and workforce planning
The rapid pace of AI-enabled change calls for a coordinated response from educators, policymakers, and industry. If graduate unemployment and underemployment rise, the education system might have to pivot toward lifelong learning.
We’d need to emphasize digital literacy, AI fluency, and cross-disciplinary skills that blend technical know-how with domain expertise. Workforce development programs could focus on retraining people displaced by automation.
Employers might want to invest more in on-the-job learning so new graduates can bridge the gap between coursework and real-world AI-assisted roles. In the near term, the data really suggest a careful, evidence-based approach.
We should monitor unemployment and underemployment trends, figure out which jobs are most at risk, and target retraining efforts where they’ll matter most. Sure, AI brings big productivity gains, but how it affects jobs? That’ll depend on policy, business decisions, and how quickly education adapts to shifting demand for skilled labor.
- AI empowerment can unlock new revenue, though it may push job requirements toward higher skills.
- New graduates face a transformed entry landscape that rewards adaptability and AI collaboration skills.
- Retraining initiatives are essential to mitigate underemployment and keep the economy resilient.
- Transparent company strategies around automation will shape public perception and workforce planning.
- Ongoing data collection (like NY Fed metrics) is crucial to track progress and adjust policies in real time.
Organizations are embedding AI deeper into operations, and the workforce of the future will probably be shaped by a mix of human expertise and smart automation. It’s up to the scientific and policy communities to turn these insights into practical, scalable solutions for workers at every level.
Here is the source article for this story: AI agents could easily send college grad unemployment over 30%, ServiceNow CEO says