Between January and September 2025, there have been more than 946,000 job cuts announced, with roughly 300,000 from the government sector. That's the highest since 2020, and it's a 55% increase from what we saw last year through the same time period. It would make sense to think AI is to blame for the layoffs. Now that we've had generative AI come in and kind of change the equation, investors and boards are asking management teams: how are you using AI? Why aren't you using AI? Can AI help you streamline costs? But the latest round of layoff announcements in the fall of 2025 suggests AI might not be the root cause of the restructurings. They also seem to be real signs that something new is happening, that we've turned a corner in the economy. So we've seen a wide range of reasons. You're not really seeing companies say, I am cutting 10,000 employees and replacing them with one single computer. Using AI and introducing it to save jobs turns out to be an enormously complicated and time consuming exercise. I think there's still a perception that it's simple and easy and cheap to do, and it's it's really not. There's no doubt AI is a powerful force in the economy right now. The extent to which we think it's affecting the economy and hiring is in graduate level, low skilled jobs. We haven't been able to find yet much evidence that AI is capable, at this moment, of taking over sort of white collar middle management jobs. So why are we seeing so many layoffs and how much of it is because of AI? Wall Street has been hyping generative AI innovation for several years now, which is putting pressure on executives to make it a part of their business model. 79% of CEOs in the US said they feared they could lose their jobs within two years if they didn't deliver measurable, AI-driven business gains. Investors need to be a little careful with what some people have called AI washing. And what that is, is this idea that because business is deteriorating or there's some difficulty going on with the business, you say, oh, we're letting people go because of AI. No, you're letting people go because the business is hurting and calling it AI, and because Wall Street is buying anything with the letters "A" and "I" attached to it. And so what you might find is you would actually get a bump in your stock because you're letting people go because of AI. There's this kind of financial fiduciary incentive for management teams to say they're using AI and say that strategies are related to AI, even if it's not totally related to AI. There's been surveys that have come out that found companies are attributing certain strategies and plans to AI, but it could be as simple as, you know, using AI to write an email for you, right? Is that really a revolutionary use of this technology? No. But can you say you're using it as part of your strategy? Technically, yes. We spend a lot of time looking carefully at companies that are actually trying to implement AI, and there's very little evidence that it cuts jobs anywhere near like the level that we're talking about. And in fact, most cases it doesn't cut headcount at all. It may come effectively later on by improving productivity. So you get some of the effects of it. But it turns out it's really, really hard to cut headcount with AI. Even Meta's decision to cut 600 workers in October 2025, they cut those workers from their AI unit. And that's because the AI unit had gotten bloated. They had hired too many people, and especially at these tech firms, where the idea of integrating new technology, innovating and disrupting, you cannot have ten people you have to go to to make a decision if you want to be a disruptor and an innovator. Companies are announcing big layoffs all the time. In a given year, there could be a million announced layoffs. The question is whether or not there's other hiring going on. And the problem we have is that there's no official hiring data. We've seen a wide variety of reasons for the layoffs that we've seen in recent months. Sometimes it's related to a larger restructuring at the company, an effort to reduce costs. Sometimes it's related to changes in the business. This is kind of a trend in corporate decision making where big corporations become really fat over time, right? You have all these layers of middle management, and it takes a long time for people to get things done, right? Corporate employees spend a lot of their time in meetings. They spend a lot of time talking about work, but not a lot of time actually doing work. As we enter into leaner economic times, you're seeing companies kind of rethink their corporate structures. Do I need five layers of management for one project to get done? If I cut out 3 to 4 of those, how quickly can we actually have this project out in front of customers? And, when you're in a high interest rate environment, the job market has become weaker, consumer spending has become weaker. You don't really have the luxury to have five layers of management to go through every time you make a decision. I think in general, they just don't seem to worry about the consequences of over cutting, nor do they worry about the consequences of what happens if they're guessing wrong about recession. So there's been some interesting research over the last couple of years showing the costs of doing that. And basically the short conclusion is the longer you can resist a layoff, the better your financial performance is likely to be. And part of that is because you don't save as much money by cutting as you think, but also on the rebound. It takes you a while to bring new people in, get them settled, not disrupt the place and then turn things around. There's a great story out there that maybe people want to tell about the coming revolution of AI wiping out all the jobs. Let's just be skeptical of that until we have a little harder evidence.