Go To College, Get A Job: Really?

Picture this: you've just landed your first "serious" job. You're excited, a little nervous, and ready to prove yourself. Day one, you expect to do the classic newbie stuff—drafting simple reports, crunching basic numbers, maybe putting together a PowerPoint no one will actually finish reading. But instead of being handed your first task, your manager waves you over to meet your new teammate: an AI tool that's already done it all. That report? Finished. Those numbers? Analyzed. That PowerPoint? It's in your inbox. Suddenly, there's no "getting your feet wet"—you're expected to swim laps.

That's the kind of workplace shift described in The Expertise Upheaval, a 2025 report from the Burning Glass Institute. It's all about how AI is changing the way people learn on the job. Spoiler: it's not just about robots "taking jobs" – it's about the weird ways AI is speeding up some career paths while blocking the usual entry routes for others.

The researchers split careers into two main groups. First, the "Growth Roles." These are jobs like junior lawyers, project coordinators, and marketing assistants—roles where you start off doing straightforward stuff and gradually move into more complex, higher-paid work. Think: a junior lawyer begins by summarizing case files before moving on to actually arguing cases. Or a marketing assistant might start by scheduling social media posts before eventually running full campaigns.

Here's the catch: AI is really good at that "starter" work. If you're a junior lawyer, AI can scan hundreds of cases and draft a legal brief before you've finished your coffee. If you're a marketing assistant, AI can whip up a month's worth of Instagram captions in seconds. That means companies might skip hiring beginners and just bring in people who can handle the tricky, high-level stuff immediately. Translation: getting your first break in these jobs could be a lot harder.

Then there are the "Mastery Roles." These are more technical gigs—data analysts, network administrators, certain engineering jobs—where the hard part is learning a big chunk of skills right at the start. Once you're in, the work doesn't change as much over time. Here, AI is your sidekick. It can teach you faster, help you debug your code, or walk you through complex processes step by step. For example, a beginner data analyst might have needed months to get good at SQL, but now AI can generate and explain queries in minutes.

So what does this mean if you're still in school? For jobs in Growth Roles, you'll need to show up ready to contribute at a higher level right away. That could mean internships where you shadow experts, building your own projects, or even running a small business on the side to prove you can handle responsibility. For Mastery Roles, AI might help you skip some of the long, painful training—but you'll still need curiosity and discipline to keep learning once you get there.

And here's the thing: it's not about avoiding AI-heavy careers. Good luck with that—AI is everywhere. It's about knowing whether the career you want is a “slow climb" type (where the first rungs might be missing) or a "steep start" type (where AI can give you a boost).

The career ladder isn't broken—it just looks different now. Some parts are missing steps, others have built-in escalators. The trick is figuring out which one you're standing on... and being ready to climb, jump, or ride as needed.