The wave of layoffs in the tech sector is real, but AI is not to blame — at least not yet
Technology and layoffs rarely go hand in hand when you are talking about a booming industry. But that is exactly what is happening right now at some of the biggest companies on the planet, and the numbers are hard to argue with.
Oracle, which has been trying to position itself as a major player in cloud computing, recently announced thousands of cuts. Block, the darling of the digital payments space, is eliminating more than 4,000 positions — nearly half of its entire workforce. Amazon and Meta have also announced rounds of layoffs. And to top it off, between 2022 and 2025, the seven giants that make up tech’s so-called magnificent seven barely grew their headcount at all. Total employment in San Francisco, the world capital of the tech industry, has dropped 3% since early 2023.
Sounds contradictory, right? After all, we have always heard that technology was synonymous with opportunity, expansion, and a guaranteed future. So what changed?
The answer making the rounds points to one name: artificial intelligence. The logic seems straightforward at first glance — machines are getting too good at the kind of work tech professionals do, and companies are taking advantage of that to trim their teams. But is AI really the villain of this whole story? Or are we making the classic mistake of pointing the finger at the most obvious suspect before looking at all the evidence?
What we know for certain is that the tech sector is not in crisis. Quite the opposite — it is in the middle of a generational boom driven precisely by artificial intelligence. And that is where things get interesting — and complicated. 👇
The numbers nobody can ignore
When you put together the layoff data from the tech sector over the past two years, the picture that emerges is very different from what most of us expected for this market. In 2024 alone, more than 130,000 tech professionals were let go by major companies around the world, according to Layoffs.fyi, which has been tracking cuts in the sector since 2020. In 2025, the numbers kept climbing, with companies like Oracle, Salesforce, Workday, and Intel topping the list of those making the deepest reductions.
These are not startups going under or companies with serious financial problems. These are profitable giants with healthy balance sheets announcing mass layoffs as part of a deliberate restructuring strategy. And that is the part that confuses a lot of people: if the books look good, why cut so many jobs?
What stands out even more is the profile of the professionals being let go. In previous rounds of cuts, like the ones that happened in late 2022 and early 2023, companies mainly trimmed support, HR, marketing, and operations teams. This time, the cuts are hitting hard in software engineering, product development, and even data teams — the very areas that historically represented the safest core of the tech job market. Programmers, data engineers, systems analysts, and front-end and back-end developers are among the most affected, and that changes the conversation significantly about what is driving these decisions.
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To understand the scale of what is happening, it helps to remember that the tech sector went through a massive expansion between 2020 and 2022, fueled by the pandemic and the boom in investment in digital companies. Many of these companies hired at a breakneck pace, sometimes doubling or tripling their teams in just a few months. When the economic landscape shifted — with rising interest rates and slowing growth — those same companies needed to course-correct. But now, with artificial intelligence available as a productivity tool, the correction comes with an added layer of complexity that goes well beyond simply adjusting headcount.
The real role of artificial intelligence in all of this
Artificial intelligence is, in fact, at the center of many of these decisions, but not necessarily in the way most headlines would have you believe. When a CEO announces cuts and, in the same week, increases AI investments, the immediate takeaway is that machines are replacing humans. And in part, that is true.
Tools like GitHub Copilot, Amazon CodeWhisperer, and OpenAI’s language models are already being used to automate tasks that once required entire teams of developers. What used to take weeks to code can now be generated in hours, with minimal human review. That has a direct impact on how many people a company needs to keep on payroll.
AI enthusiasts argue that the technology is getting extremely good, extremely fast, at the kind of work many tech professionals do. Anthropic’s latest model, for example, turned heads precisely because it demonstrated capabilities that border on unsettling in this regard. Humans, according to this more optimistic corporate view, are becoming redundant for certain roles.
But the issue goes beyond simple replacement. What is happening on a broader scale is a reorganization of work inside tech companies, where AI is being used as a lever to boost the productivity of the teams that remain — not just to eliminate the ones that leave. An engineer with access to the right AI tools can now deliver what previously took three or four people. That changes the hiring equation permanently, not temporarily. Companies will not need less human talent in terms of quality, but they will need fewer people doing the same volume of work. It is a structural transformation in the job market, and it is happening right now, in real time.
That said, pinning everything on AI would be a dangerous oversimplification. Many of the cuts we are seeing originated from business decisions that predated the generative AI boom. Investor pressure for greater operational efficiency, the need to cut costs in a higher interest rate environment, and strategic repositioning by companies that bet on products that did not take off as expected are all significant factors.
AI may be accelerating some of these decisions and giving companies the technical justification they needed, but it is not the root cause of every layoff. The situation looks more like a funnel where multiple factors are converging at the same time, and artificial intelligence happens to be right in the middle of that funnel. 🤖
What CEOs are saying between the lines
According to what company leaders themselves communicate, the tech sector is not in crisis. Quite the opposite. The official narrative is that the industry is going through a transformation so significant that it justifies completely rethinking how teams are organized. When executives talk about restructuring, the words they choose say a lot about what is really behind the cuts.
Terms like operational efficiency, focus on strategic priorities, and investment in AI show up together in internal memos and shareholder letters with a frequency that is no coincidence. They are signaling that the operating model is changing, and that companies are willing to pay the human cost of this transition to reach the new level of productivity that artificial intelligence promises to deliver.
The Block case is especially telling. Cutting nearly half of your workforce is not an incremental adjustment — it is a complete overhaul of the business. The implicit message is that the company believes it can maintain or even grow its operations with significantly fewer people, leaning on automation and intelligent tools. It is a bold bet, and the results will only show up in the coming quarters.
What rarely appears in these announcements is an honest assessment of the human impact these decisions have on the job market as a whole. Mass layoffs at tech companies create a ripple effect: displaced professionals increase competition for available positions, drive down average salaries in the sector, and put enormous pressure on workers who are still employed. While executives talk about transition and adaptation, the workers who are out of a job have to deal with a market saturated with equally qualified candidates competing for fewer opportunities.
This tension between the corporate narrative and the day-to-day reality facing professionals is one of the least discussed aspects of this crisis.
There is also an important strategic dimension involving how companies position themselves relative to their competitors. No major tech company wants to fall behind in the AI race. So when a company cuts costs in traditional labor and redirects those resources toward developing and adopting intelligent tools, it is making a long-term bet. The risk is real: if AI does not deliver the expected returns at the pace investors demand, these companies will have lost valuable human capital that took years to build. And rehiring, when the cycle turns again, comes with a steep cost that does not always show up on efficiency spreadsheets. 📊
San Francisco feels the impact on the ground
The most visible barometer of this transformation is San Francisco, the city that for decades was synonymous with opportunity in tech. With total employment in the region — including roles not directly tied to tech — registering a 3% decline since early 2023, the impact is not confined to the offices of major companies. Restaurants, coffee shops, transportation services, and the local real estate market are all feeling the effects.
Anyone walking through the SoMa district or the Financial District will notice more empty commercial spaces than there were two years ago. Coworking spaces that once had waiting lists are now offering discounts to attract new members. The dynamics of the city have shifted, and although San Francisco has been through boom-and-bust cycles before — the dot-com bubble bursting in the early 2000s being the most commonly cited example — this time feels different. It is not a bubble popping. It is an entire industry reconfiguring its inner workings while continuing to grow in revenue and market valuation.
This disconnect between company financial performance and the number of jobs being created is a relatively new phenomenon that deserves attention. Historically, when tech companies grew, they hired. Now, growth is decoupling from job creation, and artificial intelligence is one of the factors making that decoupling possible — even if it is not the only one.
The job market emerging from this transformation
Even in the middle of all this turbulence, there is a parallel narrative worth paying attention to: new roles are being created precisely because of artificial intelligence. Positions like prompt engineer, AI ethics specialist, machine learning systems architect, and training data analyst were practically nonexistent five years ago and are now showing up with increasing frequency on job platforms.
It is not that the market is shrinking in a straight line. It is reorganizing, and those who see this as a transformation — rather than a threat — have a better chance of navigating this transitional period successfully.
The big challenge is that this reorganization is not happening at the same pace for everyone. Professionals with years of experience in legacy technologies who have not had access to training on modern tools are feeling the weight of the cuts more heavily. Meanwhile, those who were already working with data, automation, and modern software development are finding new opportunities, even if the market is more competitive. The learning curve around AI is becoming, in practice, a differentiating factor on a resume, and companies are using it as a selection criterion both for new hires and for deciding who stays during a restructuring.
What tech professionals should be watching in this landscape
- Familiarity with generative AI tools is shifting from a nice-to-have to a baseline requirement for many positions
- Skills in integrating traditional systems with artificial intelligence solutions are in high demand
- The ability to work with fewer resources and more automation is increasingly valued by recruiters
- Areas like AI security, data governance, and responsible model development are gaining ground
The experiment is still underway
What is clear, looking at the full picture, is that the tech job market is going through one of the biggest transformations in decades. It is not the end of employment in tech, but it is certainly the end of a specific model of how that work was done and compensated.
The companies cutting jobs today are betting that with fewer people and more AI, they can deliver more. That experiment is still underway, and the results will take a few years to become clear. Until then, the sector will continue in this mode of constant adjustment, with waves of layoffs and hiring that reflect not only the evolution of the technology but also the bets and miscalculations of the people making the decisions.
The central point remains the same one The Economist raised in its original piece: the tech jobs crisis is real, but blaming artificial intelligence — at least right now — is premature. AI is part of the equation, not the entire equation. And understanding that difference may be what separates a surface-level take from a genuinely useful read on what is happening with the future of work in technology. 🔄
