LinkedIn's Aneesh Raman says the career ladder is disappearing in the AI era

Fast Company

a day ago

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.
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.
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 work. We still largely did physical labor. We just did it in the factory rather than the farm.
The internet came, and it fundamentally started to change work for humans. Suddenly, it wasn't just physical labor but intellectual labor that became valued by our economy. So the first thing I was looking at is, 'Okay, disruption's here. Jobs are going to change. How are they going to change?'
A new economy's on the way that I'm calling the innovation economy. Because our core skills as humans, the things that differentiate our species—the ability to imagine, to invent, to communicate complex ideas, to organize around complex ideas—those are going to come to the center of work. And that's a whole new set of skills that our economy has never fully valued. In fact, we've derided those skills often as soft skills or people skills that are nice to have, not must-haves.
So we're already starting to see in our data that communication is, like, the number one skill across job postings, not coding. All the jobs on the rise, aside from just general AI fluency or deep AI knowledge—if you're going for that small set of jobs explicitly about building AI—are all things like critical thinking, strategic thinking, closing that deal as a salesperson, persuasion, storytelling. So we're already seeing that jobs are going to shift; they're going to shift more to unique human capability.
And then the fourth phase will come where we'll see a new economy emerge. And part of what I'm waiting for, and I don't think we have these signals yet, is new job titles. Mine got made up eight to nine months ago. Moderna's got a new chief digital and people officer that they've created. New roles will emerge that aren't just AI, because we're seeing head of AI jobs have gone up, I think, three times in five years. But also new business starts, like a whole new era of innovation that's going to happen through these tools.
So there are some signals I'm waiting for. A different organizational workflow, like org charts become work charts. You have project-based work. There are a bunch of signals we'll start to see over the next year or two that start to suggest where and how the new economy is taking hold.
You looked historically at electricity and the internet, and it sounds like you're saying it's more like the internet. But it's also going to be something completely different that we don't even really know yet what it is.
Well, we know that whatever the role of humans at work is, it's going to be more human than work has ever been. And what's really important about that is . . . I always start with, 'Well, let's evaluate the status quo we've got before we A, get afraid of changing it, or B, want to imagine what it should become.' Work has never been human-centric, ever. The story of work is the story of technology at work, not humans at work.