Ep 854: The AI Labor Shift: When It Will Happen and What It Means for Jobs (Start Here Series Vol 13)

Welcome to the Everyday AI Podcast. My name is Jordan Wilson, and for the past 3 and a half years, we've put out more than 800 episodes. Yet one of the most common questions I get, I didn't really have an answer for. Where do I start on the Everyday AI Podcast? And that's why we started the Start Here series. And with fall now back in full swing, the Everyday AI Podcast is going back to school and playing back the entire Start Here series. From front to back. We've hit pause on our normal Monday to Friday programming to run back our most popular series ever for the next 30 days. We made the Start Here series for beginners and AI champions alike. So whether you're just trying to get a grasp on large language models or grappling with the best coding harness for multi-agentic workflows, the Start Here series covers it all. Plain language, no jargon, and easy to follow along each day. So make sure to subscribe to the podcast and check back each day for new insights, day by day. The series is a culmination of spending more than 10,000 hours covering generative AI over the past 3 and a half years. So you don't want to miss a single episode of the Start Here series. Let's get into it.

In the past 2 weeks alone, we've seen reports that more than 40,000+ jobs will soon be eliminated due to AI. Yet we've read all those reports for years. So it seems we may soon be entering the crossroads of slowly dying and the birth of a new era of Earth. Somehow we need to make those shifts. And while it sounds Kind of exciting, like we're concluding a new era. Also pretty scary, like we would really waste decades of our lives. There's all these agents who are way smarter than us, but just maybe— oh, we're going to be digging into this topic. Welcome to today's edition of Everyday AI and LARRUZ Start Here Series. Welcome. My name's Jordan Wilson.

Mm-hmm.

Let's just get straight to it. Here is the big picture of what we're gonna be talking about today. Jobs are getting— and no one knows what the future of work is gonna look like. I mean, we've already— 45,000 layoffs. We just got word the past week and a half that there's going to be 45,000 more. You know, the CEOs of these companies are all citing it's because of AI entering the workforce. Yet, I— our census— not here to build infrastructure. And we know that AI will ultimately create millions of new roles, but eliminate more traditional jobs than it replaces. So that puts us at this crossroads. That's exactly what you're going to learn about on today's show. Because here's what we're told. We're told about unconventional triggers behind layoffs that most workers and journalists aren't falling for. We're gonna go over why the real displacement starts already underway and almost nobody can see it. We're gonna talk about which everyday roles are first in line to be displaced by AI and which ones did not even exist 2 weeks ago. And in the end, I'm gonna leave you with the first step to survival by AI that you can start using today when you finish this call. All right. New here? This is Everyday AI. This is our Start Here series. I realized after more than 700 episodes in 3 years of talking about AI every single day, I didn't have a great answer for— which is, hey Jordan, where do I start? I'm new to the podcast. I'm like, I don't know. Well, now you start with the Start Here series. This is the essential podcast series to learn the AI basics. Double down on. So make sure you haven't already, go to starthearseries.com. It is going to give you free access to our inner circle community. It's private. You can't even find it. You can't. starthearseries.com. And that will also put you straight into our Start Here series space where you can go back and read and listen to every single episode in the series. So In our last series, we talked about the state of the AI race. Who will win in 2026? OpenAI, Microsoft, Google, or Anthropic?

And today, let's get into it.

This state, well, the AI labor shift. All right, when it'll happen and what it means for jobs. So reality, the biggest companies on earth are slashing Headcount, right? So we just saw reports that Meta is going to be laying off 2,000 jobs. Last week we saw Block cut more than 4,000, and Oracle is reportedly cutting 30,000 jobs. The February 2026 jobs report showed 92,000 jobs lost. And it, we did go up a little bit. So yeah, if you are listening to this in March, maybe that's a little relevant. Maybe you're listening to this, I don't know, in late '26 or early 2027. I don't know. So, you know, keep in mind these stats are going to change, but don't doubt it. I don't think this reality is going to change anytime soon. Big tech companies are starting to lay workers off in mass. Right? Because not all of these jobs I think are getting cut because of AI. And we're going to talk about that later. But AI does kind of become a scapegoat or a get out of jail free card for a lot of these companies.

There's actually a Harvard Business Review study that showed 60% of hiring managers cited AI for layoffs, yet only 2% actually replaced those roles or used AI to actually replace those roles. So it seems like maybe in some instances, it's just kind of corrections from this overhiring that happened post-pandemic, rising interest rates, And just margins, business profit, it's getting slimmer, thinner.

I think one of those reasons is because of artificial intelligence, right? It's allowed medium-sized companies to compete with big companies. It's allowed SMBs to compete with small enterprises. So margins are getting thinner, budgets are getting tighter, not just because of the interest rate. Because also companies are trying to do more with less because of AI, right? They're making hugely investments into artificial intelligence, right? Everyone's training their people, but bigger companies are spending maybe at least 7, 8 figures on AI investments annually. So they're like, hey, well, we got to say, hey, these Jobs are being cut by AI. And if they're a public company or a company with shareholders, that's not going to make them happy. Because Block, we talked about this on our AI news show recently, they cut 40% of staff. They cited AI and said, well, it's essentially because of new technology, and their stock rose 22%. Now, you can go back. I've been saying this since 2023. Right? Let me just get on the record right now. I've always said AI will ultimately take away more traditional full-time roles than it will create. Yes, it will create millions of jobs that no one knows what they are, but I think ultimately it will. And I've said this all along. The more companies cut jobs, public companies especially, they're going to cut jobs, say it's because of AI, stock price goes up, shareholders are happy. Wall Street is happy, the economy is happy, and then the medium-sized businesses that aren't public are going to follow suit because they're like, well, look what happens. This is kind of the trend that everyone's doing. So Forrester did predict that half of the layoffs though will be quietly reversed. So it's not always the actual answer. Sometimes it's a, you know, stop happening to either Like I said earlier, correct overhiring, or when companies honestly need a bump and maybe they have too many layers of bureaucracy, right? Like we heard the Amazon report, you know, when they cut their multiple out of, you know, more than 10,000. Well, they said it was too much bureaucracy, right? There's too much red tape and companies couldn't be lean and agile and actually build. AI allows small teams to do what used to take many, many large teams, right? When you have too many pieces of middle management and you have too many meetings, you can't do that. A great conversation I had with a leader at Google was, you know, memos, or sorry, demos over memos, because it's getting way more costly to just have meetings about things. To just actually do that, right? Whereas traditionally, that's what you do. You get smart people in, things go slowly because, well, usually the investment builds time. I really changed that. So what is actually driving these? Well, it's this shift operating expenditure to capital expenditure. All right, you don't speak business language. Essentially, companies are looking to, especially the big Fortune 100 companies, the Mag 7 companies mainly, but in general, companies are looking to move away from operating expenses, which is salaries for humans, benefits, and moving it into AI infrastructure, capital expenditures. So just 5 companies, Amazon, Alphabet, Meta, Microsoft, and Oracle. Have already announced capex things of $700 billion per month. So that's the data centers, custom silicon, cooling plants, power generation, all that good stuff, right? But they're not buying today's AI, right? That's not $700 billion that they're spending on training their current employees, right? These are a lot of the same companies that are cutting the jobs and taking that money, right? Literally just borrowing against You know, human spending in AI industry, right? Buildings, power, GPUs, right? And because they're betting on tomorrow's, not today's. Because if today's AI was these knees, right, we wouldn't be seeing all these huge companies spending hundreds of millions of dollars to build something else. They'll just say, all right, game's over, let's train our people and No, I think everyone knows that the future compute is going to be a scarce resource. And the access to it and the ability to scale it up is going to be one of a company's biggest assets, right? Even more so than in years past, right? The biggest asset was people, right? You had world-class experts. That was your company's calling card. Well, in the future, it may just be able to scale millions or billions of world-class agents, whereas maybe your competitors can only deploy 5% of that or 1%. That will be a real advantage. That's what we're seeing in this shift from OpEx to CapEx, but that still doesn't really solve the jobs, right? Obviously, there's jobs that are going to be lost. Jobs, you know, at these plants. You know, people boots literal boots on the ground constructing maintaining those plants. But what about the jobs that come after? Well, that's why this is. We did talk about this recently, so I'm not going to go too much into it. We'll bring up this labor study in episode 730. But just as an example, in graphic academy. Great study where we looked at millions of anonymized chats inside of their chatbot. Then they essentially mapped out everything across 20,000 different tasks in these government jobs datasets, essentially. And they found theoretically AI can do 94% of computer admin roles. That's just what it said. But it was only a used 33% of the time. So that's actually the highest usage observed was 33%. So in most cases, you have this massive capability gap of saying like, hey, no, AI can actually go do all these jobs that we're hiring all these people to do, right? All these codifiable tasks. Yet most companies aren't doing it, right? Even if you look at that gap, you know, sectors like management, legal, and business, below 20% preserved usage despite 80% capability, right? So it provides 80% roles, tasks associated with those sectors, management, legal, and business, yet the US at large, at least according to slides, real anonymous usage, it's only being used 20% of the time. So most companies are overwhelmingly still treating AI like chatbot. And it's actually a workforce shifter, right? You couldn't have made that claim, you know, probably 9 months ago, but can. So when does the real shift hit?

When's shift gonna hit?

And who is gonna get hit first? Well, we'll dive into that in a second after a word from our partners.

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Check out Sectio at sectioai.com. That's S-E-C-T-I-O-N-A-I.com. All right, so here's when that shift might happen and the types of roles that might feel it. And here's the reality. It's already started. You maybe haven't seen it, but we've—I've talked about it multiple times on the show. I think it started mainly toward the end of 2025, but we started to see a little bit of it in 2024. That's essentially where AI is augmenting senior workers. Well, entry-level hiring has quietly slowed, right? So we did talk about that in episode 730, where essentially. If you were to say college graduate placement was the unemployment rate, that's 14%, which again, if that was the actual unemployment rate across the board, you know, the US would be up in arms. But we've already seen, you know, companies instead of hiring juniors, instead of hiring entry-level people, they're just augmenting, you know, senior workers with AI or middle middle-tier workers with AI and then just not hiring those people. And the same thing with the baby boomers and the silver tsunami happening. Well, they're just not hiring to replace these people. But I think what we're gonna start to see this year and next year is just the flattening. It's gonna be the great flattening. I don't think it's gonna be the great white-collar recession, but I think teams are gonna restructure and that capability gap that I talked about is going to close fast because I think now the average non-AI techie, right? The people who haven't been listening to the show since 2023, they're finally starting to wake up and realize, right? I actually had a friend, you know, text our group chat the other day and she said, you know, just kind of a group of our friends. And she said, wow, like Claude just did an entire presentation for me, right? I think now, you know, these people that maybe haven't been following AI for years are starting to be like, Wait, AI can do this? Like a job that I would normally hire a human for and would probably take a lot of time? Yes, it can. So I think in 2026, 2027, that's where we see this, uh, the capability gap start to shrink and also the corporate ladder start to, well, it's not gonna be a ladder anymore. I don't think we're gonna have, you know, that normal tier, right? Where you have your entry level, you have your middle management, and then you have your senior leadership. I just think the bottom rungs of the corporate ladder are going to get chopped off. And yeah, so bye-bye middle management, I think, as well in 2026 and 2027. And then in 2028 to 2030, I think that's where we're going to start to see the return of the $700 billion and growing, obviously, of infrastructure, because I think that's when the autonomous workflows start to arrive en masse. So one of the things is, if you're listening to this, Well, you're ahead of the game. You know what's coming, right? And I'm gonna end the show by leaving you with some, some pieces of advice. But I do think it's one of those things, probably by 2030, there's most, I think most roles are gonna be orchestrating agents, right? Which might sound weird, just like it probably would've sounded weird in, you know, 1999 if someone was like, hey, all roles are gonna be using the internet. It's like, no, that makes no sense, right? But that's, that's the reality, right? So many knowledge workers are just using the internet all day. And I think that's where we're going to be. I think probably by 2030, early 2030s, most knowledge working jobs are going to be agent orchestration. So let's talk a little bit about those types of roles. So there's a recent study that came out from the Federal Reserve Bank of Dallas, and it talked about kind of codified knowledge versus tacit knowledge, which is a great way to kind of classify these different types of, well, knowledge and tasks, right? But essentially codified knowledge is what new graduates really rely on, right? It's those easy kind of quote unquote grunt work. And that's how companies have historically trained juniors, right? Junior researchers, junior analysts, whatever is this kind of this learning track that companies have always gone through. You give the easy, the quote unquote easy work that can easily be verified, but it's just manual, right? It's the manual grunt work and it's those tasks, the summarization, the personalization and the synthesization of of knowledge, synthesizing knowledge and personalizing through the company's tone and creating something of value, right? So a lot of times that's your general research tasks, you know, competitors, market trends, you know, put it in spreadsheets, run some formulas, make a little presentation, right? Like that's junior work. That is the codified knowledge that's gonna be gone, right? AI does that already much better and companies are starting to realize that and they're saying we don't need to hire humans for that anymore. Right? But the tacit knowledge, that's obviously not where AI can touch yet, right? That's the nuance required to make decisions that come along with being a subject matter expert. I think that's, you know, how you have to, you know, sometimes be able to understand a larger organization or a competitive field, right? Is that kind of the savvy that you might need, not office politics per se, but sometimes office politics, right? That's what AI cannot You know, do yet. But I think regardless, another shift that's happening and already happening is that younger generation. You know, we've seen that I already talked about 14%, you know, that the exposed fields. So hiring for younger workers, 22 to 25, in exposed fields dropped roughly 14%. All right. So what can you do about it today? Right before you finish that morning coffee that maybe you're sipping on right now, know a couple of things. Again, if you've, if you are not new to AI, you're in a great place. Even if you do feel uncomfortable about this labor shift that is going to inevitably happen, if you have been putting AI in place, if you've been, you know, listening to the show, following what we've been talking about for a long time. You're good, right? And it's actually pretty telling. The Dallas Fed study showed that actually a lot of wages have risen, right? Nationally versus where they were at previously. Because if you are keeping your job, even though there's fewer jobs, those jobs are getting paid much more. And not just the standard cost of living and inflation, it's companies have now Realize that they will have to pay a premium dollar, right? Because when you do have fewer employees, the stakes are higher. And those employees that you are going to be orchestrating agents, you really want to assure that you have the right people, right? Because that's a compounding factor that we haven't seen before. You know, usually both the risk and the reward lever was restricted to a single person and what that single person was capable of, for better or for worse. Right? But with AI and agentic AI, it is a compounding factor. So if you have the right smart people, they can literally 5x, 10x, 20x over time. So that's why, you know, these roles are actually getting paid more and workers with AI skills are earning on average 56% more than those without skills across similar industries. So it's kind of this sweet spot of domain expertise, which we talked about earlier, some of that tacit knowledge as well, plus AI fluency. That's the highest combination in any field. Although we did talk about in episode 730, well, in some cases, those are also those that are most susceptible or most exposed to AI automation. So the new AI jobs, though, they're just not going to be for engineers. I think 2 years ago, that was kind of the, the thought, right? Oh, anything, you know, for the future growth of AI, if you wanna work in there, you have to be CS. You gotta be computer science, you gotta be a coder, you gotta be an engineer. Not anymore. As an example, a recent IBM study showed that 1 in 4 companies now have a chief AI officer. Although part of that is telling, I think, in both regards. Okay, that's impressive that, you know, 1 in 4, but why not 2 in 4? Why not 3 in 4? But right now I think we're seeing emerging roles include things like context engineer, Agentic orchestrator, AI auditor, geo strategist, right? Showing up in in chat, I guess, right? But the barrier has dropped, and these roles really, I think, reward domain expertise over technical know-how or software or coding. So I think a lot of people have been scared away by job growth because we look. at how the, you know, jobs and how careers have progressed over the last couple of decades, because that's all we can look at. And I don't think that's how jobs are going to pan out because it's not going to be a 1-to-1 match and it's not even going to be a, you know, a 1-to-2-to-3. It's going to be a 1-to-B. You know, it's, it's, it's going to be on a, on a playing field. That isn't level, right? So I think a lot of times when people are saying, hey, I do have AI skills that I've been putting to place, what do I do now? Well, you might want to start looking at roles that you might have thought were previously technical roles, and they're probably not. All right. You, you have some of the greatest, you know, software engineers of all time now admitting that they don't even code anymore. These are people that have, you know, helped code the products that have changed the world. And they're saying, well, you know, not to get into, you know, self-learning and all of those things, but the models are really building the models now. Right. And humans are just orchestrating agents. So that does really change, I think, what you are capable of because that barrier has dropped. All right, so we're going to end on this. This is your 3-step survival guide for starting today because we don't know when the next round of jobs are going to be gone or when the new jobs that don't exist yet are going to start popping up. And I personally don't think it's going to be a nice, a nice handoff. I'm not saying, you know, there's going to be massive unemployment or anything like that, but I'm a realist when it comes to AI. Corporate greed, I think, is going to cause a lot more harm in the long run than AI. Obviously, those 2 things, you know, walk hand in hand, but I don't think it's going to be 5 million jobs gone this year, 5 million new jobs created 2 months later. It's not going to be like that. So here's what you have to do now. Number one, you have to audit your role. You have to start separating those daily tasks Into what are those judgment-based tasks versus those codifiable, right? Not saying that you need to panic if you know everything in your day-to-day is codifiable, but that does mean in theory that you know your job might change sooner than later. All right, so you first need to audit your role. You need to have a realistic expect. Uh, a realistic look at your day-to-day and say, how automatable is my job right now with what we know of today's models? Number 2, document your reasoning, right? Write down why you made hard decisions and what you weighed when going through those decisions. I've talked about this. I think companies and departments, this is kind of separate, right? I'm kind of leaving you with, uh, more from a personal career employability standpoint, but I've also been very bullish on companies doing this. You need to document your literal company reasoning, right? Because that is some of that, you know, knowledge, at least right now, your reasoning, your subject matter expertise, your domain experience. Sometimes you don't always practice those things because they are innate and they don't always, you know, show up in that spreadsheet. They don't always show up In that deliverable, in that artifact. A lot of times it is the filling in the, filling in the gaps. You really have to document that. And then last but not least, I think you need to master one AI platform deeply until it literally just becomes an extension of your own expertise. And I think that's difficult. I think that's difficult for people because you see all these new advancements in AI. Right? Oh, the, you know, first we had, you know, reasoning models and then we had plugins and now we have skills and now we have, you know, all these, you know, IDEs and we have all these vibe coding tools. We have all these, you know, agentic orchestration loops. You know, it's like every day there's a new flavor. And I think sometimes people think or assume, well, the way I make myself more employable in the future is I have to know a lot of everything. You will fail.

Let me say that again.

If you are just trying to keep your skillset up to par with the skillset of the week, you will fail. You can't do it. You can't, right? This is what I try to do every day. You can't do it, right? I can't do it. I can't go out and, you know, do all these things I talk about every single day. 2 years ago I could, today I can't. No single human can anymore. So you have to double down on one platform, right? What it, whatever it may be, uh, right? I don't know, developing, you know, skills for accounting, uh, right? I don't know. And when I say skills, I mean, you know, obviously agentic skills and writing them, right? But you have to overlap that with your current domain of expertise. And I think if you go through those 3 steps, It's not going to, you know, be a save-all safety net if there is a white-collar job recession, right? The AI job apocalypse. But it is your survival guide that you can start today to prepare yourself and to get yourself going down the right direction now before it's too late. All right. I hope this was helpful. As we talked about, Start Here series, volume 13, The AI Labor Shift. When it'll happen and what it means for jobs. All right. There's also, there's guys, there's way too much I couldn't get to in today's show. I'm being honest. Put together a ton of cool resources, some great things in NotebookLM, all of that. So if you do want access to this couple, you know, cinematic videos, some slideshows, all that, if you want access to all of those additional resources, if you're listening to this episode and you're like, I want to dig deeper. I wanna double down. There was so much I couldn't get to. I didn't want this to turn into one of those, you know, accidental 60-minute shows. So if you go repost this on LinkedIn, I will send you all of that over. So if you're looking for the LinkedIn show, right? If you're listening on the podcast, you probably are. Just look in the show notes. It's always in the show notes. It says like, you know, go join the conversation on LinkedIn. That is the LinkedIn link. And then just go repost that and I will send you all of those resources over. And then make sure you go to starthearseries.com. That's gonna give you free access to our private inner circle community, and you can go catch up on all of the episodes in the Start Here series. So thank you for tuning in. Hope to see you back tomorrow and every day for more Everyday AI. Thanks, y'all.

And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers, and we'll see you next time!