Microsoft’s recent decision to cut roughly 6,000 jobs (about 3% of its global workforce) isn’t just about streamlining management. It’s part of a much bigger, and more unsettling, story: the quiet rise of AI-induced job disruption.
Officially, the company has cited a familiar rationale for the move: simplifying organizational layers to boost efficiency. But dig a little deeper, and look at what Microsoft executives are actually saying, and the narrative gets a lot more complex.
To unpack the implications, I spoke to Marketing AI Institute founder and CEO Paul Roetzer on Episode 148 of The Artificial Intelligence Show, where he made one thing clear:
These aren’t just cyclical layoffs.
They’re the latest signal that AI is beginning to fundamentally reshape the workforce.
The layoffs hit technical talent the hardest. In Washington state, more than 40% of the 2,000 employees let go were software engineers, with product managers and technical program managers also disproportionately affected.
Customer-facing roles? Largely untouched.
That disparity is no accident, says Roetzer. It’s a sign that Microsoft (and other tech giants) are reallocating resources in anticipation of AI transforming how core work gets done. CEO Satya Nadella recently revealed that AI now writes up to 30% of code on some projects. And according to Microsoft CTO Kevin Scott, that number could hit 95% by 2030.
Put simply: If AI is increasingly building the software, companies need fewer people to do that job.
Roetzer first flagged this trend back on Episode 145 of the show. He called it “quiet AI layoffs”—job cuts that are ostensibly about cost savings or restructuring, but are actually driven by a belief that AI can replace (or reduce the need for) human labor.
With Microsoft’s latest move, the trend is getting harder to ignore.
The company has committed an estimated $80 billion this fiscal year to AI infrastructure—primarily to fund data centers for its cloud and AI services. And they’re already using AI to automate key business processes.
"It's not like we're drawing some difficult to find conclusion here," says Roetzer.
"If the CTO of the company is saying that within five years we expect 95% of all code to be written by AI, then what do you need a bunch of engineers for?”
Still, betting too hard on AI without the right plan can backfire. Just ask Klarna.
The Swedish fintech made headlines last year when it froze hiring and replaced large swaths of its customer support team with AI. But last week, the company reversed course, admitting the quality just wasn’t there.
Klarna’s CEO told Bloomberg that the company had over-prioritized cost savings, leading to diminished service quality. Now, they’re on a hiring spree to rebuild human support. For Roetzer, it’s a classic case of focusing on the wrong thing when it comes to AI transformation.
"We shouldn't be thinking first and foremost about getting rid of all the people," he says.
Unfortunately though, other industries are likely to face similar situations. Software engineering is only the first domino. As Roetzer points out, AI has compounding value when used to automate code, because the code itself powers further automation. But the same logic will inevitably extend to other fields, like legal, HR, accounting, healthcare, and more.
"Software engineers who are writing code are basically the canaries in the coal mine right now for AI job disruption," he says.
Many other industries will look to do exactly what leaders in engineering already are doing: start automating parts of workflows with AI, then increase that automation as much as possible until it comprises the bulk of certain jobs.
Yet despite mounting evidence, many leaders are still in denial. They assume disruption is far off—or that AI won’t affect their sector.
Roetzer disagrees.
“We’re watching it happen. Right now," he says. “And people still want to pretend like this isn’t going to affect jobs and the economy.”
Roetzer stresses that this isn’t about sounding the alarm for alarm’s sake. It’s about pushing leaders to be clear-eyed, strategic, and human-first in how they approach AI.
That means not rushing to eliminate jobs without fully understanding what AI can—and can’t—do. It also means not dismissing these changes as overhyped.
“The greater risk is that you just sit around for three years to see what happens when all these other companies are figuring this out," he says.
"Trial and error is going to lead to the breakthroughs and the innovations that are going to obsolete your company if you do nothing."
So whether you’re a software engineer, a team lead, or a CEO—now is the time to pay attention.