Jordan (0:01)

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Jordan (0:16)

Anthropic just published one of the most detailed roadmaps on AI's impacts on jobs that we've ever seen and the results are kind of misleading, especially if you take them to topically, I think that most people are getting hung up on the biggest takeaway that as of today, AI hasn't yet caused huge unemployment. But if you read beneath the surface, there's a much larger and more impactful finding from Anthropic's recently released AI labor report, it's that mass AI induced unemployment hasn't happened yet, mainly because the majority of Companies don't understand AI's capabilities. It's not because AI isn't capable yet of automating jobs, because it is. And there's one more finding that is going to hit the younger generation right now and might spell trouble for companies in the future. All right, let's get into it. I'm excited to jump into today's topic and here's what you're going to learn on today's show. Well, we're going to talk about why Anthropic says the AI job apocalypse is isn't happening, but something worse might be happening. Why AI is actually a threat to more highly educated white collar workers and not blue collared ones that we always thought automation and AI would come for. First, we're going to learn which five white collar jobs are already being automated the most right now. And we're going to dig into a little bit more on the massive capability gap in AI that almost no one is talking about and how you can actually use that to your advantage. All right, let's get into it. If you're new here, welcome. My name's Jordan and this is Everyday AI. If you're new here, this is an unedited, unscripted daily live stream, podcast and free daily newsletter helping everyday business leaders like you and me make sense of everything that's happening in the world of AI. Because it is non stop. I tell you what's important, what's not. You take that information to grow your companies and your careers. Sounds like a good trade off, right? Starts here, but make sure to go to the next level. Go to our website@your everydayai.com we break down each day's podcast as well as giving you all the other AI news that you need to know to stay ahead. Right. Like as an example, Microsoft just Released their, their new cowork. Right. Yeah, work is changing. All right, but let's get straight into something that's been dominating the headlines a lot, right? I actually, you know, at first saw this study and I'm like, okay, this is important. We shared about it in our newsletter and my wife was actually like, I'm seeing this all on my Apple news. Right. So she's seeing it everywhere. So, like, there's a certain point when AI news starts to hit the mainstream outside of our little, you know, AI, you know, closed circle here. I'm like, okay, this is worth diving into a little bit more, but let's first kind of zoom out and talk about this new study and what it found from Anthropic. So researchers tracked U.S. employment data from 2020, 2016 through, well, the post chat GPT era. And the biggest finding was, well, there's no mass AI unemployment. Right. So AI isn't taking millions or tens of millions of jobs yet. That's because while their findings over the last 10 ish years show that that hasn't happened. And the unemployment estimate for highly AI exposed workers was statistically nothing. Right. So even in areas where AI has been shown capable to automate a lot of jobs, we're not see, right. Millions of people being laid off. Right. I think early, you know, very early on in the early generative AI large language model days, you know, there's a lot of these predictions that, you know, there's going to be tens of millions of fewer jobs fairly soon. And well, we haven't seen that happen yet. And Anthropic's study, I think was one of the best that really dug into this. But here is one thing that this study found that is kind of concerning, especially if you are a younger person, but I think it has larger implications even if you are mid career running a company. And this is actually something I talked about last year on the show because it's something that I spotted a long time ago and I've been talking about it quite a bit. But this study found that hiring of workers age 22 to 25 into AI exposed fields quietly dropped by roughly 14%. Let's think about that percentage point right now because I think when people are looking at AI and its impact on jobs and unemployment, the thing that most people look at is the unemployment rate, which seems to be smart. Right. Because if AI is impacting millions of workers, well then that means the net number of Americans with jobs is going to go down, correct? Well, yes and no. Right. Because what we've seen happening. And you know, this study from Anthropic showed as much a 14% drop, right? For the most part, if you don't follow, you know, unemployment numbers like I do, you know, it, it varies by a little bit, but for the most part, you know, the unemployment rate in the US is between 4 to 5%. Aside from know anomalies like, you know, the pandemic, the financial crisis of, you know, 2028, 2009, right? But for the most part, for the last 25 years, the unemployment rate in the US has teetered, you know, 4%, give or take, right? So when people still see that 4%, they're like, okay, AI is not causing, you know, mass UN unemployment. But what I do think it has already started to cause, especially in the younger generation, is mass underemployment. Because if we had an UN unemployment rate at 14%, that would be a global disaster, right? People would be in the streets probably rioting, right? Hey, big AI, you took away my job, right? But that's essentially kind of what's happening for the younger generation. They, in those highly exposed areas at least, companies are just not hiring anymore. I've been talking about this Since I believe 2024, this process of quiet hiring, how there's been this kind of thing, you know, as post pandemic, right? More and more people are remote and hybrid. There's this thing called quiet quitting, right? Where employees, whether they're using AI, augmenting with AI or not, they're kind of doing the bare minimum and just scathing by, I think companies have already started and the, the anthropic study shows this. They've kind of done this quiet hiring. They're just no longer hiring for junior people or when people leave, right, to avoid having these, all right, we got to cut 10,000 jobs, 20,000 jobs, right? We heard reports Oracle might go up to 30,000. We've seen tens of thousands from Amazon. So for bigger companies to avoid this, well, they're just not hiring, right? So when the Silver Tsunami hits and we have millions of seniors, you know, people in their 60s retiring, well, they're just not going to refill those roles. And those younger people that are in these highly exposed areas are just not going to be able to get jobs. Also, some key findings, and we're going to dig into all of these a little bit more. But there's a massive gap, the capability gap between what AI could do versus what it's actually doing and what it's actually being used for. And the most exposed workers Right now are female educated and higher paid. So the Great Recession for white collar workers. Well, that scenario, even though it hasn't happened yet, it is still very much so on the table because that is where the exposure and the risk is. And I think with this report, Anthropic actually built an early warning system to track where disruption may show up first before any unemployment numbers can diagnose it. So let's talk about the biggest finding and that is the massive gap, right? And this kind of chart obviously went, you know, very, very viral online, right? Whether you're reading Twitter, LinkedIn or the news, you probably saw this chart. So for a podcast audience, you can always, you know, check this out obviously in the newsletter, but you can go watch the video version of this@your everydayai.com. nothing we can't describe here, but essentially this chart showed the different occupational categories, right? So everything from management, business and finance, legal, health care, food and services, personal care, office admin. Right. All these different sectors of work. And then you had a theoretical AI coverage line, right, which is in blue. And then kind of the, the spider graph that shoots out and if you, the AI could theoretically do a hundred percent of the job, then it goes all the way to, well, the exterior of this circle. So in the blue you have your theoretical AI coverage, right? And then you have your observed AI coverage in the red. All right, we're going to talk a little bit more. How Anthropic got to that essentially is a combination of U.S. employment data and millions of anonymized chats with Anthropic's Claude Chatbot. Right? So what you essentially see is, well, AI is theoretically extremely capable in many areas and right now does not have a lot of capabilities in others. Right? So some of the biggest areas where in theory, right, AI could do, you know, 80 to 90% of the work comes in fields like management, business and finance, computer and math, legal arts and media. Right? Those are areas where there's at least 80% coverage up to the mid-90s. And then there's areas, at least right now, that large language model in their current capabilities, well, they don't really touch, right. Sectors like production, installation and repair, construction, agriculture. Right. Those jobs that for the most part require you to use your hands away from a computer for the majority of the time that you're working. And that's kind of how we got to this capabilities gap. But when we talk about the theoretical AI coverage and the observed AI coverage throughout the rest of the show, the this is essentially what we are talking about it is what AI can actually do, right, According to benchmarks and AI's actual capabilities. And then the observed AI coverage, which is what Anthropic found through millions of anonymized chats. Well, what people are actually using it for. And even in those areas, right, Management, business and finance, computer and math. Nothing. Nothing hit the 40%, right? In the majority of those, even with high theoretical AI coverage, right, where, hey, technically AI could do 90% of this right now out of the box with nothing else happening, right? A lot of those areas, right, like management, legal, right. The actual observed AI coverage was low. It was, you know, less than 20% in many instances. So let's talk about one of the most obvious categories and that's in computer and math roles. So the observed capability was 90 or, sorry, the theoretical capability was 94%. So anthropic found by matching it with US jobs data that AI's capabilities right now can do 94% of tasks, but it's only being 33% observed. And that is of all the different columns, that is actually the highest observed AI coverage. So maybe you're thinking, oh well, yeah, people are just using AI for different things that maybe aren't falling on this map. Absolutely not. That is the highest observed AI coverage. And the gap there is still enormous, right? I've been talking about this capability gap. I talked about it a lot on our 2026 AI and roadmap series about this huge gap. And that people especially, I think since quarter four of 2025, they still are looking at AI like a fun little chatbot, not realizing its agentic nature, the improved scaffolding and harnessing. Well, it can probably do the majority of your work and you just don't know it. So not only is there capabilities gap that comes from training well, there's also just the education side. People don't even know. I think a lot of people understand that they maybe don't, you know, can't get behind a computer and you know, fully use a chatbot like Claude or Chat GPT or Gemini or Copilot to its fullest capabilities. But I think the majority of people, even those that follow the technology fairly closely, don't even understand what those capabilities actually are. Right? So the 61 point divide in the computer and math roles as an example, that just defines the current state of AI at work. So here's kind of my hot take I kind of already talked about a little bit. Say it's Tuesday, right? We're not doing as many hot take Tuesdays, but I'm going to go ahead and throw my hot take opinion in here. This is going to happen. We are going to see the, the great, you know, white collar work recession. It is a lagging factor, right, that 30, what was it, the 31% or, sorry, the 33% observed coverage in math and computer right now, that's going to go up. It's going to go up. It's going to go to 40, 50, 60 in the coming, in the coming months and quarters. The same thing with these other, these other areas, right? I talked about this on the prediction and roadmap series, but I think especially in anything that costs people a lot of money, right? Legal, management, business and finance, that gap is going to shrink. I think we're going to start to see measurable shrink in 2026, but I think by 2027, that gap is going to close very quickly. Quickly. I think that's how long it takes for the average, you know, US company. It takes nine to 18 months for companies to truly, number one, realize that there's a gap. I think studies like this one from Anthropic that put it into concrete terms obviously help executives in boardrooms understand that, oh wait, there is a gap, right? And you can see the methodology which we're going to talk about here in a second. But then it takes them time to start to learn to close the gap. That is, unless you and your company listen to the show every single day. Because I've been talking about this gap before Anthropic or anyone else you know, officially identified it. Granted, I didn't have millions of anonymized anthropic chats to really bring teeth into it, but this is something I've been observing, well, for the last three years since I've been doing this show.