Like most of you, I spend a lot of time thinking, and sometimes worrying, about the future. The World Economic Forum projects that by 2030, technological change will displace approximately 92 million jobs while creating 170 million new ones, resulting in a net gain of 78 million jobs globally.1 The years between disruption and recovery is what the next generation will live through in real time.
So what do I actually want young people to know? Here’s the best advice I can give.
The skills worth building aren't the ones that compete with software. They're the ones that software reveals as important. That's the frame I keep coming back to, and it changes how you spend your time when you're first starting out. Let’s get into it.
Curiosity beats credentials
Many companies have dropped college degree requirements for some of their open roles. LinkedIn's newer Skills Signal Report (2025)2 includes these findings:
- Workers matched by skills rather than job titles qualify for more than three times as many roles.
- Companies using skills-based talent searches are 12% more likely to make high-quality hires.
- Employers can expand their AI talent pool by 8.2X by focusing on skills instead of degrees or job titles.
The hiring data doesn't tell you that AI can retrieve and summarize nearly any fact in existence, but it can’t want to understand something. The people who will be most valuable in a skills-based, AI-augmented workplace aren't the ones who know the most. They're the ones who can't stop asking why. That genuine intellectual curiosity is still entirely, stubbornly human. Feed it.
Relationships compound
Decades of research have consistently shown that customer retention is one of the strongest drivers of long-term profitability. A 2023 meta-analysis reviewing 40 years of evidence confirmed that higher customer satisfaction and loyalty are consistently associated with stronger financial performance.3 The relationship isn't soft, it's structural. Every industry worth being in runs on it.
AI can have a smooth, helpful conversation, but it can’t build the kind of trust that comes from showing up for someone over years, knowing their business, and calling them when things go sideways. In insurance, the single biggest driver of customer retention after a claim isn't the speed of the payout. It's whether the person on the other end of the phone made them feel like someone was actually there. Every real relationship you invest in is an asset that appreciates. Start early.
Learn to ask better questions
Research from MIT Sloan and Harvard Business School4 found that AI significantly improved worker performance when people knew how to integrate it into their workflow. Conversely, performance declined when users relied on AI outside its areas of competence, highlighting that human judgment remains essential. Workers who over-relied on AI without strong judgment behind it saw their performance decline on tasks outside the AI's capability.
The leverage is in knowing what to ask, when to push back on the output, and when to trust your own read over the model's. That takes judgment, context, and genuine understanding of the problem, none of which the AI has. The most valuable skill in an AI-augmented workplace isn't knowing how to use the tool. It's directing it with judgement.
Don't skip the hard stuff
Research from cognitive science calls it "desirable difficulty." Struggling through something hard, rather than taking the easier path, is what actually builds durable skill. The friction isn't the obstacle, it's the point.
There's a real temptation right now to let AI handle everything uncomfortable, like the difficult email, the messy analysis, the first draft you're not sure about. Sure, AI will get it done quickly. The people who grow fastest are the ones who stay in contact with the hard parts of their work, where judgment gets built. You can't outsource your way to it.
Your taste matters
By some estimates, AI is already responsible for a significant share of online content. The volume problem is solved, but it’s clear to see the quality often leaves plenty of room for improvement.
AI produces a lot of output, but it can’t care whether that output is excellent. Develop the ability to recognize what's good. Whether it’s good work, good thinking, or good character in other people. That gap, between volume and quality, is where creative people and thoughtful people will matter more than ever. It may be the most underrated skill of the next decade.
What's left for you
The machines are getting better at the predictable. Which means what's left for you is everything that isn't.
The point of building all of this was never to replace human beings. It was to give them back their time. To let them do the parts of the work that actually deserve their attention.
For everyone who's just starting out: that's not a threat. If you know what to build, it's a pretty good deal.
Sources:
- https://www.businessinsider.com/wef-sees-4-ai-futures-for-jobs-by-2030-only-one-limits-disruption-2026-1
- https://delivery-p143253-e1476319.adobeaemcloud.com/adobe/assets/urn:aaid:aem:5b3b5344-a0b1-4447-bcc9-ba1d7c4baf09/original/as/original.pdf
- https://repository.rice.edu/items/3a311975-b9e7-49a6-bf0f-3997a2bfcdd2
- https://mitsloan.mit.edu/ideas-made-to-matter/how-generative-ai-can-boost-highly-skilled-workers-productivity
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