"We're implementing AI to drive efficiency," the CEO announced at the town hall. Three weeks later, 200 employees received termination notices. The official reason? "Organizational restructuring."
But everyone knew what "efficiency" meant.
I've been watching the AI layoff conversation unfold with a mix of concern and skepticism. On one side, you have dire predictions about mass unemployment. Oxford Economics projects AI could displace 60% of jobs in some sectors. On the other, Goldman Sachs suggests the impact will be minimal—maybe 7% job displacement globally, offset by new job creation.
So which is it? Are we heading toward an employment apocalypse, or is this another round of fear-mongering about technology that ultimately creates more opportunities than it destroys?
After working with organizations navigating this transition, here's what I've learned: The answer is complicated. And the real story isn't about what AI can do—it's about what leaders choose to do with it.
The Great AI Debate
Let's start with what the experts are actually saying, because the headlines oversimplify everything.
Oxford Economics paints a sobering picture. They argue that AI and automation will fundamentally reshape labor markets, with certain sectors—particularly those involving routine cognitive tasks—facing dramatic displacement. Think data entry, basic analysis, customer service, even some professional services like paralegal work and junior accounting roles.
Their research suggests we're not just talking about efficiency gains. We're talking about entire job categories becoming obsolete. And unlike previous technological revolutions, this one is happening faster than workers can retrain or industries can adapt.
Goldman Sachs takes a different view. Yes, AI will displace some jobs. But history shows that technological advancement creates new categories of work we can't yet imagine. The automobile eliminated jobs for stable workers and buggy manufacturers, but it created entire industries around manufacturing, infrastructure, services, and logistics.
Their analysis suggests that while 300 million jobs globally could be affected by AI, most will be augmented rather than eliminated. Humans plus AI will be more productive than either alone. And the productivity gains will drive economic growth that creates new employment opportunities.
Both perspectives have merit. Both also miss critical nuances.
What's Actually Happening on the Ground
Here's what I'm seeing in real organizations, away from the research papers and market predictions.
AI as Cover for Long-Planned Cuts
Some companies are using AI as convenient justification for layoffs they were planning anyway. The technology gives them a forward-looking narrative that sounds better than "we overhired" or "our business model is struggling."
I worked with an organization that announced AI-driven workforce optimization. When I dug into the details, they'd been trying to reduce headcount for two years due to margin pressure. AI gave them the story they needed to finally pull the trigger.
That's not AI displacing jobs. That's corporate theater using AI as a prop.
Genuine Transformation With Terrible Execution
Other organizations are legitimately transforming work processes with AI. But they're doing it badly—cutting people before they've figured out the new operating model, eliminating roles without understanding downstream impacts, moving fast without thinking through the human and operational consequences.
A healthcare system I know implemented AI for medical coding and immediately laid off half their coding staff. Six months later, they were drowning in billing errors, compliance issues, and revenue cycle problems because the AI couldn't handle complex cases and there weren't enough humans left who understood the nuances.
They saved money on salaries and lost more in delayed reimbursements and regulatory penalties.
Strategic Augmentation Done Right
Then there are organizations approaching this thoughtfully. They're using AI to handle routine tasks, freeing employees to do higher-value work. They're retraining people whose roles are changing. They're being transparent about the transformation and involving employees in designing the future.
These organizations aren't seeing mass layoffs. They're seeing role evolution, skill development, and—in some cases—the ability to grow without proportional headcount increases.
The difference? Leadership intent and execution quality.
The Questions Leaders Should Be Asking
If you're a leader navigating AI implementation, forget the macro debates for a moment. Here are the questions that actually matter for your organization.
What Problem Are You Solving?
Be honest. Are you implementing AI because you have a genuine business problem it can solve? Or are you doing it because everyone else is and you're afraid of being left behind?
If you can't articulate the specific business outcome you're trying to achieve—faster processing, better decision-making, improved customer experience, whatever—then you're not ready to implement AI. And you're definitely not ready to make workforce decisions based on it.
What Happens to Displaced Workers?
Let's say AI genuinely can perform work that currently requires 10 people, and you only need 3 people to oversee it. What happens to the other 7?
Do you have roles they can transition into? Can you retrain them for higher-value work? Will you help them find opportunities elsewhere? Or are you just planning to cut them and move on?
Your answer to this question says everything about your organizational values and culture. And it determines whether your remaining employees will trust you through the transition.
How Will This Affect Quality and Risk?
AI is powerful, but it's not infallible. It makes mistakes, sometimes in ways humans wouldn't. It lacks judgment, context, and the ability to handle truly novel situations.
What happens when the AI gets it wrong? Who catches the errors? Who owns the consequences? Have you thought through the risks, or are you so focused on efficiency gains that you're creating new vulnerabilities?
I keep thinking about that healthcare system with the coding problems. They saved money on headcount and created a compliance nightmare. That's not transformation. That's trading one problem for another.
What Are You Building Toward?
This is the question most leaders skip, and it's the most important one.
What does your organization look like in five years? What work will humans do? What work will AI do? What capabilities will you need? What culture will support this new model?
If you're just cutting costs without a vision for what you're building, you're not transforming. You're just shrinking.
The Uncomfortable Middle Ground
Here's where I land after watching this unfold: Both the optimists and pessimists are partially right.
AI will displace jobs. That's already happening. The pace and scale are up for debate, but the direction isn't.
AI will also create opportunities. New roles, new industries, new ways of working that we can't fully predict yet.
But the ratio of displacement to creation? That's not predetermined by technology. It's determined by human choices—specifically, by leadership choices.
Organizations can use AI as a tool for thoughtful transformation that augments human capability and creates value. Or they can use it as a blunt instrument for cost-cutting that destroys institutional knowledge and employee trust.
The technology enables both paths. Leaders choose which one to take.
What This Means for You
If you're an executive considering AI implementation, here's my advice:
Be Honest About Your Motives
If you're using AI primarily to cut costs, own that. Don't dress it up as innovation or transformation. The people affected deserve honesty, and your remaining employees will see through the spin anyway.
Invest in Your People
If AI is going to change how work gets done, invest in helping your workforce adapt. Training, reskilling, career development—these aren't nice-to-haves. They're requirements for successful transformation.
And if you can't afford to invest in your people through the transition, you can't afford the AI implementation either.
Think Beyond Headcount
Stop measuring AI success primarily by how many positions you eliminated. Measure it by business outcomes: better decisions, faster processing, improved quality, enhanced customer experience, increased innovation.
If your AI business case depends entirely on headcount reduction, you're probably missing bigger opportunities and setting yourself up for long-term problems.
Communicate Transparently
Your workforce is already anxious about AI. They're reading the headlines. They're watching what you do, not just what you say.
Be transparent about your plans, your timeline, and your intentions. Involve employees in designing the future. Create psychological safety so people can voice concerns and ask questions.
Secrecy and spin breed cynicism and disengagement.
The Real Answer
So are AI layoffs real or corporate theater?
Both. Sometimes simultaneously.
Some job displacement from AI is inevitable and already underway. Some announcements are opportunistic cost-cutting wrapped in technology language.
The more important question isn't whether AI will affect employment—it will. The question is whether leaders will navigate that transition thoughtfully or use it as cover for decisions they were going to make anyway.
Your organization's story is still being written. The technology is a tool. You're the author.
Choose wisely.
