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    Home»Business»LinkedIn’s chief economic opportunity officer on how to get ahead in the age of AI
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    LinkedIn’s chief economic opportunity officer on how to get ahead in the age of AI

    April 14, 20264 Mins Read
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    Many tech observers initially believed the software engineers would become scarce in the face of AI. But that hasn’t turned out to be the case—in part due to the power of human ingenuity.

    “Software engineers are spending less time coding,” says Aneesh Raman, the chief economic opportunity officer at LinkedIn, who just published the book Open to Work: How to Get Ahead in the Age of AI. “But now they’re getting to build things in a way they couldn’t before. They’re going into conversations with clients and customers. Or they’re thinking about the ethical implications of what they build.” 

    In their book, Raman and his coauthor—LinkedIn CEO Ryan Roslansky—argue that there’s no point trying to beat AI at its own game and “out-machine” a machine. Instead, workers who are concerned about being unseated by AI should focus on what they bring to the table that cannot be automated. 

    “One of the biggest arguments we make in the book is: Jobs are not titles,” he says. “They’re a set of tasks.” Raman sorts those tasks into three buckets. One of those buckets includes the tasks you can automate or simplify with AI; the second bucket might be new things you can do by harnessing AI. But the most crucial bucket is the last one, which involves what is “unique to you as a human.” 

    “No one beats you at being you,” Raman says. “Not even AI.”

    It is these skills that have currency in the era of AI, according to Raman. Soft skills, which are often undervalued, have new relevance as AI erodes the value of technical prowess. “For generations now, we have valued technical and analytic abilities above all else,” he says. “And we have described these people skills—these human skills—as soft in a very dismissive way. The script is about to flip.”

    In their book, Raman and Roslansky sought to better articulate what constitutes soft skills, enlisting neuroscientists, psychologists, and behavioral economists to do so. They came up with the five C’s (curiosity, compassion, creativity, communication, and courage) to capture the qualities that AI “can help us with but can’t beat us at.” 

    Raman also wants to reframe these attributes as skills that you can actually improve over time, rather than fixed or innate traits. “Part of the issue with how we thought about these skills isn’t just that we’ve said they’re soft,” he says. “We also said a lot of these are talents, not skills—creativity being a good example. You can get better at any of these five C’s. You just have to do it every day. And be uncomfortable.”

    The doomsday narrative of AI has focused heavily on the toll for white-collar workers and especially recently college graduates. While all kinds of workers are at risk of automation, including those who lack four-year degrees, Raman believes college graduates are in a better position than media coverage might lead them to believe. 

    “If you’re coming out of college, every headline is telling you this is horrible for you right now,” he says. “Start with strengths. You’re coming out of college probably the most fluent with AI of any generation. You’ve had it for your entire four years in college. You’re also coming out of college with a more entrepreneurial mindset. You know about the gig economy, the side hustle, the creator economy. You don’t believe you’re going to get one job at one company, and then that’s going to be it. Those are the two most important skills for anyone right now: AI fluency and entrepreneurialism.”

    In fact, it’s not college graduates who he thinks are most vulnerable at this moment. He points to people in his peer group—the generation of workers that relied on traditional paths to success, be it a college degree or rising through the ranks at one company. “The people I’m most worried about are people that have never failed, have never had to adapt, have never had to manage ambiguity,” he says. 

    As plenty of economists have asserted, nobody knows exactly what the future holds. With his book, Raman hopes that he might help puncture the sense of fatalism and inevitability that has consumed discussions of how AI will reshape the workforce. 

    “Nothing about this is predetermined,” he says. “Let go of what’s happening around you. Don’t look for CEOs to have the answers, for AI to have the answers, for headlines to have the answers. Focus on what you can control.”



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