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Fast Company
5 days ago
- Business
- Fast Company
LinkedIn's Aneesh Raman says the career ladder is disappearing in the AI era
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.
Fast Company
01-07-2025
- Business
- Fast Company
Yahoo CEO Jim Lanzone talks AI, reinvention, and reclaiming relevance
Yahoo is at a critical inflection point. Despite having a large user base—across Yahoo Finance, Yahoo Sports, and Yahoo News—the media company hasn't reclaimed the buzz of its early days. CEO Jim Lanzone candidly discusses the fear of being 'left behind' and how he's pushing the brand to shed its old skin. He explains the wide-ranging implications as AI remakes search engines into answer engines and shares insights about the line between fantasy sports and gambling. This is an abridged transcript of an interview from Rapid Response, hosted by the former editor-in-chief of Fast Company Bob Safian. 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. I wanted to ask you, you talk about it like Yahoo is sort of in a turnaround or a restart. But I mean, Yahoo News is the number-one news site on the internet, right? Yahoo Finance is the number one. Your fantasy sports platform is huge. You've got a big ad tech business, which I'm sure you talk about here. Second-largest email platform. You've got search, not Google-size search, but still substantial . . . All that sounds pretty robust. Yeah. Amazing ingredients with which to do a turnaround. So the way I would think about it is that absolutely the brands are still extremely relevant and they've had very loyal user bases. As a business, I think a lot of people know, but some maybe don't, that we were spun out of Verizon. Over the years, Yahoo was a stand-alone public company. It was acquired by Verizon in the mid-2010s. They also acquired AOL, which we also own and is one of our brands. And we were acquired for about $5 billion. So if you think about the other brands in and around our rankings in the traffic rankings, they're all trillion dollar brands. And so we had something to work with in terms of the size and loyalty of some of the audiences. But in some cases, email's one of them. We had a big announcement last week. The core product hadn't been improved in over 10 years. And so in the last nine months, every product that we operate has been relaunched with brand-new versions. And so taking advantage of the size of that audience to rebuild the business to be super valuable is the more turnaround side of it. And when you look at something that is robust, like the fantasy sports, as the NFL season comes, which will be your next big burst, right? We actually have a lot planned for it this year. I was curious, how much of the goal is to use this opportunity to introduce those users to other things you have, versus give them new things around what they already are coming for? I mean, what you'll find is that our individual brands have in some ways different audiences. People who really use Yahoo Finance as their way to make more money and save more money and attract stocks and all that is pretty independent of people who love fantasy or love checking sports scores with Yahoo Sports. I definitely think the secret sauce of Yahoo, especially for advertisers, since we're here, is that, collectively, it's hundreds of millions of people who have a first-party relationship with us, which makes our ad targeting extremely effective. So one Yahoo overall is something that actually is true about the actual business. Getting people to use Yahoo as one point for everything is something that will happen over time, but we're not going top-down in how we go about it. But it sounds like you don't necessarily, at least right now, need to convert people into being like, 'I'm a Yahoo, and I do everything in the Yahoo world.' I think that was the '90s Yahoo, and I think the internet kind of moved past that. That said, we did relaunch the Yahoo homepage in February after months of testing different variations of it because the user base gets pretty locked in with how they do things, and you can really mess it up in the link chain if you change something. So we found one that really worked, and the most interesting thing about it was we went back to adding more portal-like features. Over the years, it'd become kind of just a newsfeed, and we added things back that were more utility-based around weather and other things and found that people love that. So actually, the Yahoo homepage that is more of a place to get things done is probably more the direction we'll head with it than just straight news. Not everything about the way the internet was framed in the beginning was wrong. Right? It's interesting because having competed against the people at Yahoo for the first 20-plus years of my career and taking that eye towards it, working here, you do kind of get an appreciation for how . . . If you go back and look at the 2007 version of the homepage or 2003, there was some magic to that and how it all worked, especially with the way the internet has gone with a lot of slop and misinformation, disinformation, clickbait, and people trying to get you to do things. The fact that it kind of had everything in one place, I don't know, it was maybe taken for granted a little bit. So we actually have taken some inspiration from that. Obviously we try to modernize it. But yeah, we've taken some inspiration from it. So with the generative AI wave, media is changing like crazy. As search engines like Google become more of an answer engine as opposed to a search engine, sites like a lot of yours may see some of their referral traffic decline. At the same time, you have a search business yourselves. And if you follow where that is going to become more of an answer engine, you may encourage the development in that direction in people's habits, which could undercut the other part of your business. I'm just curious how you think about those pieces fitting together. Yeah. And I spent the first 10 years of my career in search, and a lot of what we did back in the day was absolutely moving things towards an answer engine. And so I would say that's not really new. What people know as Google OneBox, a lot of the search engines in the early 2000s were doing, already brought answers like the weather or music lyrics or multimedia or translations directly into the page. So this has always been the case. Now, there are certain kinds of queries called navigational queries. Those are trying to get you directly to a website. I do find it interesting that a lot of the generative . . . A lot of the large language models, they're getting a lot of their traffic and sending it to places that are more canonical. So for ChatGPT, 50% of their citations are Wikipedia. For Perplexity, almost 50% are Reddit. And so those are more evergreen, deeper, almost more educational responses. A lot of Yahoo's content is real-time, stock prices, sports scores. So for us personally, we operate in a kind of a different space. But you don't expect that referral traffic to decline? So a couple things. So one is I actually strongly believe that the role of search is not to take traffic from the open web, but to send traffic. And in our case, Yahoo's been doing that for over two decades. We have relationships with all of our publishers where we share revenue, we send traffic downstream. And so I actually think that's part of what Yahoo's always done really well is help create a healthy ecosystem. That was also part of the bargain of the open web for search, that you would make yourself available to the engine that would then send you traffic downstream. Having that traffic get cut off and just subsuming that data to then keep it for yourself was not part of that grand bargain. I think we're in the early days of figuring out how that's going to go. What I actually think will happen in search over time, because I think we're still in the primordial phase here of what AI versions of search will look like, is that the page will respond to your query and to what the search engine knows about you personally to have a different version of the search results page depending on the query type and depending on you. And so you're never going to get the same kind of response to each one of these. I personally really believe that it should ultimately wind up sending traffic downstream to the sources, and little citation links probably are not going to do that.
