The headlines say the job market is holding steady. But the devil is in the details.
Quiet buyouts, strategic tech layoffs, and hiring freezes are sweeping through some of the world’s most profitable companies.
The signs are pointing towards a new type of corporate operating model, and artificial intelligence is at the center of it.
Why are companies cutting jobs in a growing economy?
Since early 2025, companies like Google, Microsoft, Amazon, and Procter & Gamble have eliminated thousands of jobs.
The pattern is not limited to one sector. Cybersecurity firms, education platforms, retail giants, and media companies are all doing the same.
Most reports cite “cost-cutting” or “efficiency.” But the macro data doesn’t fully support that narrative.
The US labor market appears stable. April jobs data beat expectations. Inflation has cooled. Yet corporate layoffs continue in waves.
Source: CNBC
The same pattern is visible in China, where job fairs for new graduates are oversaturated and automation is growing fast in marketing and software engineering.
This is not a cyclical pullback. It’s a structural adjustment.
The economic pressure from tariffs is part of it, especially after President Trump’s trade policies resumed in 2025, raising import costs and prompting new rounds of price hikes.
But the deeper force is the rise of enterprise-level AI. And it’s real. Companies are not just experimenting with AI.
They’re redesigning entire departments around it.
AI isn’t taking jobs – it’s replacing departments
Google has spent over $75 billion this year on AI infrastructure, according to the Wall Street Journal.
That includes the development of “AI Mode” for search, a restructuring of internal learning tools, and massive capital outlays across engineering and research.
To fund this shift, the company has quietly offered voluntary buyouts across Search, Ads, HR, Legal, and Communications.
Executives have framed it as a “supportive exit path,” especially for those not aligned with the company’s new direction.
In reality, it is a managed transition toward an AI-first workforce.
Microsoft has followed a similar pattern. In May, it eliminated 6,000 positions across all divisions, unrelated to performance, with the stated goal of removing management layers.
Klarna cut 40% of its workforce after AI replaced over 700 customer service agents.
Shopify now requires teams to justify why a job can’t be automated before they can make a new hire.
Salesforce says internal AI tools have reduced the need to hire more engineers and customer service staff, allowing the company to save $50 million this year by redeploying hundreds of roles instead of expanding headcount.
Meta is also in the middle of a sweeping AI overhaul.
The company plans to spend up to $72 billion this year to automate internal systems, replace human-led reviews, and fully transform its advertising business with generative tools.
At Meta, everything from privacy checks to campaign creation is being rebuilt through AI to lower costs and reduce reliance on outside agencies.
In China, the situation is more public. Meituan reported that 52% of new code in May was generated by AI, up from 27% just two months earlier.
Zhou Hongyi, founder of 360 Security, announced he plans to eliminate the entire marketing department and use generative AI tools to handle communications. He claims it will save “tens of millions per year.”
This is not about saving a few percentage points on headcount. It’s about rebalancing how work gets done.
White-collar work is no longer the default entry point
AI adoption is creating a new labor bottleneck, especially at the entry level.
Job cuts are not just reducing teams. They are removing the traditional onboarding ramp for young professionals.
March and April job growth in the US was revised down by 95,000 positions.
According to ADP, private-sector hiring hit its lowest level in over two years.
New graduates are finding it harder to enter the job market.
At the same time, internal mobility is slowing, with incumbent employees choosing to stay put.
In China, the Ministry of Finance has allocated nearly $9.3 billion in employment subsidies, and a new pilot program is testing robots for elderly care.
But the cultural and structural issues run deeper.
Competition remains extreme, overtime is normalized, and many college graduates are turning to livestream selling or gig work in the absence of stable employment.
In both countries, the message is clear: if you don’t know how to use AI, your job prospects are limited.
Employers are no longer willing to train from scratch. They expect AI fluency up front.
Are buyouts the new tech layoffs?
Since early 2024, Google has changed its downsizing strategy from mass layoffs to voluntary exit programs.
In January 2023, the company faced backlash for cutting off access to internal systems without warning.
Since then, it has offered buyouts across hardware, HR, legal, and now search.
The same offers now come with office mandates. Remote workers living within 50 miles of a Google office are required to return on a hybrid basis.
Those unwilling to do so are subtly encouraged to take the buyout.
This trend is not unique to Google. Across the tech sector, return-to-office policies now serve as filters.
They allow companies to reduce headcount without direct termination.
The result is a cleaner exit path, especially for mid-level employees misaligned with new performance expectations.
This shows that work-from-anywhere flexibility is no longer considered a baseline perk. It’s a variable in cost analysis.
What comes next?
The first clear sign of the next phase is the disappearance of entry-level white-collar jobs.
These roles are being absorbed by software, outsourced, or removed altogether.
New hires will be fewer, and those who remain will be expected to integrate AI tools into their daily workflows.
Anthropic CEO Dario Amodei has warned that AI could eliminate 50% of entry-level white-collar jobs in the next five years.
He predicts unemployment could reach 10-20% unless governments intervene. He proposed a “token tax” on large AI models to help redistribute productivity gains.
Meanwhile, in both the US and China, labor policies have not caught up. The conversation is still about reskilling and subsidy programs.
But the deeper issue is that the structure of employment itself is changing.
We are moving toward a world where productivity does not require people in the same way it used to.
AI is not just a tool. It’s becoming the template. And tech companies are rushing to adopt it.
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