The Secret Behind AI Layoffs: When Corporate Speak Meets Reality
As the corporate layoff carnage continues its relentless march, I keep digging into the reasons behind such bizarre behavior. In my previous essay, The EPIC Cycle: When Winnie-the-Pooh Meets Silicon Valley Economics, I identified that companies are now in the Panic phase of my EPIC (Exuberance, Panic, Ideation, Creation) cycle. Today, let's get specific about what's really happening behind the curtain.
The Numbers are straight forward (But the explanations are not)
Point one: The scale is staggering. Microsoft alone confirmed plans to cut 9,000 roles, bringing their total 2025 cuts to over 15,000, all while framing these reductions as part of a push to "simplify operations and invest heavily in AI" [Tech Layoffs 2025: Why AI is Behind the Rising Job Cuts].
Now let’s examine another data point: over 50,000 tech workers have already lost their jobs in 2025 – far surpassing last year's pace. But here's where it gets interesting: out of 286,679 planned layoffs so far this year, only 20,000 were officially linked to automation, with just 75 explicitly tied to AI implementation [Summer Lull in June 2025 as Companies Announce Virtually the Same Number of Cuts as Last Year | Challenger, Gray & Christmas]. Interesting contradiction.
Now here's the kicker: this is happening against a backdrop of very strong financial performance. Microsoft reported Q1 2025 revenue of $70.1 billion – a 13% increase from the previous year – while simultaneously cutting more than 15,000 jobs. Amazon and others are posting similarly strong earnings.
This creates an obvious question: why cut jobs during record profits? All this is extraordinary and requires some... creative explanation. And boy, did we get one! It's all about "renewed focus on AI," they tell us. Watch closely – companies are laying people off to "focus their priorities on AI."
The Real Story (Hint: It's Not About AI per se)
Having watched how businesses operate for decades, I find this explanation somewhat wonky. It reminds me of previous corporate speak – remember the "microeconomic climate" explanation for everything? Looks like an attempt to continue to fund AI without a more R&D budget.
Here's what I think is happening: companies are reallocating resources away from roles whose value has fallen below their "AI investment line" and doubling down on roles that help monetize AI in their view. In effect, AI does not replace people, companies are trying to cut costs to continue to fund AI without new investment but admitting that creates undesirable PR effects. So instead, we get vague euphemisms about "strategic realignment" and "operational excellence."
There's another fascinating layer to this story – the chickens from COVID over-hiring are coming home to roost. That massive hiring spree never translated into profit because it wasn't done with any strategy or targeted innovation. Companies just... hired lots of people. When economic uncertainty spooked them, they decided to shed anyone not deemed "essential."
Companies are discovering that the only way to increase AI investment is to cut costs elsewhere, hence the suspicious correlation between AI investment announcements and workforce reductions [Tech sector layoffs mount amid AI investment frenzy | Computer Weekly].
The P in EPIC
We have the AI reality check that leads to the question of who will train the AI – I think this is the cause of “panic” and subsequent behavior.
Here's the thing about AI that the C-suite seems to have missed: AI can automate jobs, but it needs very clear instructions on how to perform those jobs. You need crystal-clear role definitions and success criteria.
Not having clear AI implementation strategy is apparent and will create negative effects. Organizations should resolve fundamental operational inefficiencies—including role clarity, accountability structures, and talent management systems—before implementing AI solutions. Without addressing these foundational issues, AI becomes a costly overlay on dysfunctional operations rather than a transformative tool [AI Isn’t To Blame for the Rise in Layoffs — Your Systems Are | Built In]
You can't simply instruct an AI agent to "improve customer satisfaction" or "reduce expenses by 5% next year." You need a crisp understanding of how those tasks can be performed, where to get the data, what the checkpoints are, legal constraints, and so on. AI is fundamentally a robot – it can't invent chess, but it can win at chess if given precise instructions, decision algorithms, and access to every chess game ever played.
Consider how AI works in practice – how Deep Blue beat Kasparov. Deep Blue wasn't just told to "win" – it was trained and improved by a big team of very specialized people. Similarly, if companies want to replace humans with AI, they need to do it diligently. And frankly? I don't see that level of rigor yet.
Here's where it gets truly absurd. Look at LinkedIn or check out Big Tech Layoffs Aftermath: Who Found a Job & Where? – the average experience of laid-off workers is almost 12 years. Most people I see getting the axe have 20+ years of experience.
This represents an unbelievable waste of human capital. Remember those "people are our most valuable asset" proclamations? These weren't fresh graduates – they were seasoned professionals who were trained on the job and had gained deep insights and experience. And yet, companies are tossing them aside.
The real kicker? Remember that companies are laying off people who, in their view, do not produce value for AI? Those are exactly the people who could have been productively used to train and develop AI systems to do their jobs effectively – while gaining new skills in the process! Instead, we're just... throwing them away. To close the loop with Deep Blue analogy – where are the equivalents of IBM folk who trained the Deep Blue?
The Bottom Line
What we're witnessing is companies largely masking business and financial issues – not to mention fear of an impending economic crisis – with the "AI excuse." They're using it to cut costs while doubling down on AI investment, hoping it magically produces profits.
It's Winnie-the-Pooh logic reigning supreme, and I see it being applied to more areas of the industry every day. Companies are essentially saying, "We don't really know what we're doing with AI, but everyone else is doing it, so we better do it too – and fire a bunch of people to pay for it."
Is there hope?
I think there is. Philosophically, everything goes in cycles, systematically, the theory of homeostasis and complex adaptive systems tells us that systems self-stabilize after the disturbing impact. All that is currently going on will settle. What we need to do is prepare and adapt. The objective is to become valuable in the era of AI that is not quite here yet but will come. The nuance is that it will not be what many think of it now.
In my next installments, I'll share thoughts on the future of Product and Program Managers and Software Developers, subjects dear to my heart. Because if current trends continue, we're in for quite a ride.
The EPIC cycle continues to spin, and we're still firmly in the Panic phase. The question is: how long before companies realize that throwing experienced humans away while chasing AI mirages might not be the strategic masterstroke they think it is?