The unemployment rate among young college grads sits at 5.6%, hovering near its highest level in more than a decade outside the pandemic. Yet IBM just did something that would make most CFOs pause: announce plans to triple entry-level hiring in the US.
"The companies three to five years from now that are going to be the most successful are those companies that doubled down on entry-level hiring in this environment," Nickle LaMoreaux, IBM's chief human resources officer, said this week. "We are tripling our entry-level hiring, and yes, that is for software developers and all these jobs we're being told AI can do."
The math is brutal for new grads. Data from the Federal Reserve indicates that the unemployment rate among recent college graduates is on the rise, at about 5.6%. Although it remains lower than the 7.8% rate among all young workers between 22 and 27 years old, men with a college degree now have roughly the same unemployment rate as young men who didn't go to college. The college premium is dead. IBM sees opportunity where others see overhead.
The Rewrite Strategy
IBM didn't just announce more hiring. They rewrote the job descriptions. Ultimately, in this AI age, enterprises must "rewrite every job," LaMoreaux noted. "The entry level jobs that you had two to three years ago, AI can do most of them," she said. "You have to rewrite every job."
For example, in 2024, IBM developers would have spent 34 hours a week coding, she said. Now, in 2026, they're still coding, but with AI assistance. They may continue to do testing, but they're also spending more time talking to marketing teams and consulting with and getting feedback from clients to accelerate "milestone roadmaps," LaMoreaux said. Software engineers will spend less time on routine coding—and more on interacting with customers, and HR staffers will work more on intervening with chatbots, rather than having to answer every question.
From Fusion AI's perspective working with enterprises across the GCC, this pattern makes sense. We've watched companies struggle with the false choice between cutting junior staff or ignoring AI capabilities. IBM's approach suggests a third way: redefine roles around what humans do best while letting AI handle the routine.
The Pipeline Problem
Speaking at the 2026 Leading with AI summit in New York last week, IBM's chief human resources officer, Nickle LaMoreaux, described the false economy of layoffs in a world of AI-driven innovation and advancement. While firing those replaced by AI and reducing entry-level hiring may drive cost savings in the near term, LaMoreaux said that risked creating a longer-term scarcity of mid-level managers and experienced workers within the organization.
Between the lines: Hiring at the entry level is a cheap option. One of the earliest studies on AI's workforce impact, from 2023, found that it serves as a way to quickly train newbie employees, and helped reduce turnover. IBMs LaMoreaux explained: If companies simply forego hiring cheaper entry level talent, they may likely have to poach mid-level employees from competitors at three times the cost.
The economics are stark. In 2025, IBM cut its 270,000 person workforce by about 1%, driven by business demand. But they're betting that tripling junior hires will cost less than competing for experienced talent in a tight market. At Fusion AI, we've seen this pattern in DIFC. Senior talent commands premium rates. Junior talent, properly trained, scales faster.
Skills Over Degrees
Natasha Pillay-Bemath, IBM's VP of global talent acquisition and executive search, added that the company is specifically hiring entry‑level talent across roles that support its AI and hybrid cloud roadmap, including software developers, cybersecurity analysts, and AI engineers. Their roles are no longer purely task‑driven, she noted. They are rooted in analysis, problem‑solving, and effective AI use.
According to LinkedIn, AI literacy is now the fastest-growing skill in the U.S. This tracks with what enterprises in the UAE are demanding. From our work with clients across Dubai and the broader GCC, AI fluency isn't optional anymore. It's table stakes.
IBM's approach sidesteps the degree debate entirely. Instead of cutting entry-level positions because AI can do the work, they're hiring people who can work with AI systems. The shift, LaMoreaux said, builds more durable skills for workers while creating greater long-term value for the company. Skills trump credentials when the game changes this fast.
The Counter-Trend
In a time when companies are reducing headcounts in favor of adopting AI tools, IBM is doing something completely different: The tech giant is tripling its entry level hiring, not easing up on it or indiscriminately slashing jobs. In a survey of 240 financial services CEOs released this week by EY, 60% said investment in AI would lead to maintaining or increasing headcount.
The narrative was simple: AI kills entry-level jobs. The reality is more complex. An MIT study in 2025 estimated that 11.7% of jobs could likely already be automated by AI. A TechCrunch survey found that multiple investors think 2026 will start to show AI's potential impact on the labor market. IBM is betting the impact isn't replacement but transformation.
Fusion AI has seen this pattern across our clients. The companies that succeed aren't the ones that cut fastest. They're the ones that adapt smartest. IBM's strategy suggests they understand something about AI that others missed: it's better at augmenting talent pipelines than replacing them.
What This Means for Enterprise Leaders
IBM's move signals a shift in how forward-thinking enterprises approach AI and talent strategy. The question isn't whether AI can do entry-level work. It can. The question is whether cutting junior talent creates more problems than it solves.
We are tripling our entry-level hiring, and yes, that is for software developers and all these jobs we're being told AI can do.
For enterprise leaders in the GCC, the lesson is clear. AI transformation isn't about choosing between humans and machines. It's about redesigning work to leverage both. IBM's approach—rewrite roles, invest in training, build AI-native talent pipelines—offers a template for navigating the transition without sacrificing future capability.
The companies that thrive in the AI era won't be the ones that cut deepest. They'll be the ones that build smartest. IBM just showed their hand.