7 Skills You Need to Stay Employed in the Age of AI

If I had to distill the future of work into one idea, it would be in the form of a single question that only you can answer. If you couldn't rely on your job title to explain what it is that you do and you could only share the unique skills that you offer, the outcomes that you make possible on a team or for a company, and the problems that you are uniquely equipped to solve, what would that be? In other words, if you were to describe yourself as a many organization, what does that organization offer? That is a snapshot of the future of work, where we're moving toward a future that is less defined by job titles and these distinct roles and towards a future where the workforce is defined by skills. When AI becomes the foundation of the workforce, it's going to continue to change what skills companies are going to need because AI is going to learn more tricks over time so it's going to be able to do more things, which means it's going to change the skills we have to bring to the table. It's going to change the problems companies are able to solve the products that they're able to launch, which makes it much more challenging to hire somebody full-time because that role is going to look completely different in 12 months or in 18 months or in two years. Instead, we'll start to move towards companies hiring for a bundle of skills for a particular project or to achieve a particular outcome. This is a very different way to think about the workforce. It means to be stop looking at ourselves like job titles and moving up that traditional career ladder and instead, we look at ourselves as a unique bundle of skills, as a many organization that has an offering to different projects and different companies at any one time. I call this the rise of the independent era and of course has many implications for how we think about work, how we think about social security, health insurance, economic security and we're going to get to that in another episode. But today I want to talk about the non-negotiable essential skills for this era, regardless of how fast job titles start to disappear and how fast the workforce starts to change. These are the non-negotiable skills for the future. The first AI literacy. Right now working with AI and knowing how to work with it is still a bit more of a novelty. That's all going to change. Knowing how to work with an AI system is going to become the expectation. The same way nobody asks if you can work with a computer or if you can operate a smartphone or if you know how to attach a PowerPoint slide to an email. That's the assumption. That is the path that AI is on. It is going to become that assumed and that expected in the workforce. Now is the time to be building these skills. It is really a non-negotiable and that means we have to stop thinking about AI as this chatbot that we sometimes choose to ask a few questions too and sometimes we don't. That's not what's happening. AI is a general-purpose technology like the internet. So the foundation of everything we do will happen on top of it. All the roles, HR, pools, candidates from the internet, marketing, targets, customers on the internet. It's a part of everything. That's the same path that AI is on. It's going to go from being a novelty to the expectation. AI literacy isn't about being a computer scientist or knowing how to code, but it's also not just asking AI to summarize a document for you or write this email more quickly for you. It's understanding the dynamics of how these AI systems actually work, right? That they're trained on a bunch of data. They spot patterns in data and they make predictions based on those underlying patterns. So it means before you ask AI to solve a problem for you, you're thinking, was this system trained on the right data for what I am trying to do? Is this the right kind of AI model for the problem I'm trying to solve? What happens if AI gets this answer wrong or AI is kind of misled? If you're thinking about a marketing slogan, not the biggest deal. If you're asking for a legal brief, a very big deal. So AI literacy is also about the reasoning that happens before you ask AI to do anything. It also means that when you delegate a task to AI and it doesn't do a great job, you don't just stop and think, well, AI is so overhyped, can't do anything. You think about how did I structure the problem that I gave AI? Did I treat it much more like an intern, which requires a back and forth dialogue? It requires me providing context for the AI, or did I just ask it to do something randomly? And then when it gave me the answer, I'm like, nope, doesn't really work. Finally, understanding things like bias in the data set. AI is trained on data. Data has a lot of biases in it. Thinking about that, when AI gives you an answer, what assumptions are baked into this answer? What biases might be found in this data that are going to be embedded in the outcomes and the options that AI provide? So those are all the fundamentals of AI literacy. The next skill is critical thinking. And a way to think about this, I'm going to give you an example. If you come across quite a sensational health claim on social media, what do you do next? Do you immediately send it on to a friend? Or do you stop and think, hmm, who benefits if I share this video? What are the assumptions or the evidence that this person making a scientific claim is relying on? Are there other similar scientists or similar material that I can review? Was there more evidence that supports these claims? How well do you examine the assumptions that are being made? Do you evaluate evidence? Do you analyze the reliability of what you're seeing? Right? So these are all vital critical thinking steps. And the more AI becomes embedded in all of the tasks that we do, the more valuable these critical thinking skills become. And the challenges right now, we're seeing a lot of people offloading their thinking to AI systems. They're not just asking it to build out the PowerPoint slide. Like sure, that's fine. AI is going to do more and more of building out slides and writing documents, but they're not even thinking about what they're asking the AI to do. So right now we're in a strange position in the workforce where we're still getting paid for the tasks AI can do. Building out beautiful marketing materials, writing a sales script when you make your next sales call. We're moving towards a future where the assumption is going to be that AI did that for you, that AI does the doing and we get rated on and evaluated on and paid based on the thinking that we provide. We get paid for the incremental value. We add above the AI just executing on the tasks. And if you're outsourcing all of your deep thinking to AI and you're just asking it to do things and then implementing exactly what it says, well, not only is that that cognitive muscle going to atrophy, but you're going to become more and more dependent on AI. And so again, it's not just that you don't ask the eye to write your slides. AI is probably better than most of us at putting together a slide deck. But you think more deeply now about, is this the right brand strategy we should even be pursuing? What assumptions am I making when I think about we should continue to target this market over that market? Could I, if somebody asked me why I'm choosing the strategy, really clearly articulate and support it with evidence or is it just because AI said that this is the best thing to do? The next skill and this is really linked to critical thinking and we talk about this all the time in this podcast, judgment. We are moving toward the workforce where we direct supercomputers and we evaluate the answers that they give us. At first, it might just seem like, oh, this is going to be a really hands-off workforce. No one's going to do anything. If AI can do all of the executing and instead you get evaluated on the depth of the problems that you ask a super computer to solve, why did you ask it to build that app in the first place and not this other thing? And when AI gave you the right answer or gave you two amazing answers, which one is better for the context that you're in and why? That is much more deep thinking and much more judgment than we usually exercise. AI can flood you with possibilities, but it can't tell you which of those possibilities actually matter and it can't decide what is worth doing in the first place. And I'm going to give you an example of what judgment and critical thinking look like in the future in the form of somebody that isn't exercising it. So let's say you work in human resources and now the HR department uses AI for everything to write all of the job descriptions, to pick which candidates are going to come for the interviews. So in terms of your performance, it improves in terms of the speed at which you're able to hire new candidates. It's great. You save tons of time. But then the attrition rate and the rate that people keep quitting hasn't improved. The rate of training, the amount of time it takes to train someone hasn't improved, which shows you didn't actually exercise any judgment or critical thinking beyond what the AI has helped you do. You didn't step back and think, is this the best market we should be procuring talent from in the first place? What assumptions is the AI making when it's selecting different candidates? What about our training program is no longer working? So if you're not exercising that judgment, it's going to become really clear that the problem is you. Because AI can execute perfectly on all of the things you're asking to optimize for. We want smart engineers to do X, Y, and Z. Great. That was the description. It's going to go find those people in a pool of a million people. But maybe that's actually not what the company needs. And before you gave AI that optimization function or before you gave AI that problem to solve, you didn't stop and think that wasn't the right thing to ask it. So judgment and critical thinking become more important. And it's going to be a lot easier to see who's exercising thinking and who's not. In a future where AI starts doing the doing and we get evaluated on what we're asking and how we evaluate the outcomes. The next skill is communication. And this could seem counterintuitive. The more we work with AI, the better we need to be at communicating with people. And here's why. Right now, most people are using artificial intelligence. Not in secret, but maybe. So AI writes your slide deck or it writes your script for your sales report. It's not assumed that AI did that for you. But we're moving towards a future where it is. The assumption is, okay, this is the strategy that AI built. So now you have to be able to articulate to a team of people, what assumption the AI is making? What trade-offs the company is going to be making by pursuing this strategy over that strategy? You're going to have to get really clear at working with people and explaining the work that you're doing. And I'm going to give you a really detailed example. Imagine you're working in marketing and the AI system that your team uses suggests that you run an email campaign and offer a huge discount to this particular market. Great, that is the strategy that the AI suggests. When you go to your team, you're going to have to be able to convince them that this is the right thing to do. So you're going to have to say things like, here's what the AI is recommending and why. It is telling us that the people in Region X have historically responded well to discounts. So this system is predicting that we're going to get a quick win if we push this price. But here's what the AI isn't seeing. It's only looking at past emails and past purchasing data. It has no sense of our brand perception. It has no sense of competitor activity. It's only optimizing for short-term responses, not our long-term goal towards becoming a premium company in the future. So everybody in the room, this is the trade-off that we're making. If we follow this strategy, we're going to get a short-term win in revenue, but long-term, we may start to train this segment of the market to only buy our products when they're on sale. Are we okay with this? That is the clarity of communication that we're going to have to have in the future. We can't just kind of hide behind computer results anymore. So the more AI gets embedded in our workflows, the more valuable communication becomes. Another essential skill for the future of work is being somebody that people actually like to work with. And this doesn't mean you have to be super social or the loudest person or the most outgoing person, but somebody who makes work easier, rather than more challenging. And here's why, the more independent the workforce becomes and the more project-based, and we're just going to build teams and they're going to dissolve really quickly. If you're really challenging to work with, it's quite unlikely that you're going to be called back to work on projects over and over again, because people will have more options. Well, we're only working with this team for six months and this one person was really hard to work with last time. Maybe you can find somebody else with similar skills. And this becomes more important and the more capable AI gets, right? So the more of the executing that AI actually does, the writing of the legal briefs and the doing of the code, the work experience becomes much more about working with other people. Yes, working with AI, but communicating strategies to other people, bringing people on board of the direction that you should be taking. People are going to start to really value the experience of working with you, not just the technical skills that you bring. So that's something to keep in mind. And I'd say the final two skills for the future, learning and adaptability, learning how to learn. Most of us don't even know how we learn. And what context do you learn best? By reading, by listening to something, by hearing somebody explain something, how quickly do you learn? Are you able to spot when you're not understanding something and be able to break down what it is you're not understanding and into a component part and figure a structure and a strategy to get clarity on that? All of these aspects of learning are really important for the future because the technical skills that we bring to the table are going to become obsolete, faster and faster as AI continues to learn new tricks over time. So if we think even about AI in this moment, how are you doing at starting to learn these skills? Are you leaning into it? Are you practicing and just at least trying? And are you understanding what you're not understanding? And thinking about, okay, this is the area that's not clicking for me. What do I do next? How do I break down this big problem of things I need to learn into something modular and tackle it one piece at a time? So learning how to learn is really important because the reality is nobody can predict the exact type of work that's going to exist in two years or in five years. But if you know how to learn and you're a quick learner or you at least know under what conditions you learn best, you'll be able to learn and adapt in that moment and you'll be fine. So learning how to learn, start practicing that learning muscle now and working with AI is a key way to do it because that's one thing that we're all trying to do right now in this moment, learning how to work with these systems and finally, being adaptable. How well do you adapt to change? And a way to think about that is how well are you adapting in this moment? When you think about all the different things we're going to have to adapt to in the future, we're going to have to continue to learn new things over time. We're going to continue to work with different people, maybe every three months, maybe every five months. We're going to have to learn how to become more entrepreneurs. These are all things that we're going to have to adapt to and not just once, over and over and over again. We can't even say what AI is going to look like in five years. And if it's something that you struggle with, it's a great time to start building out that resilience and building out that adaptability muscle now. So when summary, the skills that we cover today, AI literacy, critical thinking, judgment, communication, learning, adaptability, and being somebody that people like to work with. And I want to make sure that you know that you are not late to this moment. CEOs don't even know what they're doing with this technology, really and truly. So you're not late, but you do have to start leaning in and start building some of these skills. And even the non-technical skills like judgment and being a good communicator, those can actually be more challenging to build than something like AI literacy. So the most important thing is starting now. One thing I always like to say about the future is no matter what you believe to be true about it, the best thing we can always do is prepare for it. And that's something that we're really committed to on this podcast. We're going to be with you every step of the way when it comes to understanding these trends about the future of work and preparing for them and building out these skills. If you have questions for us, please drop them in the comments or you can submit them on our website via email. When we write about the future of work, the trends that we're seeing and how we can best prepare in our weekly newsletter, which we'll link below. So thanks so much for tuning into this episode, and I look forward to seeing you at the next one.