Tech Layoffs on Track to Hit 1M Since 2022: Why We Should Be Worried

Tech layoffs this year have just hit over 70,000, with an estimated 80 companies affected. This is just in Q1, and is a 140% increase from last year’s Q1 numbers. 

If these tech layoffs continue to build momentum, we’re likely to see the number of cut jobs reach over 120,000, totalling a staggering 1M cuts since 2022. Let’s break it down.

A Gruesome Q1

For many in the world of tech, Q1 has now reached its end. Unfortunately, 71,447 tech employees were laid off during the quarter, which is 140% more than 2025’s 29,845 employees, according to Layoffs.fyi. 

Some of the layoffs announced last quarter were in the tens of thousands, including Oracle’s global cuts last week and Amazon’s 16,000 cut roles in January. 

Although layoffs rounds within tech are more normalized now, with companies typically undergoing one to two rounds a year, they have not come without scrutiny, especially as artificial intelligence has seemingly been a key player in many of them. 

Data suggest that over 120,000 jobs have been lost due to AI since January 2025, with varying debates on how much tech falls into that category. The degree to which AI has been driving these layoffs has also been debated, spurring conversations around whether they are AI-driven or AI-influenced, and whether we should even call them “AI layoffs” at all. 

Salesforce’s Slice of the Pie

In Q1, Salesforce announced that it was laying off under 1,000 employees – its latest major layoff effort since last February, when it laid off over 1,000 employees. The end of January marks the end of Salesforce’s fiscal year, and February is typically when it announces its results, and is an important time for the company to prove to investors and analysts that it has had a successful year.

It is likely that Q4 is when leadership finalizes budgets, and layoffs are announced shortly after this to directly impact the next fiscal year’s cost base. Essentially, cutting roles in January or February can lead to immediate improvement in margins for the new year. 

Mid-year layoffs can signal course corrections or company panic, so Salesforce’s layoff decisions are likely very strategic. 

On Track for 1M+ Layoffs 

As it currently stands, there have been just under 780,000 layoffs since 2022. This collates:

• 165,269 layoffs in 2022
• 264,320 layoffs in 2023
• 152,922 layoffs in 2024
• 124,201 layoffs in 2025
• 71,447 layoffs so far in 2026

So far, 2026 is tracking similarly to 2024 levels, with only a 24% difference between 2024’s Q1 numbers.

If 2026 continues on its current trajectory, we will likely finish this year with 120,000-155,000 total layoffs, bringing the total number of cuts since 2022 anywhere between 900,000-935,000. Hitting the 1M mark could come as early as the end of Q1, 2027. 

What Does This Mean for the Rest of the Year?

At the end of last year, I predicted that if AI adoption keeps lifting productivity and leadership keeps emphasizing “efficiency + optimized structure,” layoffs would become the ultimate consequence. At present, this is something I still firmly believe.

I did, however, say that further layoffs should not necessarily be expected, but that does not seem as plausible now, especially if AI advances fast enough to convince businesses like Salesforce that the more cost-effective way forward is with an automation tool, or it can be used as a scapegoat.

We may never truly know the real reasons behind laying off employees, but it appears as if these layoffs have become as common as announcing quarterly results. To say more were not on the way would not only be wishful thinking, but a complete dismissal of how impacted these companies are by investor pressure and the rate of technological advancement.

Final Thoughts

Being on track to reach 1M layoffs since 2022  is not a prospect we should be excited about, and it should highlight how dramatically the tides of tech have shifted over the last few years. 

Unfortunately, data does suggest that more layoffs are coming, and although we can try to predict when, ultimately, it will vary company to company. It should now be regarded as a common business practice and heavily considered when deciding whether or not to start pursuing or continue pursuing a career in this industry.