The Boomerang Effect: Are AI Layoffs for Real, or Just an Alibi?

Speaker A: Recently, a tech company in Hangzhou, China's eastern AI hub, deployed AI, uh, large language models to take over a quality assurance supervisor's core responsibilities. Look right away to the irony of this story. The supervisor's job, his core responsibility was exactly verifying the accuracy of AI generated outputs. Yeah, that's right. The man whose job was making sure AI didn't mess things up was eventually fired because AI took over his job of making sure AI didn't mess things up. But here's where it gets really interesting. The company didn't fire him right away. They first offered him a reassignment, a quieter way of saying demotion at a 40% salary reduction. When the employee, identified only by his surname, Joe, refused, the company terminated his contract. Their justification was that organizational restructuring and reduced staffing needs driven by AI adoption. Hanzhou fought back. He filed an arbitration claim and eventually he won. But as the company sued to overturn that decision, it eventually lost at the district court level. And just last week, they lost again on appeal. And why so? The Hangzhou Intermediate People's Court ruled the dismissal unlawful on two grounds. First, AI AH driven workforce reduction does not constitute a, ah major change in objective circumstances. Under China's labor contract law, the legal threshold that is required to justify termination based on redundancy. Now, a second, the steep salary cut embedded in the reassignment offer was itself unreasonable. The court's conclusion was as elegant as it was radical. Companies cannot shift the cost of technological transformation onto their employees. And here's the reflection that lies behind this episode of between youn and AI if this ruling becomes the global template, well, companies will have to prove that AI actually does the job before firing the human. And as someone who sat on the executive side of the table when those decisions get made, well, let me tell you, the uncomfortable, um, question for leaders is would your AI layoffs survive a courtroom? Especially right now, because we're watching something strange unfold in real time. Companies are firing thousands of people because of AI and then quietly, they're hiring people back. I call this the AI layoff. Uh, boomerang. So which is it? Are these layoffs for real or they're just an alibi? And that's what we're going to talk about in this episode of between youn and AI here's your host, Andrea Yoro, speaking. I'm an Italian KeyNote speaker and USA Today best selling author, former head of Tinder Latin America for five years. I was also the Chief Digital Officer at l' Oreal Brazil, an MBA professor at Funda Salon Cabrao and I'm a columnist at the MIT Technology Review and Wired Mexico. My latest book is called between youn and AI, published by Wiley. You can get to know me better and my work, uh, uh, in keynotes and workshops at andrea yo audio.com so let's zoom out for a second. See, the Hangzhou ruling is not an isolated development. It builds on a December 2024 arbitration decision in Beijing involving a data mapping worker whose job was automated away. The panel reached almost the same conclusion that an employer's decision to adopt AI is not an uncontrollable event and the cost of that business choice cannot be unilaterally passed to to employees through dismissal or demotion. And CDs. Not just China. Watch what's happening at the same time on other three continents. For example, in the European Union, mass layoffs driven by automation can trigger consultation obligations under the collective redundancies directive. Translation? You have to sit down with work councils and explain yourself before you cut any job. And Starting in late 2027, after the recently agreed omnibus deferral, the UE AI act will add a separate compliance layer for high risk AI UH systems used in employment, including hiring, performance management and task allocation, with penalties up to 35 million euros or 7% of global revenue. That's GDPR level uh, penalties. In the UK dismissals linked to technological change can engage unfair dismissal protection tribunals. Look at whether employers followed fair processes and genuinely considered alternatives. Across Asia Pacific, in places like Singapore and Japan you have mandatory RE employment obligations, notice periods tied to seniority and sector specific labor. All of which create real legal exposure for employers who think AI related restructuring is just a clean business decision. So what does this all add up to? Well, to three different philosophies on what an employer actually owes a work. Same technology AI, but three completely different answers. China says the employer bears the cost of transformation, period. Europe says you have to consult document justify and the United States that we haven't mentioned so far. Well, the USA AI did it is a sufficient explanation and at will employment does the rest. Interesting, as China is at the same time at the forefront of the AI revolution and it's clashing of course head to head with uh, the us but they have very different approaches. And here's what every multinational leader is about to discover that your values that beautiful slide at the top of every culture deck will now produce different outcomes depending on which country your worker happens to be sitting in. Now, opponents of regulation will surely call all of this public interference. The state getting in the way of innovation, the visible hand strangling Adam Smith invisible one and would obviously argue that this is the wrong way to go and that the US got it right. But here's the thing that's interesting. The Chinese court isn't ahead of the market. It's the market that is finally catching up to the court. What we're calling a ah, legal restriction is actually the market quietly conceding that full replacement was also a mistake and eventually backfired in a number of cases. Let's take Klarna as an example. The Swedish fintech that became the poster child of AI, uh, replacement. They fired roughly 700 service workers and replaced them with an OpenAI powered chatbot. CEO Sabian Siem Atovsky went on CNBC to proudly share that the hound count um, dropped, investors applauded. Then six months later customer satisfaction actually dropped. Chatbot looped people in circles it couldn't hand emotionally charged interactions disputes that messy 20% of cases that actually matter. So Klarna started quietly rehiring and Semiatowski said something remarkable. From a brand perspective, a company perspective, I just think it's so critical that you're clear to your customers that there will always be a human if you want. We went too far. Maybe it's not a coincidence. Now that Klarna reached break even for its first time on May 2026, IBM did the same with HR. The company cut 8,000 HR jobs and pushed them into a system called Ask Ah hr. Then it discovered that AI couldn't handle empathy, judgment or cases that didn't fit the script. So it started rehiring humans. And then there's Duolingo. And this one is interesting because it's a softer version of the same pattern. In April 2025, CEO Luis von Han sent his now famous AI first memo. Contractors would be phased out where AI could handle the work and employees would be evaluated on how much they used AI. Framing went viral, but not in the way he wanted. A year later, Von Hahn has quietly walked back almost every piece of it. The AI usage performance metric gone. After his own employees asked whether they were just being told to use AI for AI sake, the AI first rhetoric softened. In a recent Fast Company interview, he admitted I did not give enough context. And he was even more candid about the technology itself. The happy path is really fast, but the unhappy path makes it so that you end up spending more on that than the time you saved on the other things. So in plain language, AI didn't deliver what the memo promised. So the memo got rewritten one walk back at a time. See the pattern? Klarna first fired, then rehired. IBM cut and rehired. Duolingo declared and retreated then. These are not isolated cases. Foerster's Predictions 2026 report found that 55% of employers now regret having laid off workers for AI. And Gartner predicts that half of all AI attributed layoffs will be reversed by 2027, though. And this part stings often offshore or at significantly lower salaries. So this. So is this kind of a boomerang effect? It is. And it's a particular kind of boomerang because the version of you that comes back is not the version that was fired. It comes back lower paid, less stable, often in a different country, with less institutional knowledge, less morale, and more skepticism about whether their employer ever actually understood what they did for a living. Now let's go even deeper, because the more I think about the boomerang effect, the more I ask myself, because if the market is having to walk back its AI layoffs, what does that say about how real those AI layoffs were in the first place? This brings us to what Sam, um Altman himself has now publicly acknowledged. He calls it the AI washing. And the data is striking. Forrester's Prediction 2026 report found that nearly 6 in 10 hiring managers admit AI was cited as the reason for layoffs. That they were actually driven by other things. Budget cuts, revenue uncertainty, or the need to unwind the aggressive hiring speeds of 2021 and 2022. Why are companies doing this? Well, three reasons. First, AI layoffs play differently on Wall Street. Marc Benioff knows it best when he announced 4,000 customer support scattered salesforce. I said I need less headcount. Well, layoffs framed that cost cutting trigger questions about why you hired too many people in the first place. Now layoffs frame that AI transformation can trigger a 3% stock pop and a Bloomberg piece about leadership. Second, AI gives executives moral, uh, cover. If you say we're cutting because of AI, well, you're not the villain. AI is the villain. And you see, nobody made a decision. But in reality, it's your human decision. Being outsourced to AI. More convenient, isn't it? And third, it's contagious. The clustering of Oracle, Meta and Snap layoff announcements in the first three weeks of April 2026 wasn't a coincidence. It was a corporate play becoming standard practice. Because once one CEO frames cuts as AI, uh, driven gets rewarded. Well, every other CEO has to ask whether not doing so makes them look Behind. So what we have in plain language, is a market where companies are firing people for a story their CFOs don't fully believe, hiring them back when the story doesn't work, and reframing the whole sequence as innovation. And here's the deeper issue. There's a real cost to this kind of dishonesty, and the cost is trust. The Chinese court's ruling, the Klarna reversal, the AI washing data, they're all chapters in the same story, a story that a generation of workers is figuring out that AI was the name we gave to a decision that was made by a person. And this brings us to what I think is the deepest layer in this whole story. And honestly, it's the reason I wanted to do this episode at all. It is that. Well, the Hangzhou court made a legal argument, but buried inside the legal argument is a philosophical one. And I'd argue it's one of the most important reframes of the I conversation that we've seen in years. See, what the court said is that AI driven workforce reduction does not qualify as a major change in objective circumstances. Now, objective circumstances sounds like legal jargon, right? But impact it. What the court was really saying is AI is not like, I don't know, market collapse. It's not a flaw. It's not an act of God. It's a choice. It's a choice a company makes. And because it's a choice, the cost belongs to whomever made the choice, not to the worker who was reorganized around it. And I want you to sit with that for a second, because every layoff narrative of the last two years has leaned on the same trick. AI is treated as something happening to the company. The technology is moving so fast, we have no choice but to adapt. The future is here. Notice the passive voice. Notice the disappearance of responsibility. So, to wrap it up, let's come back to where we started. Somewhere in Hangzhou, there's a man named Zhou. We don't know his first name. We only know he was a QA supervisor whose job was to make sure AI got things right. His employer decided that AI no longer needed his supervision. So they offered, um, him 60% of his old salary or the door. He chose neither. He chose the courts. And the courts told his employer something that every executive listening to this should hear. You don't get to call your decision the future. You don't get to call your decision the technology. You don't get to call your decision anything other than what it is. That's your decision. And the question for the next decade of leadership isn't going to be whether AI takes jobs. It's going to be whether you as a leader can stand behind what you do with AI without hiding behind it. So I'll leave you with this. When you make your next big AI call, the next restructure, the next automation rollout, the next AI driven efficiency play well, picture the courtroom. Picture the zo. Picture the version of your decision that has to survive contact with someone whose life just changed. If your decision cannot survive that picture, well, maybe it isn't really about AI. And with this, I wanted to thank you for your attention. Up to the end of this episode of between youn and AI. Here is your host, Andrea Iorio. If this episode made you think, well, share it with a colleague, a friend, a leader. And, uh, check out my book, between youn and AI published by Wiley. You can find anything related to my work, uh, as a keynote speaker@andreayorio.com See you next week with yet another episode of between youn and AI.