The global tech industry is undergoing an unprecedented restructuring, and its ripple effects are being felt deeply in countries like India, which for decades functioned as the world’s IT export machine.

A recent deep-dive video by The Thought Effect, titled “Why Tech Companies Don’t Want Indians Anymore?”, explores a perplexing modern phenomenon: tech giants are pulling in record revenues while simultaneously laying off tens of thousands of workers. In 2026 alone, layoffs.com recorded over 128,000 tech layoffs across nearly 300 companies.

So, what is driving this paradox, and what does it mean for the future of IT?

The Pandemic Hangover and the Growth Paradox

Historically, the tech industry operated on a simple formula: more expected customers equals more engineers. This model turned India into a $224 billion IT export powerhouse, heavily reliant on markets like the US, UK, and the EU.

During the pandemic, companies accelerated their digital transformation by years, over-hiring to meet extraordinary demand. But as the world normalized, growth cooled to standard rates. Suddenly, companies realized they were overstaffed.

The key realization here is that a company doesn’t need to be losing money to fire people. If a company can maintain its billions in revenue with fewer employees, executives will make the cut to optimize costs.

The Skills Mismatch

The second major factor is a shift in required skill sets. Having millions of educated tech workers doesn’t automatically mean a workforce possesses the exact skills required today. Companies are transitioning aggressively toward AI, cloud computing, cybersecurity, and advanced engineering. While the IT industry is still hiring, they are no longer just asking “do we need more employees?” They are asking, “do we need more of these specific employees?”

The “AI Layoff Trap”

This brings us to the most disruptive force in modern tech: Generative AI.

Generative AI doesn’t just make humans faster; it actually performs parts of the work itself—writing code, generating reports, analyzing data, and testing software. If a team of 100 employees equipped with AI can suddenly double their output, the company simply doesn’t need to hire 50 more people for its next project.

Economists refer to this scenario as the “AI Layoff Trap”. The logic is simple but brutal:

1. The Monopoly Example: If one giant company fires 90% of its staff to automate with AI, they instantly realize those fired workers are their customers, effectively destroying their own demand.
2. The Competitive Reality: In a competitive market, a CEO knows that firing a few workers won’t completely erode their individual customer base. However, if every CEO adopts this dominant strategy to stay competitive, it leads to a disastrous scenario where global demand is eroded, and every firm suffers.

As one expert in the video noted, CEOs see this economic cliff coming, but “if I hold back and I don’t [automate], all the other companies are going to automate and now I’m going to go bankrupt.”

A Broken Career Ladder

For young tech professionals, the implications are severe. Historically, the career ladder involved entering as a junior doing basic coding, testing, or documentation, and slowly gaining the experience needed to become a senior developer.

AI is currently excelling at these exact entry-level tasks. If tech companies no longer need juniors to do the heavy lifting of basic documentation and code generation, the first rung of the career ladder disappears. This begs the uncomfortable question: If companies stop hiring juniors, how does anyone become a senior?

Looking Forward: AGI and ASI

As we look toward the potential arrival of Artificial General Intelligence (AGI) or Artificial Superintelligence (ASI), the conversation shifts from a technological problem to an economic one. If AI keeps getting dramatically better, it could create entirely new industries. However, if the global economy simply becomes hyper-productive while requiring drastically fewer humans, we are facing a structural economic crisis.

For tech professionals navigating this turbulent landscape, the strategy is clear: continuous upskilling into advanced systems architecture, AI management, and strategic roles that machines cannot easily replicate is no longer an option—it is survival.