As AI evolves, the world of work is getting even better for the most creative, curious, and growth-minded employees. So says Aneesh Raman, LinkedIn’s chief economic opportunity officer. Raman has intriguing and urgent insights on why the career ladder is disappearing—and how AI will help transform it into more of a climbing wall, with a unique path for each of us. Learn which parts of the workforce Raman sees as most affected by AI, and why he remains “radically pro-human” as the very nature of work dramatically shifts.  This is an abridged transcript of an interview from Rapid Response, hosted by Bob Safian, the former editor-in-chief of Fast Company. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with today’s top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode. You wrote an opinion piece for The New York Times with a headline about the bottom rung of the career ladder breaking, and it went viral. Did that surprise you? I’ve been in the arena for moments of big change before—when I was with CNN, when I was with President Obama—so I have a sense of what it’s like when cultural conversations start to take hold. With this one, I didn’t know what exactly was going to happen. I did an op-ed in The New York Times last year, and that one—it percolated here or there, but it wasn’t like this one. Aneesh Raman [Photo: Courtesy of the subject] And so this one really hit, I think, an underlying tension that we’re all feeling that something big is underway. That it isn’t playing out cleanly, quickly, everywhere all at once. It’s not like the pandemic, where we all just know what’s happening and then our life changes overnight, but that it is coming to us eventually. And evidently, entry-level work is the place where we’re all able to focus first, as a place where something real and big is happening. And that’s what I’ve been encouraged by. Because a lot of what I wrote this op-ed for was to provoke the conversations about AI and work, which is: “What do we do about this, and how do we get to better?” And there’s speculation about where AI hits the workforce hardest. The CEO of Anthropic has pointed to white-collar jobs. You’re talking about entry-level tasks. Are those two different scenarios based on different assumptions, or is it two parts of the same thing? The thing I can say with certainty is that this will affect every worker, in every company, in every sector, in every society. When it impacts every worker in every company, I don’t know. It’ll depend on where you work, what you do, but it’s going to hit everyone. And it’s going to hit everyone in a way that can lead to better for everyone, which I know we’ll talk about. What I don’t think anyone can do right now is in any absolute way predict net employment. We don’t know so much of what’s about to hit, and so much of where it goes depends on what we do as humans right now to shape this new economy as it forms. So we know historically, jobs have been disrupted, and new jobs have been created, every time we’ve gone into a new economy. It’s unclear to me whether we’ll see more jobs changing than new jobs emerging, and it’s going to take a bit for us to figure that out. But what we know is happening right now is that everyone’s job is changing on them, even if they are not changing jobs. And that’s where we should be focused. And the data about roles that you see on LinkedIn’s platform, the overall jobs numbers that come from the government, are fairly solid. How fast is this change happening? Are companies already hiring fewer, newer grads, or do we not quite know yet? Everything’s happening and everything’s not happening, because there’s no, again, universal way. It’s not an either/or situation. So I think a lot of what we’ve got to push beyond is this: Are entry-level jobs going away? Are they going to stay? It’s neither. It’s both. It’s yes. So when I think about entering a new economy and I look back across economic anthropology and economic history, there are generally four phases. The first phase is disruption. This new technology becomes real. And this is, I think, a technology equivalent to general-purpose technologies like the steam engine, like electricity, like the internet. We’re in that zone. So we already know that’s happening. Any number of metrics of people using AI at work, we’ve got data. Nearly 90% of C-suite leaders globally say, “AI adoption is a top priority for 2025.” So this technology is here, and it’s in the day-to-day. Now, the second thing that happens when you enter a new economy is that jobs change. And a lot of what I looked at early on with AI is: “Is AI going to be more like electricity or like the internet?” And the reason I ask that is that electricity changed everything for everyone, but it actually didn’t change much for humans at w