AI, economic pressures and other causes of Big Tech layoffs

Two-thirds into 2026, layoffs in the tech sector have surpassed the total of jobs cut in 2025.

As of August, 284 tech companies have laid off 127,180 workers. Last year, 278 tech companies laid off 122,606 employees, according to Layoffs.fyi. Competing narratives swirl around Big Tech layoffs. Some executives publicly attribute the job cuts to AI, either in the name of efficiencies gained or in the hopes of getting there in the future. Skeptics cry AI washing. General economic pressure and a weak labor market cast a long shadow.

This wave of layoffs is not the first. Big Tech companies cut large swaths of jobs over many different periods in the past, sparking debate. Is this wave akin to previous ones, or is it entirely different?

As CIOs at other enterprises watch these layoffs unfold, they must consider their own approach to AI investments and workforce planning.

Tech layoffs over the years

Various factors have driven each cycle of tech sector layoffs over the last several years. Crunchbase tallied up the approximate U.S.-based tech company layoff counts for the past several years, which are as follows:

• 2022: 93,000
• 2023: 191,000
• 2024: 95,667
• 2025: 127,000

Layoffs in 2022 and 2023 came on the tail end of the COVID-19 pandemic. Tech companies cut thousands of jobs in response to macroeconomic concerns.

In 2024 and 2025, AI entered the equation. Tech companies started to pour more money into the technology and restructure their teams against the backdrop of ongoing economic uncertainty.

The same themes of AI and uncertainty persist in 2026. Yet, the current wave of layoffs differs from past waves in the growing potential for structural workforce transformation.

"Leaders have the decision point of: Do I need a human to do it, or can I have an AI agent to do it? We've never had that before," said Cindi Howson, chief data and AI strategy officer at ThoughtSpot, a business intelligence and analytics company.

The forces behind the current wave of Big Tech layoffs

It is impossible to talk about the current wave of layoffs without bringing up AI and its ability to automate work. But zoomed in, the forces behind the Big Tech layoffs are more complicated.

"I'm still not seeing a correlation between AI productivity and those layoffs," said Grant Zallis, managing partner of emerging technology at executive recruiting firm DHR Global.

Erika McEntarfer, a labor economist, research scholar and distinguished policy fellow at the Stanford Institute for Economic Policy Research, dug into AI's effect on jobs. She sees a divide between company messaging and AI maturity.

"There is a real gap between the way companies talk about AI, their public messaging about AI and actual deployment maturity," she said. "If you're laying people off without mature, ready-to-go AI agents that can actually replace those workers, then you're not really laying people off because of AI."

But just the perception that AI can automate entire swaths of jobs can be a boon for companies.

"Wall Street is rewarding those organizations that [make] cuts because of AI. They're seen as AI-forward," Howson said.

In February, Block laid off more than 4,000 people -- almost half of its workforce. Block CFO Amrita Ahuja positioned the big cut as part of "an opportunity to move faster with smaller, highly talented teams using AI to automate more work," CNBC reported. Block's stock jumped 24% after the announcement.

Layoffs can even be a tool to drive a workforce to get on board with AI. Snowflake CIO Mike Blandina said he made cuts to the company's software engineering team at the beginning of the year with that exact goal in mind, The Information reported.

Being AI-forward requires resources, and layoffs are an expedient way to get them.

"Big Tech, they're deciding that they would rather invest in compute infrastructure … or in LLM training rather than people," Howson said.

Many Big Tech companies, such as Meta and Oracle, are undergoing significant restructuring to sustain massive AI infrastructure spending and demonstrate efficiency gains.

Oracle had approximately $55.7 billion in Capex for the fiscal year 2026. It is gearing up for more workforce reductions, following its spring layoffs.

Meta also cut 8,000 jobs back in the spring in the name of efficiency and offsetting its other investments. Its Q2 Capex was $31.08 billion.

What CIOs should watch for

Big Tech layoffs are impossible to ignore. These companies represent a vital piece of the U.S. economy. Each time they make big cuts, thousands of people are back out in a tough job market. But that doesn't mean Big Tech is creating a blueprint for other enterprises to follow.

"Big Tech will decide one thing. What Amazon decides is not necessarily the same as what, say, a bank or an insurer or a healthcare provider or a retailer decides," Howson said.

As CIOs watch how Big Tech hires and fires talent, they must consider the following points for their own AI workforce planning and investments.

1. Complementary investments

While Big Tech may point to layoffs as a sign that AI is powerful enough in its efficiency and capabilities to replace people, getting value from AI isn't as simple as buying a tool and cutting head count.

"Firms need to make a lot of complementary investments to make enterprise technology work," McEntarfer said. "There was some, perhaps, magical thinking that all that would need to happen is buy some commercial licenses for the staff and productivity would magically appear, and everybody's figuring out that's not really how this works."

2. Emergence of new roles

The expectation is for AI to eventually create more jobs than it eliminates. Gartner predicted the pendulum will swing to more job creation in 2028.

As Big Tech makes cuts, CIOs can consider which new jobs might emerge and which their enterprises will need to fill. For example, an AI literacy coach is a new role Howson is starting to see.

3. New org charts

In addition to creating new roles, AI is reshaping organizational structures. CIOs at companies undertaking this kind of compression need to be careful not to become the scapegoats if the cuts don't yield the desired results, Zallis said.

"The danger that CIOs have to watch out for is being asked to automate processes in systems that they don't fundamentally understand," Zallis said. "Unless they have a really close relationship with their COO, with the people who own those workflows, the danger is compressing org charts in areas where you actually can't do that."

4. Governance

As AI changes organizational structures through layoffs, restructuring or a combination of the two, CIOs must keep governance at the core of AI initiatives.

"Where does a CIO really keep their job and really elevate themselves?" Zallis said. "It's on the governance side, security side [and] accountability for what the systems do."

Balancing innovation with workforce stability

CIOs walk a tightrope. They must be at the forefront of pushing AI innovation, but their workforces exist in an environment littered with examples of Big Tech companies proclaiming AI is more efficient than human workers.

"If you look at big enterprises, they're just not great at rapid change, regardless of the nature of that change," Zallis said. "When you combine that with an antsy board who are expecting AI to drive efficiency because they're afraid of getting left behind, you have a perfect storm."

Layoffs might please Wall Street and appease those antsy boards for now, but if AI initiatives can't take on the work and more people are let go, CIOs are facing a long-term problem.

"If you're letting those people go, you're trading a single quarter of margin for, in my mind, really a year of capability, the speed at which people are executing on some of these things…in many cases is going to come back to haunt them," Zallis said.

CIOs and their enterprise peers are faced with the prospect of planning for the uncertain future of AI. Uncertainty is likely to lead to more layoffs, and each enterprise must determine whether deep job cuts are the answer to its AI innovation and workforce goals.

"Everyone can chase the short-term profits and stock boost, but is that really the right thing to do in the long term?" Howson said. "Building a durable company is a long-term play."

Carrie Pallardy is a freelance journalist with experience writing in cybersecurity, technology and healthcare. She currently covers a wide range of issues relevant to today's CIOs and IT leaders.