Talk about AI causing layoffs started back in 2024.
At that time, many companies were under pressure because of the global economy. Budgets were tight, investors demanded better efficiency, and companies wanted to look “AI-driven” and modern. In this situation, layoffs were often explained as “AI optimization.”
But did AI really automate all of this work? It’s hard to say for sure. However, we can look at how AI is actually being adopted in companies.
According to McKinsey’s The State of AI in 2025, only about a third of companies have even begun to scale AI beyond pilots, and just 7% have deployed it across the whole organization, even though 88% already use AI regularly in at least one function.
From my own experience talking to AI enablement specialists, attending conferences, and doing research, the real level of AI adoption inside companies is often even lower than what companies publicly claim.
Having a ChatGPT subscription or an AI assistant that helps with emails does not mean AI is fully integrated into company workflows. The field is moving very fast, and standards keep changing. What was “best practice” a few months ago can already be outdated. As a result, adoption is uneven: some teams use AI agents heavily, while others don’t even know what MCP or agent workflows are.
Recently, I wrote an article called “Will AI Replace Software Developers?”, where I explained why AI will not simply replace developers. And I still believe that AI itself will not take your job.
However, there is an important point I didn’t fully cover there. Your job might not be replaced by AI, but it can be reduced by management decisions.
Does AI make developers faster? Yes, it does. But some managers take a very simple view: if each developer produces more code, we can reduce the team size. The problem is that writing code is only a small part of software development. With AI, we do write more code. But we also spend more time on planning, testing, code review, validation, and system design discussions. Productivity increases, but it doesn’t mean we need fewer people in a linear way.
Even if leadership understands this and avoids the AI hype, there is another issue: the cost of using AI.
Most companies already operate under tight budgets. Now they also need to pay for AI models, infrastructure, integrations, and trainings.
Many people forget that today’s AI pricing is largely held up by investors. Sam Altman has admitted that OpenAI loses money even on the $200 ChatGPT Pro subscription, and providers have kept prices below cost for years to capture the market. Even now, the monthly cost for advanced AI tools can become significant for large companies. This means companies are not only paying for growth, but also for maintaining their AI strategy.
That’s why we still see layoffs in tech. According to layoffs.fyi, the industry cut around 122,500 jobs in 2025, fewer than the 153,000 in 2024, but the wave has not stopped. AI was named as a direct reason in less than 8% of announcements, so it was rarely the only factor. Often, it’s not because AI fully replaced people, but because companies need to reallocate budgets to expensive AI infrastructure and projects.
So when we hear about mass layoffs, it’s important to understand: AI is rarely the only reason.
More often, it’s a combination of:
- global economic pressure
- investor expectations
- budget constraints
- AI hype and unrealistic expectations
- rising infrastructure and model costs
All of these together are shaping today’s job market.
I don’t believe AI will replace most professionals. But I do believe AI is already adding pressure to an already difficult market.
The good news is that these cycles don’t last forever. The tech industry has gone through crises and corrections before. Over time, things stabilize, companies adapt, and the job market finds a new balance.
No one is safe from layoffs.
But your skills, reputation, network, and ability to adapt greatly increase your chances of quickly finding a new and even better opportunity. So keep learning, keep building your skills, stay active on LinkedIn, and stay aware of how the industry is changing.
In the long run, that is still the best protection against change.
