You Won’t Believe What Microsoft Just Revealed About The Job Market

Microsoft just announced another round of job cuts, thousands of layoffs, and immediately the internet had its answer. Two letters, A and I. AI is eliminating all the white-collar work, here come the robots. And while that is an emotionally powerful story because it feels like it fits, it is missing the broader point. And for many of these announcements, that is the point. A giant tech company cuts workers at the exact same time every CEO on earth is talking about artificial intelligence, so the conclusion seems obvious. That doesn't mean it's true though, because when you actually look beneath the headlines, the story gets a lot more complicated and in many ways a lot more troubling. The labor market is not healthy, but it's not collapsing because AI suddenly became good enough to replace everybody. The deeper problem is that companies aren't hiring. Businesses are cautious, including Microsoft, and the macroeconomic climate is doing what it always does before people fully admit there's a problem. It's freezing the system. That's what consumers actually feel. The labor market today is not a mass firing story, it's a no hiring story. And AI, it's becoming the perfect excuse. How do we know? Because many businesses like Ford are rehiring human workers already. A growing list of CEOs and corporate execs now say they regret turning to AI as much as they had. Microsoft's latest job cuts are a perfect example of how the conversation around jobs in the labor market has become so distorted. Instead, the real story is a very familiar curve. When a company like Microsoft lays off thousands of its workers, people naturally look for one big cause. And right now, the easiest cause to point to is AI. Microsoft is investing heavily in the tech like everyone else is. It's building AI tools into its products and selling the system to enterprise customers. So, when a company like that cuts thousands of jobs, the public reaction is, here it comes. The machines are replacing people. But that explanation skips over the bigger environment every large company is operating in. This is a difficult labor market because the macroeconomy just isn't there. Demand is uncertain. Consumers are more selective. Businesses, they have to protect their margins these days. Investors are rewarding companies that promise efficiency. And in that kind of environment, executives do what executives always do. They slow down hiring, they consolidate their teams and trim costs in many ways as they possibly can, and then wrap all those decisions in the language that Wall Street wants to hear. And today, Wall Street wants to hear the one phrase more than any other. AI-driven efficiency. Now, it doesn't mean that AI is irrelevant because it's obviously not. AI is a real changing technology with tremendous long-run promise. It's changing workflow, so it's going to affect jobs. And it's already affecting certain tasks like coding, customer service, analytics, and back-office work. But the idea that today's weak labor market is mainly the result of AI replacing workers is not supported by the broader evidence. The evidence points to something more traditional and more macroeconomic. Companies refuse to hire, and many are turning to some firing to try to make it work in this environment. And to see that, you really got to look at the labor market data the way it was meant to be read. Most people don't actually have a money problem, they have a visibility problem. And that's what today's video sponsor, Monarch, has been built to solve. If you're juggling between bank apps and credit cards and investment accounts, you never really see the full picture. So you end up guessing, am I doing fine? Am I overspending? 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Did the unemployment rate go up? Did the unemployment rate go down? But there is so much more information beyond strictly the establishment survey, which everybody's going to focus on tomorrow. Those numbers can matter, but as we know, they're noisy, they're always revised, they can be misleading in real time. A better way to understand the labor market's underlying condition is to look at something like turnover, and this is where JOLTS comes in. JOLTS stands for Job Openings and Labor Turnover Survey. The media usually focuses on the JO part of it, or job openings, and if openings are high, then the labor market must be strong. That's the thinking. And if openings fall, the labor market must be weakening. But openings are only the part of the story. They're intentions. Hiring. That's action. A company can post a job and still not urgently want to fill it. It can leave a listing online for months or just collect resumes without pulling the trigger, the so-called ghost listing. Employers can claim that they have openings while quietly waiting to see if demand actually improves. That's why the hiring rate matters so much more. This is what workers see and experience, and therefore, why they are so damn pessimistic. They're told to blame the bots for this, but forgot how to grow flat beverage started long before this year. And the latest JOLTS picture has been pointing to a very uncomfortable reality. Hiring remains non-existent. Quits are low, therefore, and net turnover is worse than the headline payroll figures suggest. That's not a labor market of confident employers and confident workers. It's one of a hiring freeze. When hires are this dismal, it means companies aren't expanding their payrolls with any kind of urgency. And when quits are so minimal, it means workers aren't confident that they can leave one job and easily find a better one. And when the net turnover suggests payroll growth is basically zero at best, that tells you the headline labor market may be much softer than the payroll report numbers suggest. And that's the key point. A labor market can be bad without the mass layoffs. Job openings remain on websites, but actual hiring basically stops. The whole system becomes less dynamic. And that's exactly the kind of labor market people experience as bad, even before the official unemployment rate spikes. And we are seeing that experience show up in the confidence data. This is a big one because consumers as workers are far better at small e economics than all the capital economist PhDs that are out there, certainly the ones that are working for the Federal Reserve. And they have been warning for well over a year, going back to early 2025, with the collapse and pessimism, that there was going to be a similar downturn in jobs and incomes. And guess what? There has been. The latest results come from the conference board yesterday showing that the share of people who are saying jobs are hard to get jumped to the highest level since early 2021. Further confirming what the late labor data showed that we just went over. This is important because consumer confidence surveys capture what people really feel about the economy. They tell you whether people think opportunity is expanding or shrinking. And when more people say jobs are hard to get, they're not talking about an abstract AI future. They're talking about the job market right now. They're talking about sending out applications and getting silence or interviews that go nowhere. Companies that say they're hiring but never seem to make any offers. Fewer recruiters reach out to anyone. So more people are stuck in jobs they dislike because the risk of leaving, it just feels way too high. That is not primarily an AI story. And this distinction big-time matters because if we misdiagnose the problem, we misunderstand the situation. If AI were truly the dominant force behind the labor market weakness, we would expect to see a broad pattern of businesses replacing humans and then permanently operating better with smaller staffs. But increasingly we're seeing something else. The honeymoon is starting to be over. There's more than a little AI regret popping up. Now some companies that did move aggressively into AI replacing workers are finding out that may not have been the best idea. Maybe the technology was over promised and now it's starting to under deliver. And so they're bringing humans back. They're bringing people, actual workers back. Take Ford. According to Bloomberg, Ford Motor Company has been rehiring veteran engineers, what it calls gray bird engineers, to help fix stubborn quality problems and to retrain or reprogram AI tools that were not getting the job done. How is that for irony? Workers have to come in and retrain AI. Over the last couple years Ford says it hired 350 veteran engineers, many of them who are former employees or people who came from suppliers, helping them address quality issues that had cost the automaker reportedly billions, billions. And here's the important part. Ford's results actually improved. The company became the top mainstream brand in the latest JD Power initial quality survey. Ford's vice president vehicle hardware engineering put it very clearly. Artificial intelligence is a fantastic tool but it's only as good as the information you use to train it. And that sentence cuts through a lot of this hype. AI can be useful. It can be powerful. But it doesn't magically replace decades of institutional knowledge and automatically understand why a product fails in the field. It doesn't carry the judgment of an engineer who has seen multiple product cycles, multiple design mistakes, and of course many many real-world failures. Ford didn't solve its quality problem by firing all the experienced people and letting the algorithm just figure it out. It solved the problem by bringing experienced people back and using them to make AI better. That's not AI replaces humans, that is AI needs humans or the other way around. Humans use AI and Ford is not the only example. Klarna became one of the most cited companies in the AI replacement narrative. Two years ago it implemented a hiring freeze and began replacing its human staff with AI. Its headcount it fell sharply from around 3,800 to about 2,000 by 2024. The company said its AI chatbot could perform the work of hundreds of employees but then reality showed up. Klarna's CEO later acknowledged that customers still want the option to speak to actual humans. The company realized that reduced service quality and customer satisfaction were real problems. It is now making sure customers can always reach a human if they want one and it's pursuing a new hiring strategy that includes remote contract based workers. Again this does not mean AI is useless. Klarna still says it's investing heavily in the technology but it doesn't mean the most extreme version of the replacement story was the case. IBM is another example. The company adopted automation and parts of its human resources and use an AI powered system called Ask HR for many routine HR tasks. But reports indicated that after cutting thousands of workers IBM had to rehire people for areas where the technology couldn't handle empathy, subjectivity, and more complicated human issues. An IBM CEO has also said that despite widespread AI adoption the company's total employment has actually gone up because automation and some workflows freed investment for others. It's a very different story from AI eliminates the workforce. This by the way is the future not the dystopian nonsense that gets spouted off by various commentators who are unaware of economic history. It's closer to what technological adoption usually looks like. Some tasks are automated, some roles change, some functions actually shrink, others just disappear entirely and businesses they learn that technology without human judgment actually creates more problems than it solves. And surveys are starting to show the same thing in more widespread fashion a sort of AI regret that's settling across the business community. You had visionaries out there selling a singularity like you do like you see in every technological adoption cycle. It starts out with pie in the sky ideas and then people actually have to start using the product and in the initial stages anyway it tends to be underwhelming. Now one of those surveys by OrgView found that more than half of business leaders who laid off workers because of AI later regretted those decisions. 4 in 10 executives said they cut workers to implement AI and 55% later said they regretted it. Other forecasts suggest many AI related job cuts might be reversed by next year and that should make everyone pause. If AI replacement were already working cleanly why would so many companies be second-guessing their cuts? And the answer is replacing humans is harder than producing a slide deck that just says hey we did some AI. And that brings us to a term that's becoming more important. AI washing. AI washing is when companies exaggerate the role of artificial intelligence in their business decisions to impress investors or shape public perceptions or just to make their ordinary cost-cutting sound innovative. During the dot-com bubble for example companies wanted to attach themselves to the Internet. Today they all want to attach themselves to the hottest thing which is AI. If you're cutting jobs because demand is weak that sounds bad. But if you're cutting jobs because you say you're becoming more agile AI first it sounds almost visionary. Same layoffs different packaging. Now Coinbase that's a useful example of this AI washing pattern. The company announced layoffs affecting about 14% of its employees with the CEO describing a flatter organization and return to a startup like speed with AI at the forefront. But Coinbase is also a crypto company operating in a crypto cycle that is increasingly unfavorable. When the crypto market weakens like it is now trading activity revenue and the risk appetite all weakens with it. And in that context Coinbase's layoffs are not some pure demonstration that AI has made hundreds of people obsolete overnight. The macros and sector downturn is not just some kind of footnote. It is the driver. AI becomes simply the rebranding. And this is why and how the Microsoft layoffs should be reinterpreted. Yes AI is going to disrupt a whole lot of things but it's not going to be overnight. And like a lot of technology it's going to take some time to be adopted which means there will be time for the entire world to adjust and move forward. So yes Microsoft is using AI and it may allow some of their teams to do more with fewer people. Certain jobs inside large tech companies are going to be vulnerable to automation and restructuring. But Microsoft is also operating in the same macro climate as everybody else is. Investors are demanding margin discipline growth that is more selective than during the pandemic lockdown supply shock years and a corporate environment where efficiency isn't just rewarded it's demanded. Big tech simply overhired during the what they call the boom years. It really wasn't. Many companies assume that the demand trends for 2020 and 2021 we're just going to continue forever. Amazon another really good example of that. But then the world forgot how to grow after consumers were impoverished by the whole thing. Enterprise customers became more careful and so companies have had to reset. And that reset has been described as AI. But the deeper cause is more cyclical, more basic, more pure small e economics. And this is what makes the current labor market so frustrating. It's not bad in the simple dramatic way that people expect. It's not a 2008 style wave of mass layoffs everywhere all at once. It's a quieter slower more confusing period. Company cuts a few thousand workers here another announces a hiring freeze there. Job postings stay online but offers never happen. Workers stop quitting. New graduates in particular they struggle to get interviews. Mid-career professionals find that searches take months instead of weeks. Consumers they grow more cautious as a result and so businesses protect their cash and everyone keeps waiting for the clean signal that never arrives. That is the no hire some fire economy and it could be extremely painful. Because if you're unemployed a hiring freeze feels almost the same as a recession. It really doesn't matter that layoffs aren't exploding if nobody is answering your text. It doesn't matter the job openings technically exist if employers are not actually filling them. Who cares what the official unemployment rate is if your job search is going nowhere. And this is why focusing only on layoffs what you're told and taught to do oftentimes misses the point. Layoffs are very visible. The hiring freeze is invisible. The layoffs get the headlines the non decisions that companies don't take they don't get any press they don't get any attention. A company firing 5,000 people that's news but a company deciding not to hire 5,000 people over the next year or so is not news. Nobody ever hears about it even though the effect and opportunity can be just as devastating. This also explains why the AI narrative spreads so easily. AI is visible. Chatbots they're there. CEOs talking about automation. Everyone sees and hears it. A weak macro hiring environment is harder to see. But that doesn't mean that AI is harmless. It doesn't mean every job is safe. It doesn't mean people should ignore the technology. Workers absolutely should learn how AI affects their field and then learn to use it themselves. They should also understand the tools and which tasks that can be automated which skills become more valuable when that automation spreads in partnership with human use. But that kind of panic that people are under it's not analysis. The current labor market weakness is not best explained by robots suddenly taking over everyone's jobs. It's better explained by companies who are facing uncertain demand, higher costs and pressure to preserve profits than using AI as the language of justification. And these examples of Ford, Klarna, IBM and a whole bunch of others, they show why the AI replaces human story is overblown. AI can do a lot of things. It can write, it can summarize and speed up workflows while reducing the need for some repetitive work. But it also struggles a lot. This is typical for adoption cycles. That's why Ford brought back its veteran engineers and why Klarna is restoring human customer support options. It's also why IBM needs people in its sensitive HR functions. This is where IBM shows it still needs people in sensitive HR functions. The companies that treated AI as some kind of magic substitute are learning that it's often better understood as a tool and tools. They still need skilled operators. So the next time you see a headline like Microsoft cutting thousands of jobs, don't stop at the AI explanation. Ask what else is happening because that is where the real story is. The labor market is difficult, but the difficulty is not mainly that AI has suddenly made human work obsolete. The difficulty is the economy forgot what an upside is and lost momentum in the place where it matters most, opportunity. Not everyone is being fired, but hardly anyone is being fired. And for millions of workers, that can feel very... If you like this video, I've got another one for you where we go over what Uridel University actually does, how we put this macro information together with our market signals and why no one else knows about them or uses them, where all that came from, as well as at the end of the video, we talk about using this information in a money management, portfolio management setting, investments, all that kind of stuff. And that's the video I've got linked on the screen.