The massive layoffs from big global companies like Amazon and TCS made everyone question — why are companies replacing employees with AI. It’s not because of revenue as reports recorded revenue of $716.9 billion for Amazon in 2026. Pinterest cut up to 15% of its staff and converted that money into AI products.
Why Are Companies Replacing Employees With AI?
Three forces are running at the same time. AI is now the easiest reason to give investors for a layoff. Companies are spending enormous sums on AI infrastructure and need to cut costs somewhere else. And entry-level work is the first thing leaders assume a chatbot can handle.
The figures highlight just how quickly AI-related job cuts have increased. According to reports from Challenger, Gray & Christmas, there are 87,714 job cuts to AI in US companies in May 2026. That accounted for roughly 22% of all announced layoffs which means its already surpassing 54,836 AI-related cuts recorded throughout 2025.
In May alone, companies blamed AI for 38,579 job cuts out of 97,006. This was the largest layoffs since challengers started tracking AI-related layoffs in 2023. The reports suggest that AI remained the highest reason for layoffs, accounting for around 22% of job cuts through August.
Must Read: AI Is Replacing Human Jobs in 2026: Which Careers Are at Risk?
“AI” Sounds Better Than “We Missed Our Numbers”
When a company says they’re restructuring around AI, it looks like the company is heading towards advanced workflow but financial issues sound like trouble.
A Resume.org survey found that nearly two-thirds of companies observed that stakeholders give a positive reaction when they hear job cuts reason is AI rather than financial problems at the company.
There are many companies that admit they frame AI for their big layoffs or hiring slowdowns but the real reason was financial.
The AI Bill Has to Be Paid by Someone
Alphabet, Microsoft, Meta and Amazon are on track to spend close to $700 billion combined on AI infrastructure in 2026, according to CNBC. That money does not appear from thin air. Headcount is the biggest controllable cost on any balance sheet, so it becomes the line item that funds the bet. In many of these cases, the people being let go were not doing work that a model has taken over. Their salaries were simply needed elsewhere.
Entry-Level Roles Are the Easiest Target
AI-related job cuts are not affecting everyone equally. A report from an industry analyst says that 21% of companies have already stopped hiring freshers because of AI, and other firms are also expected to do the same by the end of 2026.
The entry-level jobs such as customer support, data entry and junior coding jobs are the most affected because of AI since it would be easier for AI to handle. So jobs that have repetitive tasks that follow clear instructions are going to vanish by the AI in 2030.
As a result, companies are increasingly using AI instead of hiring people for these positions.
Is AI Actually Doing Your Work?
The companies cut jobs over automation whether or not the technology was paying off, and the firms reporting strong returns were not the same ones announcing AI-related cuts. Most of the companies were not replacing workers with AI on a large scale. However, AI adoption had not yet led to a clear increase in productivity across the economy. Humans are needed because companies expect a lot from AI, but the actual results have not caught up yet.
So companies are betting on efficiency gains that have not shown up yet. Some are already regretting it. Several reports describe firms that cut staff for AI and then quietly rehired.
What This Means for Your Career
When you’re at the start of your career, it’s not be the risk of the model micro-managing your exact role in the next generation. The risk is that the entry-level competition is getting fiercer as companies wait for AI to get working.
India’s biggest IT services company, TCS, reduced its staff by net 23,460 employees in FY2026 to 584,519 from 607,979. Though the company said that its downsizing was due to restructuring, efficiency gains, selective role replacement, and attrition, more generally, the scale of the reduction is evidence of the automation pressures on IT-services employment.
Conclusion
Get trained to build AI into your own workflow, not just talk about it. Companies themselves encourage their workers to upskill and reskill in regards to AI integration.
Build proof of judgment, such as decisions you made, errors you caught and clients you kept, because that is what a model cannot easily show.
So whenever you come across a company layoff headline, ask: is the company outsourcing the work or just shuffling funds? The answer is why you need to be concerned.

























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