The tech industry’s favorite two-word explanation in 2026 might be “because AI.” Convenient, neat, investor-friendly — and maybe a little too neat.
New reports suggest the sector shed 78,557 jobs between January 1 and early April 2026, with nearly half of those cuts linked to AI and automation. That sounds like the beginning of a massive labor reset. But scratch the surface and the picture gets messier: some experts say AI is genuinely starting to reshape work, while others argue it is being used as a polished excuse for old-fashioned cost cutting and bad planning.
The numbers are ugly, even by tech’s standards
Layoffs have become such a routine part of tech news that they almost risk sounding normal. They are not. Nearly 80,000 lost jobs in just the first quarter of 2026 is a brutal figure, and more than three-quarters of those affected roles were in the United States.
What stands out even more is the AI angle. Of the total layoffs, 37,638 positions — about 47.9% — were reportedly attributed to reduced demand for human workers because of AI and workflow automation.
That is the kind of statistic that practically writes its own headline. It also raises an obvious question: are companies actually replacing workers with productive AI systems, or are they simply pinning layoffs on the hottest buzzword in business?
AI may be changing jobs — but maybe not that fast
Babak Hodjat, Cognizant’s Chief AI Officer, offered a much more cautious view than the headlines might suggest. His take is that companies may be invoking AI before they are truly seeing the operational gains needed to justify those cuts.
In other words, some executives may be acting like AI is already a fully trained, infinitely patient digital employee. Reality, as usual, is less cinematic.
Hodjat’s argument is that the real workforce impact from modern AI may still be six months to a year away, once companies begin seeing measurable productivity gains. Until then, blaming AI for layoffs can sometimes look suspiciously like a tidy narrative for broader restructuring.
And frankly, that tracks. Tech has never needed much encouragement to overhire during boom times and overcorrect when the spreadsheets start sweating.
Checkout my other article: AI Didn’t Kill Journalism—Humans Did
The “AI did it” defense is getting popular
Hodjat is not alone in questioning the narrative. OpenAI CEO Sam Altman has also suggested that some companies are engaging in what might be called “AI washing” — using artificial intelligence as a public-facing explanation for layoffs that would have happened anyway.
That matters because not all layoffs are created equal.
Some cuts may reflect legitimate shifts in how work gets done. Repetitive tasks in coding, support, and operations are clearly becoming more vulnerable as automation improves. But some layoffs may have far less to do with technological progress and far more to do with:
- weak business performance
- overexpansion during better market conditions
- pressure to improve margins
- the desire to redirect spending into AI infrastructure and data centers
Oracle is one example hovering in the background of this discussion, reportedly cutting more than 10,000 jobs while channeling savings toward data center investments. That is still an AI story, but not necessarily a simple “the bot took your desk” story. Sometimes the machine is not replacing you directly. Sometimes your budget is just being reassigned to feed the machine.
Also read: AI and Humans: The Third Relationship
The warnings are getting louder
Even if some companies are overstating AI’s immediate impact, there is no shortage of people warning that real disruption is coming.
Executives like Anthropic CEO Dario Amodei and Ford CEO Jim Farley have already floated alarming predictions about AI wiping out large portions of entry-level white-collar work in the United States. Research is also beginning to support the idea that junior roles may be especially exposed.
That is what makes this moment so unsettling. Entry-level jobs are not just low-cost labor slots. They are the training ground. They are where future specialists, team leads, and managers start building experience.
Cut too deeply at the bottom of the ladder, and companies may save money today while quietly sabotaging their own talent pipeline tomorrow.
It is the corporate equivalent of eating the seed corn and then acting surprised next season.
Entry-level workers look especially vulnerable
This is where the AI layoff conversation gets more serious than the usual quarterly downsizing drama.
Several studies and industry analyses suggest that early-career roles in coding, customer service, and administrative work are already under pressure. That makes intuitive sense. These jobs often involve structured, repeatable tasks — exactly the kind of work current AI systems handle best.
But there is a strategic downside to cutting too many junior roles.
A company still needs people who understand the business, grow into more complex responsibilities, and eventually become experienced operators. You cannot magically hire a workforce made entirely of senior talent. Somebody has to become senior first.
That is why a short-term AI efficiency play could become a long-term management problem. If firms eliminate too many early-career jobs now, they may find themselves with a future shortage of trained mid-level employees who actually know how the business runs.
Not every company is slamming the brakes on hiring
For all the doom-laden predictions, the story is not universally bleak.
IBM is reportedly moving in the opposite direction, tripling its entry-level hiring in 2026. Its reasoning is refreshingly grounded: AI can handle parts of junior-level work, but organizations still need human judgment, adaptability, and domain understanding.
That view is also supported by European Union data suggesting that companies investing in AI are often more likely to hire, not less.
That does not mean AI is harmless to employment. It means the effect may be more complicated than “automation in, humans out.” In some cases, AI can reduce certain tasks while increasing demand for workers who can supervise systems, apply domain expertise, and integrate the tools into real business processes.
The real shift may not be a collapse in hiring, but a redefinition of what makes a worker valuable.
Cognizant’s approach points to another path
Cognizant is also worth watching here because its business is deeply tied to human labor through outsourcing and services. If any company had a reason to frame AI as a headcount-reduction engine, it would be one like this.
Instead, the company appears to be leaning toward retraining rather than cutting. It has built AI labs in San Francisco and Bengaluru and is developing custom AI agents for clients, especially where off-the-shelf tools fall short on performance or security.
That is an important distinction. Enterprise AI is not just about plugging a chatbot into Slack and calling it innovation. Many corporate use cases require customization, oversight, and people who understand both the business problem and the technology.
According to Hodjat, Cognizant does not expect these AI efforts to trigger layoffs. The company instead plans to train existing staff and continue bringing in junior talent.
That may end up being the more durable model: use AI to augment workers, not erase them.
What this means for the industry
The headline number — nearly 80,000 layoffs, with almost half tied to AI — is undeniably alarming. But the deeper lesson is that the industry is still in an awkward transition phase.
AI is real. The disruption is real. But the accounting around it is also getting fuzzy.
Right now, “AI-driven layoff” can mean several different things:
- a job genuinely replaced by automation
- a company restructuring in anticipation of future AI gains
- a cost-cutting move dressed up as technological inevitability
- a budget shift from payroll to infrastructure
Those are not the same thing, and lumping them together makes the labor picture harder to read.
The takeaway
AI is starting to reshape tech employment, but the story is not as simple as robots marching workers out of the building with cardboard boxes.
Some layoffs are likely tied to real automation. Others look more like strategic repositioning — or plain old business cleanup with a futuristic label slapped on top. The companies that treat AI as a tool for retraining and restructuring work, rather than just trimming payroll, may be the ones best positioned in the long run.
For workers, though, the message is less comforting: the disruption is here, the definitions are slippery, and the “entry-level” rung on the ladder is looking increasingly fragile.
Which is not ideal, considering every industry still needs a next generation of talent — even the ones busy automating the welcome mat.
It’s a really interesting point about AI being used as a convenient explanation. I think the root problems are much more complex than just one technology.