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Below, Aneesh Raman and Ryan Roslansky share five key insights from their new book, Open to Work: How to Get Ahead in the Age of AI<\/em>.<\/p>\n Raman is LinkedIn\u2019s chief economic opportunity officer. He previously served as senior adviser on economic strategy to the state of California and led economic impact at Facebook. Roslansky, who is CEO of LinkedIn, is also EVP of Microsoft Office and Copilot. <\/p>\n AI\u2019s impact on work is unfolding in real time\u2014rapidly\u2014and individuals have more agency than they think. By understanding how skills, roles, and industries are evolving, anyone can actively shape their career and stay ahead in the age of AI.<\/p>\n Listen to the audio version of this Book Bite\u2014read by Raman\u2014in the Next Big Idea app<\/a>, or buy the book<\/a>.<\/p>\n Most of us define ourselves and what we do based on our job titles: I\u2019m an accountant, I\u2019m a nurse, I\u2019m a marketer, or I\u2019m an engineer. And it makes sense, given that for decades our titles told our companies where to put us. But titles are not the most useful way to think about work anymore because AI is not coming for titles, it\u2019s coming for tasks. When you start seeing your job not as a title but as a set of tasks, it makes it easier to understand what\u2019s changing and what to do about it.<\/p>\n Go grab a piece of paper. Now write down the top dozen tasks that take up most of your time at work. Not your job title, job description, or your goals. The actual things you do day-to-day. Then, sort all those tasks into three buckets:<\/p>\n Now, think of these three buckets like a conveyor belt: Bucket 1 tasks will increasingly disappear as AI gets more advanced. But as they do, new opportunities emerge in Bucket 2, allowing you to use AI to do things that weren\u2019t possible before. And as you master Bucket 2, you create space and ideas for deeper Bucket 3 work that no machine can touch.<\/p>\n Over time, success is about moving tasks across your buckets. Start deliberately moving tasks from Bucket 1 to Bucket 2 by adding human judgment to routine work. Start using AI tools in Bucket 2 to free up time for more Bucket 3 tasks. And start expanding your Bucket 3 capabilities, because that\u2019s where durable value lives.<\/p>\n It\u2019s not just about sorting tasks into buckets but developing the meta-skill of actively curating them over time. This is not a one-time exercise, but something you\u2019ll continue to work at as your job evolves.<\/p>\n Certain skills set us apart from AI, and we call them the 5Cs:<\/p>\n These skills are core to how we come up with new ideas and solutions. For decades, the 5Cs have been dismissed as soft skills, meaning \u201cnice-to-haves\u201d that took a back seat to the hard skills our economy valued most. In the coming years, it will become clear that soft skills are anything but soft. They are key to our survival at work.<\/p>\n Think about how these 5Cs show up in your own work today:<\/p>\n Don\u2019t think of these skills in isolation. As neuroscientist Vivienne Ming points out, \u201cThese aren\u2019t five separate items on a checklist. They feed each other. Curiosity without courage leads to inaction. Creativity without communication remains a private hobby. Compassion gives our work purpose.\u201d<\/p>\n While everyone\u2019s racing to out-code AI, you should be honing the things that AI can never replace. The 5Cs are your competitive edge.<\/p>\n The career ladder is a relic of the industrial age, and it\u2019s coming undone. For generations, the playbook was clear and unchanging: By and large, you joined a company after graduating from school, climbed steadily for decades, and retired with a pension and a gold watch. One path. One employer. One direction\u2014up.<\/p>\n But ladders only work when the world is stable. When skills last decades. When jobs stay the same. That world has been on the way out, but now AI is accelerating the pace. Professionals entering the workforce today will hold twice<\/em> as many jobs over their careers as those in the previous generation. The ladder doesn\u2019t work when your job changes faster than you can get promoted. Or when your industry shifts faster than you can figure out what to pivot into next.<\/p>\n So, think of your career path less like a ladder and more like a climbing wall. Multiple routes up. Sideways motions that build new skills. Sometimes, even going down to find stronger positions. The best climbers won\u2019t follow someone else\u2019s path: They\u2019ll design their own.<\/p>\n You\u2019re already on the wall, whether you realize it or not. To guide your climb, ask yourself three big questions:<\/p>\n The S curve of change is a helpful way to understand how big shifts, like new technologies or major trends, tend to unfold over time. At first, progress is slow and almost invisible\u2014that\u2019s the bottom of the S, and that\u2019s when most people feel comfortable ignoring it. Like the internet in 1993, social media in 2004, and AI in 2020. Then, momentum builds and adoption accelerates rapidly\u2014that\u2019s the steep middle of the S. Finally, growth levels off as the change becomes mainstream and widely accepted\u2014that\u2019s the top of the S.<\/p>\n AI isn\u2019t at the bottom of the S curve anymore. ChatGPT hit 100 million users faster than any technology in history. We\u2019re entering the steep part where adoption stops being optional. The question is: Are you engaging with this change as it starts to speed up?<\/p>\n Our brains are wired to fear change and not process exponential change. That\u2019s why managing S curves is so hard. And while we have had decades and years to manage past ones, we don\u2019t have as much time with AI. Change will never be this slow again. AI will never be this basic again. The time to experiment is now. Adapting beats predicting.<\/p>\n There are well over three billion people in the global workforce. More than a billion of them are on LinkedIn. Only one of them is you.<\/p>\n That might sound obvious, but it\u2019s easy to forget when you\u2019re at work, trying to fit in. We often spend our careers molding ourselves to job descriptions, industry standards, and the \u201cproven path.\u201d We\u2019re asked to demonstrate the right competencies to show we can do what others have already done. The entire machinery of work, from r\u00e9sum\u00e9s to reviews, is designed to make us comparable, categorizable, and measurable against others.<\/p>\n But when AI handles the standard, things start to flip. Suddenly, your differences become your competitive advantage. The specific combination of failures and triumphs that taught you resilience in ways no curriculum could capture. The childhood spent between cultures that lets you see patterns others miss. The decade you \u201cwasted\u201d in the wrong career that gave you insights no straight path could provide. The quirks in how you approach problems. The unconventional connections you make between ideas.<\/p>\n For your entire career, you\u2019ve probably been told to smooth over these edges to make yourself more marketable. In a world where AI can replicate the standard approach, those edges are going to make you irreplaceable.<\/p>\n Enjoy our full library of Book Bites\u2014read by the authors!\u2014in the Next Big Idea app<\/a><\/em>.<\/p>\n This article originally appeared<\/a> in <\/em>Next Big Idea Club magazine and is reprinted with permission.<\/em><\/p>\nWhat\u2019s the big idea?<\/h2>\n
1. Jobs are tasks, not titles.<\/h2>\n
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2. Soft skills are survival skills.<\/h2>\n
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3. Careers aren\u2019t ladders; they\u2019re climbing walls.<\/h2>\n
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4. Our brains aren\u2019t wired to handle exponential change.<\/h2>\n
5. Nobody beats you at being you.<\/h2>\n
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