The widespread layoffs within large tech companies are becoming more of a long-term trend rather than a mere temporary solution.
Big names in the industry, such as Meta, Microsoft, and Amazon, lay off thousands of employees, investing millions into developing artificial intelligence. Such an approach seems controversial, but it is not. Artificial intelligence is not only used to provide consumers with better products. This technology is employed to save money on the workforce while boosting production.
So far in 2026, more than 92,000 tech employees have been fired. Overall, since 2020, nearly 900,000 employees have had to leave their workplaces. Such numbers cannot be explained by minor alterations within a company’s internal structure; instead, a bigger picture should be considered.
The AI-Driven Recalibration of the Modern Workforce
During the pandemic, tech companies experienced a significant influx of customers. With the pandemic fading away, such high demand slowed down. However, technological advancements in artificial intelligence have increased rapidly. Thus, tasks that required a whole team could be completed using fewer employees along with artificial intelligence.
It can already be seen from what is going on within companies. Meta will reduce its workforce by around 10% and scrap thousands of job openings. Microsoft is also offering early retirements to a significant portion of its U.S. employees. Amazon has reduced tens of thousands of jobs already. All these actions have something in common. They involve doing more while reducing staff.
Moreover, such decisions are no longer confined to tech firms. The recent layoffs at Nike, mostly focused on the firm’s technology department, prove that point. While developing new technologies and digitizing businesses, organisations also try to find ways of making their systems work with a minimal number of people.
At the moment, there are various programs that help automate coding, customer service, and even analysis. Thereby, the demand for entry-level and general employees falls, and so does the need to hire them. However, hiring managers still search for specialists in AI.
This results in an imbalance. Employment is being reduced at a rate higher than new employment creation. The new jobs also require different skill sets, further complicating matters for employees.
AI, Productivity, and the Modern Startup Landscape
Some proponents contend that this is part of a natural process. Every advancement in technology comes with job displacement and creation. The popularity of smartphones brought about mobile app developers, while the development of the internet has seen the creation of IT jobs.
This remains true, although the rate of progress differs from previous advancements. Artificial intelligence is advancing much more quickly than other innovations. There are yet unanswered questions regarding its potential capabilities.
Startups are the perfect case study in this area. Startups can now create and grow their products far faster than ever before. A company of fifty people can generate revenues that previously took many more people to achieve. There is an increasing expectation from investors in this area.
As a result, large corporations are feeling the heat. With startups being able to run on smaller teams, large organisations need to do the same thing. This usually means downsizing.
Meanwhile, investments in AI keep growing. Large tech companies are forecasted to spend hundreds of billions on AI-related infrastructure this year. Investments go into data centres, chips, and model training. These investments are made for the future, when AI is expected to generate additional growth, despite cutting jobs in the process.
Meta-Analysis, The AI Paradox and Workforce Stagnation
From the point of view of employees, this generates insecurity. The job satisfaction index in the industry is down. Fewer employees leave their jobs voluntarily. Many remain in place due to fears about reemployment. This may impact job satisfaction and career development negatively.
The employer’s approach to evaluating performance is evolving as well. With less voluntary turnover, companies will be more inclined to force low-performing workers to leave. One way to do this is through layoffs, while a stricter evaluation system would also have a similar effect.
Thus, we have a workforce experiencing limited movement. Workers are witnessing swift change but not actively participating in it. They understand the ability of artificial intelligence to increase productivity, but they are also witnessing automation taking over work that they previously did.
This is a unique period since the creators of the technology are its primary targets. Software engineers, analysts, and design specialists work with AI tools every day. However, at the same time, there is always a chance that the very same technology will render their skills obsolete.
The final result remains unknown. While there will certainly be new jobs, they will need competencies that not all employees might have. The process can last for several years, but different people will progress differently.
However, one thing is certain now. The business environment is changing into a leaner one. More results are achieved despite fewer personnel. AI technology lies behind the transformation.
But this is not just another wave of recruiting. This time, a fundamental change takes place.
