LinkedIn VP Aneesh Raman on Why Adaptability Is the Skill of the Moment

MOLLY WOOD: Today, I’m having a great conversation with Aneesh Raman, vice president at LinkedIn and head of the company’s Opportunity Project, which focuses on building a more dynamic and equitable global labor market. He’s here to tell us one simple thing: jobs are changing all around you, even if you aren’t changing jobs. And this is a guy who knows a little something about changing jobs. He formerly worked as a CNN war correspondent, and a speechwriter for President Obama. He’s now focused on how tech innovations are transforming the way we work, but also how they’re creating and expanding opportunities for people without standard career paths and educational backgrounds. Here’s my conversation with Aneesh.

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MOLLY WOOD: So you have had a remarkable set of careers—journalist, author, speechwriter for the president, advisor to the governor of California, now an executive at LinkedIn. Has there been, could you say, a through line to all of these tasks and jobs? 

ANEESH RAMAN: Up until recently, it was hard for me to articulate a through line. And that was hard for me, just personally, because I found it hard to explain my career. It was a classic squiggly line career, but across every job, explanatory storytelling was core to what I did. That was true as a reporter, it was true as a speechwriter, it was true in all the roles I had in tech and with Governor Newsom—I am a storyteller. 

MOLLY WOOD: Well, a squiggly line is kind of an increasingly common career path. Let’s talk a little more about that—how much jobs really are changing, and how we should deal with that. 

ANEESH RAMAN: Yeah, I mean, I want to repeat it, because I want people to really hear it: jobs are changing on you, even if you’re not changing jobs. So here I am, this very extreme example of someone who has not just changed jobs but changed careers, from journalist to speechwriter to tech executive. And so it can be easy to say, well, that’s someone else. But everyone is a version of me, even if you don’t realize it, because the way the technology has changed, what we do at work has already had an impact. Twenty-five percent of the skills required to do jobs have changed over the past eight years, by our data. But 65 percent will change by 2030—65 percent of the skills required for a job will change by 2030. That’s basically a new job. 

MOLLY WOOD: Tell me what that means. Like, I’m doing a job right now, I think I know how to do it, and 65 percent of that is going to be totally different. 

ANEESH RAMAN: Yeah, in your day-to-day, think about just, you know, look back maybe a decade, how you’re using tools differently. How we started using email, and we started using the instant communication tools that weren’t there a decade ago. How that meant that what we needed to meet about was different. How businesses had to change to adapt to the internet age and e-commerce. So we have been in a state, really, since the internet age took hold, of constant change. Now, the speed of that change has been measured. And so we could feel it perhaps year over year, it felt kind of incremental, we could walk our way through the way our job was changing. I think AI is going to speed all that up. And so it means we’ve all got to be a lot more focused on how we’re going to do lifelong learning, how we’re going to keep track of what are the new and better tools we can be using? How we’re going to keep track of what are the ways we have to upskill?—ahead of where the business that we’re working at is going, or the team that we’re leading needs to go. And again, I just go back to skills-first, because it’s really the only way you can get your head around it. You can’t just cut and paste job descriptions if you’re a company, you can’t just wait to get your manager’s job if you’re an individual. Because all of this stuff that is underneath a job—the tasks are changing. And so the key takeaway, I think, for us all is just adaptability is the best way to have agency right now. I think in a moment of big change like we’re living through now, the thing we all most want is not just a way to understand it but a way to manage it. And at the core of that right now is just going to be building that muscle of adaptability. 

MOLLY WOOD: It sounds like you’re talking to everybody in an organization, without question, that this is going to have to be you know, bottom up, but I do wonder how you manage through that. As a business leader. 

ANEESH RAMAN: I think it starts with communication. I mean, people are really nervous right now. They’re really anxious right now. As I described, I now see myself as a storyteller, and I think storytelling is a must-do right now for everyone, to give a vision for where this technology is going to take your team or your company, and in a direction that includes the people you’ve got, and the support you’re going to give, to upskill the people you’ve got. So I think it’s really important for us all to bring that kind of energy to how we are communicating out to teams, because this is one of those moments, those early days of a big shift, where the story sets the tone, and the tone sets the direction, and over time, the direction becomes self-fulfilling and inevitable. And I think there are a lot of reasons for us all to be thoughtful about AI, to really think about intent as it’s built, to think about the responsibility that needs to be built into AI. But it’s important for us all to also see what’s possible because of AI. The aspirational other end of this, that we think of at LinkedIn as a world of work that’s more human, not less. Because people skills are going to come more to the center of individual career growth, and people-to-people collaboration is going to come into the center more for company growth. For leaders, you’ve got to start with communicating clearly, compassionately, and empathetically with your teams. And then I think it’s really building a culture of learning. That’s like the most important thing because there is no universal answer to where this is going. There’s no way to know, except to know where it’s going next. And so I go back to that adaptability is the best way to have agency. How are your teams talking about the latest AI tools? How are your teams learning together, growing together? How are you encouraging team members to think about tours of duty and skills transferability? All of those things are really important right now. 

MOLLY WOOD: Well, and a culture of learning is also a culture of training, and a culture of time and patience. Like, it seems to me that what we’re talking about in large part is a leadership structure that says, We want to help you develop these skills, as opposed to set an expectation that you will spend all your nights and weekends learning about this when you’re not on the job. And that could really change workdays, I would imagine. 

ANEESH RAMAN: Employers are going to become educators more and more. And the good news for employers is that—and employees—a lot of that is going to be on the job. One of the things I like to ask the audience at any panel I’m at is, to think about the job that they’re doing right now and raise their hand if more than half of what they do in their job is based on what they learned in college or the degree they got. And very few, if any, hands go up. Then I say, raise your hand if most of what you do in your job is stuff you learned on the job or in previous jobs, and almost every hand goes up. So the idea of learning on the job is not new. It’s going to get faster and more complicated now, but a lot of this is going to be just how in our day-to-day jobs we’re starting to upskill and learn—not something we do separate from work but within work. I’m a good example. I am someone who writes a lot, as my job. And I have been working with ChatGPT a lot to help me get through a first draft, to help me refine positioning, to debate with me what core themes are. That is now embedding into my workflow, and I’m getting really good at prompting. So that’s the kind of learning I think that companies want to encourage, and that people should feel excited about. Because, again, I really think AI will be a tool. And humans have built and perfected tools over millennia, to help us do more of what we love, and to help us do the work that we love to do better. 

MOLLY WOOD: Okay, talk to me more about debating. Tell me more about the prompts that get you to engage in a back and forth. Are you really doing that? It’s super cool. 

ANEESH RAMAN: Yeah, I mean, I did a post recently on LinkedIn about how I think philosophy, and the study of philosophy, is going to become this “it skill” across all these different areas of how AI is going to affect work, about social cohesion, ethics, lifelong learning, resilience. And as I was building that—you know, there are a bunch of different ways you could describe philosophy as relevant to the changes hitting work. And so I sort of did this starter, and I prompted it with assigning it who it was—you are a speechwriter helping me out. I am—described what I’m working on—thinking about a post that talks about philosophy and its role in the age of AI. Some notes, but really, I was trying to get to what do I think are the core themes, the core takeaways for people? And I had a couple. I asked it for ideas, it had a couple, some were good, some were not. And it was in that back-and-forth that I was able to really articulate these different ways that I think the study of philosophy will help us. That’s just one example. As you think about any sort of content you’re doing, any sort of meeting that you’re leading, any sort of moment where you are trying to inspire new thought—a lot of that work is really hard at the front end, because you’re taking this kind of abstract idea and trying to get it to paper. And I have found that AI is helping me speed up that front process so I can spend more time on the stuff I love most and that I think I am, as a human, best positioned to do. 

MOLLY WOOD: You have talked about how it’s important to think about skills as kind of naturally dividing into three buckets. Can you tell us—you’ve given us some examples, but can you tell us more about what those buckets are? 

ANEESH RAMAN: Yeah, I think, you know, for me to come up here and say, AI is a big deal, which I think it is, and that it’s going to change, you know, how we work and how we live—it’s going to change how we work and how we live in different ways based on your sector or function. That’s like a lot to manage. It’s a really complex, nuanced moment of big change. So I like to also offer up what I think is the best way to feel some agency, something actionable in managing that, and I think that is skills. And here’s why. Probably the biggest impact of AI on work is that I think it’s going to force us to redefine jobs—not as titles, but as a set of tasks. So if you take your job, and you put aside your title, and you think about, let’s say, the top dozen tasks that you do on any given day—what you can do now is break those tasks into three buckets. The first is, tasks that AI is ready to do almost fully for you: summarizing meeting notes, even writing code in some instances. The second bucket are tasks that you’re going to do with AI, and prompting is the best example of that. And then the third are tasks that require your unique skills, your people skills, creativity, collaboration. So everyone can do that math. And if your job or your team or your workforce is heavy on that first or second bucket, that’s a good indication that it’s time to upskill. And then everyone should be thinking about that third bucket, where we have the most competitive skill set, which is the people skills. So again, like, you could break jobs into tasks, and then with a skills-first mindset, we can all—starting today—know where we’re at and what we need to do to feel agency right now. 

MOLLY WOOD: There has been, kind of, talk of skills-based hiring and, you know, skills-based management for a long time. And it’s been very—it’s hard to implement, it is actually you know… It’s so obvious and necessary, and it opens a ton of doors for a ton of different kinds of employees. And it is sort of anathema to how companies operate right now. Talk to me about the level of change that this will require in the adaptability in companies. 

ANEESH RAMAN: So the first thing I always concede about skills is that it does feel early. It feels hard to scale. It feels hard to define. It is not as easy to filter for skills as you filter for degrees. But I promise everyone that it is easier than any other way that exists to figure out what is going to happen to work, to your job, to your team in the age of AI, and how you can take advantage of the opportunities that are emerging. Winston Churchill has this quote about democracy that basically says, democracy is the worst, except for everything else. Name me any way that we currently judge potential in people that isn’t skills first, and I’ll show you how it’s either broken or going to break over time. Those ways may be easy now, because the systems exist around them. But they’re not going to be effective going forward. And so then I think, as a company, you have two choices: to sort of ignore that reality and to stay focused on systems that are easy now, or to do the work now to test and learn and build the systems around skills first that make you an adaptive company with an adaptive workforce later. And the big reason for hope that didn’t exist before out in the broader conversation is that, while AI is an accelerant for why people have to think in a skills-first way, it is also going to be a tool that helps us build the systems around skills first. It helps us build taxonomies to connect to job descriptions that are linked to LinkedIn profiles and the skills people have in ways that are dynamic and that are keeping track of trends across the labor market. That’s what’s held skills-first thinking back, is the human need to do all of that. And now we’ve got a tool to build those systems. But it’s really, to me, the only way forward. 

MOLLY WOOD: I mean, I think we’re all going to have to learn how to devise the ideal prompts to get the most out of AI. But actually, Jared Spataro, Microsoft’s Corporate Vice President of Modern Work and Business Applications, has suggested that there is crossover between people who are good at prompting and doing all the setup and preparation and context setting and information sharing that you’re describing, and people who are also good managers. 

ANEESH RAMAN: And I also think the people part of managing is going to become more and more important, because a lot of what it is to manage that the tools and that AI could help us now do in terms of tracking budgets, and making sure priorities are aligned, and all these things that we might be able to now through a tool be able to have visibility on and track against. It’s going to then open up the space and open up the need for managers to be focused on the people part of managing, and that goes to the people skills that I really think are going to come to the center of the labor market—empathy, collaboration, listening, and leading by listening. 

MOLLY WOOD: You know, there’s obviously a lot of demand for AI experience and people who are good at prompting. But LinkedIn’s June 2023 executive confidence index shows that 72 percent of US executives agree that soft skills are even more valuable than those AI skills. And I think by soft skills, we mean what’s traditionally been called people skills, right? Communication, creativity, adaptability. Why do you think those skills are so valuable now? And how do you teach that?

ANEESH RAMAN: Soft skills have always been core skills. Because they are skills we uniquely do as humans. If you think back millennia, not just centuries, and two or more people doing something together—buying or selling, investing, building, hiring, executing—it’s all that happened before technology around that. How did I build a relationship with you, talk about the product I have in a way that was something you wanted to buy? How do I collaborate? How do I empathize with where you’re at, so when I communicate with you it’s something that lands with you and isn’t just me talking over you or at you—all of those things. What’s interesting is that over the past few decades, because of the internet age, when we think about workforce development, so much effort has been, understandably, on technical skills, computer science degrees, coding boot camps, educated and credentialed—technical skills. We now, I think, you’re going to have to do that for soft skills. And that is a big new challenge for us, in terms of workforce development. Again, I think AI will help—help define soft skills in an aggregate way. Help us do credentialing based on contextualizing skills, like I do on my profile. Millions of skills are getting added every year on LinkedIn profiles, where members are saying, these are the skills I used to do this work. What does it mean to communicate? And where did you do it that led to a deliverable that you can show? At one level, I think you’ll see a little bit of a recalibration where all of this funding and energy went to the engineering departments on college campuses, I think the humanities will have a bit of a renaissance. But also, again, the shelf life of a degree is shrinking pretty dramatically. So, how soft skills are applied to this changing world of work is going to change. And I think that’s going to mean workforce development, not just going into college, but after college and across your career, it’s going to have to account for soft skills now as a core skill for us to identify and credential. 

MOLLY WOOD: I love this idea. I think, you know, it’s particularly a conversation when you talk about, for example, women coming back into the workforce, or hiring veterans, or just more equitable hiring overall. You are, I should say, speaking as someone who is a Harvard grad and a Fulbright scholar, and it sounds like you’re kind of saying you want the importance of those titles to fade into the background over time. 

ANEESH RAMAN: Well, I would say I would like them to be less relevant to how I succeed or how anyone succeeds in their career. Because I think they are not in and of themselves an issue, but representations of a labor market that has really required pedigree signals to get ahead. And we know that pedigree signals often come from privilege. What I am excited about with skills-first thinking is that we can finally put an objective dataset underneath the labor market so that people match talent and opportunity in a more efficient and equitable way. If you look at the history of work, for most of human history you inherited work, you did what your parents did. That’s wildly inefficient and unequal. Then you had these industrial revolutions, and they opened up new opportunities for work. And over time, college especially, but higher ed and education generally was meant to be the mechanism of mobility. No matter what station I was born into, I could learn my way into new and better jobs. That model has had a bunch of challenges hit it over time, not just least of which is the cost of college, but also the way that curriculum is developed. It’s really hard to tether that to the changing dynamics of work, to make sure that as you develop curriculum, when you’re done, it’s still relevant to where work is and is going. And all of that means I think that we’ve got this opportunity now to take the guesswork out of work, to put skills at the base of it. And with that, college will still be an important credential, but create other ways, other credentials for people to come into and across the labor market. And to really, you know, challenge some of these baked-in inequities, the gender inequities in the labor market, a lot of the roles that have the people skills associated with them are often undervalued and underpaid, because we have focused so much of value around the technical skills. I think that’s going to shift. If you look at home healthcare workers, as an example, a profession that is a very high-skilled profession that we will start to, I think, better describe as high-skilled. So I think there’s a great equalizing effect, a great democratization of economic opportunity that’s about to happen, spurred by the age of AI. 

MOLLY WOOD: Let it be. Lord, let it be. [Laughter] We tend to have these conversations anytime a new technology comes along, that’s going to enable greater efficiency, but it feels really transformative now to be talking about these skills in such a different way. 

ANEESH RAMAN: Well, as a storyteller, my first reaction is, we can’t just say, let it be, we have to say, make it be. And I think right now, the story really matters. Our ability to articulate a vision for AI that will democratize access to economic opportunity will make it more likely that the people who are around the systems of workforce development start to align it in that direction. But I’ll take you even one step further than just equalizing opportunity in the labor market, in terms of how I see the potential for AI. You know, a lot of the discussion about AI has been on how it will help reduce the drudgery of our day, the repetitive tasks we do that are not fun. But I think some of the most powerful impacts of AI will come in reducing the barriers in how we communicate with each other. One of the most important skills in the world is communicating to someone else in a way that isn’t just about you talking at them with a focus on what you’re saying, but talking with them with a focus on what they’re hearing. That is tremendously difficult to do. Because it requires understanding where the other person is at, and bringing empathy to how you communicate. That becomes impossibly difficult to do as you think about divides across geography and culture and language and sector and function and market. All of these barriers have existed for some time now that make it really difficult to talk human to human. And I think AI is going to help us all get better at that. It’s going to help us, in real time, break down those barriers to communication that I think will lead to higher quality conversations and more meaningful collaborations. What’s exciting to me about that is that if we’re able to do that in the world of work, it’s pretty easy to see how that can extend out into society, and into a world where we are bringing greater humanity into how we all live. And that’s my real hope here. And I think it’s important to say that that’s not inevitable. And that that will require us being really deliberate with the intent of AI that is being built and the responsibility that we have to build into it. But that it’s also possible. And if we can believe it’s possible, it’s amazing the degree to which that can affect how we approach the early days of this big shift, and how that can actually make it much more likely that that’s where things end up. 

MOLLY WOOD: Yeah, I hope so too. Okay, well, before I let you go, let me bring this back to you. You are using AI a lot. So how is it saving you time? And what are you doing with the time it saves you?

ANEESH RAMAN: The time I am saving with AI in terms of the tasks I would be doing if I didn’t have AI—which are generally that first draft, first cut first outline—I’m now able to spend a lot more time on the creative part of how do you perfect the language? And how do I think about how it sounds when I’m saying it out loud? And I find that really enjoyable. Because I found, and I’ve always found, the first draft, the first outline, the first how do I take an idea and start to think about the logic flow? necessary but not fun. And I, you know, would have feared if I told you that there was something that would help me with that, that maybe I’d lose something in terms of, you have to slog your way through that. And that’s how you get to the fun of the creative crafting. But no, that’s not what happens. You actually just get to dive right into the fun. 

MOLLY WOOD: Aneesh Raman, vice president at LinkedIn and head of the company’s Opportunity Project—the guy who’s going to make it be. Thank you so much for the time. 

ANEESH RAMAN: Make it be with you and everyone else. Thanks so much for having me.

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MOLLY WOOD: And that’s it for this episode of WorkLab, the podcast from Microsoft. Please subscribe and check back for the next episode, where I’ll be talking to James Thomas, Global Head of Technology at Dentsu Creative about how full integration of AI is transforming organizations. If you’ve got a question or comment, drop us an email at [email protected]. And check out Microsoft’s Work Trend Indexes and the WorkLab digital publication, where you’ll find all of our episodes, along with thoughtful stories that explore how business leaders are thriving in today’s new world of work. You can find all of that at microsoft.com/worklab. As for this podcast, please rate us, review, and follow us wherever you listen. It helps us out a ton. The WorkLab podcast is a place for experts to share their insights and opinions. As students of the future of work, Microsoft values inputs from a diverse set of voices. That said, the opinions and findings of our guests are their own, and they may not necessarily reflect Microsoft’s own research or positions. WorkLab is produced by Microsoft with Godfrey Dadich Partners and Reasonable Volume. I’m your host, Molly Wood. Sharon Kallander and Matthew Duncan produced this episode. Jessica Voelker is the WorkLab editor.