Sometimes the corporate world is silent.
It’s not the silence after a product launch fails. It’s not the silence after a quarterly miss. It’s the silence that comes when a company publicly fired hundreds of people, told the world AI had made those workers obsolete, and is now trying to hire some of them back without issuing a single press release about it.
That’s what’s happening right now. And the story isn’t really about AI at all. It’s about what companies owe the people caught in the middle of a technology bet that didn’t pan out.
The Wave Nobody Announced
Between 2024 and 2026, more than 180,000 workers lost their jobs at companies that cited AI as the reason. The announcements were confident, often grandiose. Executives explained on podcasts which roles AI could absorb. The framing was consistent: this is efficiency, this is the future, this is inevitable.
Here’s a plot twist. Surveys of HR professionals now suggest that more than two-thirds of organizations that conducted AI-driven mass layoffs are actively rehiring. Not replacing those roles with different talent. Rehiring for the same functions they cut.
The companies doing this are not holding press conferences.
What AI Actually Couldn’t Do
Here’s what the quarterly projections didn’t account for: the work that actually retains customers is intensely human.
AI tools turned out to be effective at processing structured information, automating repetitive tasks, and generating first drafts of things. They turned out to be considerably less effective at de-escalating a frustrated customer who has been transferred three times. At making a judgment call that isn’t covered by any training data. At reading the subtext in a client relationship that’s about to go sideways.
The nuanced work, the relationship work, the judgment work. That’s the work that makes or loses money in ways that don’t show up cleanly in a cost-reduction model until they start showing up in churn, in complaints, in contracts not renewed.
Companies ran the efficiency math and skipped the fragility math. Now they’re doing the fragility math.
The People in the Middle
It’s easy to discuss this as a corporate strategy story. The more honest frame is a human one.
Think about what those workers actually experienced. A public announcement told them their jobs had been eliminated because technology had advanced beyond what they offered. That’s not just a layoff. It’s a specific kind of professional diminishment. It’s a company declaring, in front of the whole industry, that the work you did was essentially easy to automate.
Then, months later, someone from HR calls. Or a recruiter reaches out on LinkedIn with a job description that looks a lot like the role you used to hold.
Some workers have gone back. The economy is unforgiving, and a paycheck is a paycheck. Others have moved on and aren’t interested in returning to an organization that treated them as disposable when the hype was loud. Both responses are completely understandable.
What’s less understandable is how little acknowledgment has accompanied the reversal. No public statements. No letters to former employees. No accounting for what happened.
Premature Optimization Has a Human Cost
There’s a phrase making the rounds in technology circles: premature optimization. In software development, it means solving for efficiency before you fully understand the problem. Applied to workforce decisions, it means cutting human capacity before you’ve genuinely tested what AI made simple. What can it and what can’t it replace in your specific operational context?
The companies that did this weren’t all acting in bad faith. Some genuinely believed the capability claims they were hearing. Some were under investor pressure to show they were taking AI seriously. Some were following each other’s moves without doing independent evaluation.
That doesn’t absolve anyone of responsibility. Believing the hype doesn’t make the impact on workers any less real. The people who lost those jobs had mortgages and families and professional reputations. They had to explain to their next interviewer why their position had been eliminated. They had to recalibrate their sense of what they were worth in a market that was loudly telling them they were replaceable.
The organizational reasons for the layoffs don’t change any of that.
What Accountability Looks Like
Corporate accountability during technology transitions doesn’t require companies to be omniscient about what AI will and won’t be able to do. Nobody has that clarity. The technology is genuinely developing fast, and reasonable people disagree about its trajectory.
What accountability does require is honesty about uncertainty.
If a company is making workforce decisions based on AI capability projections, those projections should be treated as projections, not certainties. Workers deserve to know when their roles are being evaluated against technology that hasn’t been proven in their specific context. They deserve transition support that reflects genuine uncertainty, not confidence that turns out to be misplaced.
And when the reversal comes, when the private rehiring starts because the AI-only approach didn’t work, workers deserve some form of acknowledgment that the original decision was, at minimum, premature.
The silence isn’t protecting anyone. It’s just protecting the company’s public image at the expense of the workers who bore the cost of getting the bet wrong.
The Pattern Will Repeat
The technology adoption cycle tends to run the same way: a new capability arrives, confidence outpaces evidence, decisions get made based on possibility rather than proof, and then reality provides a correction. This happened with previous waves of automation. It’s happening now with AI. It will happen again with whatever comes next.
Each cycle catches workers in the gap between announcement and correction.
The productive question isn’t whether AI will continue to change what jobs look like. It will. The productive question is whether companies can learn to move through these transitions with more honesty about what they know and what they’re gambling on.
The rehiring wave is a correction. That’s not a bad thing. It means reality still works.
The silence around it, though, is a choice. And the workers who rebuilt their lives after being publicly told they were obsolete deserve better than a LinkedIn connection request as the only acknowledgment that the math didn’t add up the way the press release said it would.
Joel Comm is a columnist at Grit Daily, New York Times bestselling author, internet pioneer, and keynote speaker who has been helping people understand emerging technology since the early days of the web. Best known for making complex topics accessible, Joel speaks and writes about AI, entrepreneurship, digital media, and the future of technology in everyday life. He is the co-host of The Bad Crypto Podcast and host of AI for Everyone, where he explores practical, human-centered uses of artificial intelligence.
