Insights from the CEO

In a recent interview, Matt Garman, CEO of Amazon Web Services, pointed out that the number one skill to succeed in the age of AI is critical thinking (I’d go even further: the future of our society may very well hinge on our collective ability to master this skill, but that’s a conversation for another time).

Meanwhile, in a different discussion on The Diary of a CEO podcast with Steven Bartlett, Geoffrey Hinton, the so-called “godfather of AI”, was asked which profession young people should pursue to secure their future. His answer? “Plumber.”

From engineering to plumbing: it’s hard to imagine a sharper contrast, but their answers perfectly capture the turbulence shaping today’s job market.

For young people choosing a career, the spectrum is striking. On one end, there’s the choice of trades: plumbers, electricians, carpenters, and other manual roles that appear relatively insulated from the AI revolution. On the other end, students may take on significant debt for a university degree only to find that lawyers now compete with AI models capable of passing the bar exam, while engineers are in demand only if they can meet the narrow, fiercely competitive requirements of AI development itself.

Healthcare might seem like the last truly AI-resistant sector. Doctors, nurses, and caregivers are professions where human presence remains essential. But realistically, not everyone can (or should) become a doctor or a nurse.

A recent Stanford University survey underscores the disruption: “entry-level workers in occupations most exposed to AI saw a 6% decline in employment between late 2022 and mid-2025, while older workers in the same fields experienced 6% to 9% growth”. In other words, the impact is uneven.

The steepest declines are concentrated among young, entry-level workers: the very people whose skills are most easily automated. By contrast, seasoned professionals benefit from the fact that experience and context are much harder to replace. The study highlights a “13% relative drop in employment for early-career workers in AI-exposed jobs since generative AI tools took off”, while employment for more experienced workers in those same roles has held steady or even grown.

This reveals a profound risk: we are undermining the pipeline of talent needed to carry knowledge forward. It’s true that an AI system often performs better than a brand-new employee, especially in the early months when young workers are still being trained, not just in their tasks, but also in company culture. But this perspective is dangerously short-sighted. Without younger employees to learn, grow, and inherit institutional know-how, who will carry it into the future?

Too many companies are fixated solely on efficiency and cost reduction, overlooking the bigger picture. AI will soon make optimization and productivity gains a commodity. The real differentiator will not be cost savings, but the workforce’s ability to master those “hard-to-codify” skills like collaboration, adaptability, judgment, empathy, that allow humans to use AI as a tool, not as a crutch.

In short, the future won’t be defined by who can optimize tasks the fastest. It will belong to those who can pair the raw power of AI with the uniquely human strengths we call soft skills.

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