The AI layoff narrative is missing the real story | Daily Reports Online
The numbers circulating through fintech right now are hard to ignore. Almost 10,000 jobs have been cut across the global sector in 2026 so far. PayPal is eliminating roughly 20% of its workforce. Block has shrunk to fewer than 6,000 employees, and Coinbase cut 14% of its headcount.
Partner at Schwarzwald Capital.
And hovering over all of it is a single explanation, repeated so often that it starts to remind us of a dot-com bubble — artificial intelligence. But is that actually what’s happening? And more importantly, does it matter if the story isn’t entirely true?
When the story becomes the strategy
AI accounted for 40% of all announced layoffs in May 2026, up from much lower levels earlier in the year. At first glance, it seems like a natural explanation: if the technology handles the routine work better than a human, then why not cut costs?
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But the thing is, when we start looking closer at why exactly these mass layoffs are taking place, a deeper structural problem appears. So far, AI is just a good justification for how the industry communicates these shifts.
Deutsche Bank analysts identified this neat disguise in January. They called it “AI redundancy washing.” Put simply, it’s the practice of attributing workforce reductions to AI adoption when the underlying drivers are far more familiar.
But if it’s not really AI which replaces the workers, then what are the real reasons for all these layoffs? If each company were to be considered individually, it could be anything, from deteriorating unit economics to the pressure of demonstrating operational discipline after years of “growth-at-all-costs.”
Research points to the same explanation: nearly 60% of US hiring managers acknowledged that they emphasize AI’s role in layoffs just because it lands better with stakeholders. Indeed, a headcount reduction could have sparked fears about companies’ growth models, but framing it as a strategic AI implementation makes it sound good.
The productivity paradox
Let’s assume that some of the companies are indeed replacing their workers with AI tools. In this case, there should be numbers to show it. But they don’t share any effectiveness ratios, at least not yet.
A survey of 350 executives at companies with over $1 billion in revenue found that 80% of organizations piloting AI or autonomous technology reported workforce reductions. But after that, many honestly admit that they cut jobs regardless of whether the technology was actually generating returns.
This way, planning to spend another $10 million or more in 2026, companies are betting on a future that hasn’t fully arrived. And trimming headcount in anticipation of a productivity windfall that remains, for most, theoretical.
Even if AI is implemented in a particular organization, it’s mostly in pilot mode, sitting on top of existing infrastructure rather than remaking it. Moreover, the AI payback picture is modest: only 25% of AI initiatives deliver the expected returns, and only 16% reach the scale of the entire organization.
McKinsey’s 2025 global AI survey found the same results. While most firms are using AI in at least one function, nearly 70% are still stuck in experimentation or pilot stages rather than scaling AI across the enterprise. And what’s more upsetting is that no more than 39% reported a significant EBIT impact from the technology adoption.
Where the capital is actually going
If AI isn’t yet delivering the productivity revolution that many executives promised, then where is the industry’s attention? The answer is less exciting than the headlines suggest — only last year, infrastructure and internal business systems received more than $200 billion worth of investments.
For now, fintech companies are under pressure to prove that all the promises made around AI weren’t just another cycle of hype. So instead of reinventing financial services overnight, many are turning inward, looking for ways to make existing operations cheaper and easier to scale.
Even though the AI hasn’t brought the desired effect yet, the shift to automation is still important. For the past decade, fintech has largely been focused on the customer experience to offer a disruptive product, but from now on, more effort will go into the mechanisms behind the product than the product itself.
But this doesn’t mean that the “AI replaced the workers” narrative feels complete. Cutting headcount and replacing employees with bots may look good on a quarterly report, but it’s not much of a strategy. Cost reduction can improve margins in the short term, but it rarely creates lasting differentiation.
So, in this environment, the winning ones will be those asking and answering honestly to a different question: What can we offer the market today that we couldn’t offer a year ago?
The value of AI innovation beyond cost-cutting
Arguably, the more important part of AI adoption isn’t about how it replaces workers at all, but rather about what new value it creates. Historically, the biggest technological shifts rarely created value by simply making existing processes cheaper. They created entirely new products, services, and business models that were impossible before.
Without going too far in search of examples, let’s just remember the Internet. When it first arrived, a lot of people justified investing in it by bringing up “efficiency” aspects, such as digitizing paperwork or reducing communications costs through e-mails.
In reality, though, the Internet went much further than that, creating entirely new business models: online media, social networks, search engines, cloud software, and more. Giants like Google or Amazon did not get to where they are now simply because they optimized their processes. They found success precisely because they built products that simply couldn’t have found success before the Internet became widely adopted.
Now, it’s AI’s turn to go down that road. What innovations it will bring is a story that still remains largely unexplored in fintech, but the potential is massive. In this sense, today’s hyper-focus on workforce cuts is likely going to be just a short phase in a much larger legacy that AI will leave in finance. The true winning move for companies now is to work out how they can use it to better serve their customers in new, never-before-explored ways.
Cost savings may be a measurable and immediate metric, but over time, the true advantage of adopting this technology will come from what it brings to the table, not what it takes away from it.
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