Listen, we need to stop pretending the IT sector layoffs happening right now are just normal market corrections. They're not.
India's IT industry—the whole $250 billion edifice that's been the country's ticket to global relevance for the last two decades—is going through something that doesn't fit neatly into any economic textbook we've relied on. And honestly, most people talking about it are missing the real catastrophe.
Sure, IT companies in India —everyone's laying people off. You've heard the numbers. But what's getting lost in the noise about "efficiency gains" and "AI optimization" is this: millions of Indian professionals who were the backbone of middle-class consumption are about to stop spending money. And that's going to ripple through the entire economy in ways that GDP growth statistics won't capture.
The Numbers Game: Why "Net Job Creation" Is a Lie We're Telling Ourselves
Okay, here's where it gets tricky. The data isn't wrong, exactly—but it's deeply misleading in the way all aggregated data can be.
Yeah, GCCs (Global Capability Centers) added 135,000 to 150,000 jobs in 2025. Startups are still hiring in AI and data science. Technically, the sector might show "job creation" when you crunch the numbers. So the cheerleaders point to this and say, "See? It's fine. The market's adjusting."
Except it's not fine. Not even close.
Here's the thing nobody wants to say out loud: a junior software engineer laid off from Infosys after 8 years of career building is not getting one of those shiny new AI positions at a GCC. Neither is the 45-year-old who spent his career maintaining legacy banking systems. Those new 150,000 jobs? They're going to fresh graduates and specialists who've already spent years in machine learning.
The job market is bifurcating. On one side, you've got the elite track—the people with AI credentials, the ones companies want to pay premium salaries to. On the other side, you've got hundreds of thousands of experienced professionals who suddenly find their 15 years of expertise is worthless because the market changed overnight.
What AI Actually Does (And Why Companies Love It)
From a pure economics standpoint, AI is a game-changer for corporations. A task that took 5 engineers 6 months? Chat GPT does it in a week. Code generation, testing, documentation, routine debugging—all of it gets compressed or eliminated.
Shareholders love this. Margins go up. Competitive advantage increases. For the people running these companies, AI is the best thing that's happened in a decade.
For the people working in these companies? It's a guillotine.
The scary part is how fast this is happening. We've seen tech disruptions before—outsourcing in the 2000s, automation in manufacturing. But those happened slowly enough that you could see them coming. You could plan. You could find another sector. This feels different because it is different. Within 6 months of a company announcing AI adoption, entire departments are being "optimized." Teams that took months to replace people, replacing them in weeks.
And here's what makes it worse: there's no cushion. In the 1980s when ATMs started replacing bank tellers, the banking sector was still growing, creating other roles. This time, the entire sector is shrinking simultaneously. Everyone's being "efficient" at the same time. You can't just go work at another IT company because they're all doing the same layoff dance.
The chain reaction is brutal—one company lays off, anxiety spreads, other companies rush to cut before "falling behind," hiring freezes everywhere, unemployment ticks up, spending drops. It's synchronized mass disruption.
The Part Everyone's Ignoring: Your Bangalore Software Engineer Was Carrying the Economy on His Back
This is the thing that keeps me up at night about this whole situation. Everyone focuses on jobs and unemployment stats. Fine. But nobody's talking about what happens when millions of high-earning professionals suddenly stop spending.
A software engineer in Bangalore making ₹20 lakhs a year (and there are millions making this or more)—that person isn't rich by global standards. But in India? That's not middle class, that's upper middle class. That's the person buying a car every 4-5 years. That's the person thinking about upgrading their apartment. That's someone taking a family vacation. Kids in private school. Frequent restaurant meals. New clothes. Home renovations.
Multiply that across 5 million IT professionals, and you're looking at an engine of consumption that's been propping up entire sectors.
Now imagine 20-30% of those people losing their income, even temporarily. What happens?
Car sales crater. Not eventually—immediately. We've already seen this in real estate markets where IT layoffs hit hard. Apartment complexes built specifically for young tech professionals suddenly have thousands of units they can't sell or rent.
Restaurants in Bangalore's tech corridors see revenue drop because people aren't casually dropping ₹1500 for lunch anymore. Malls have fewer customers. Premium education services get hit hard because parents suddenly can't afford that ₹5 lakh annual school fees. Training institutes that taught advanced courses to aspirational IT professionals see enrollment collapse.
The secondary effects are even worse. A construction worker whose job depends on building apartments for IT professionals gets laid off. A restaurant owner who employed 20 people closes down. A tuition center shuts. Each one of these represents someone else's income gone.
This isn't just individual suffering—though that's real enough. It's aggregate demand destruction happening across the entire economy. And GDP numbers measuring output won't fully capture what's happening to purchasing power and consumer confidence.
You can't fix demand destruction by saying "but look, GCCs created 150,000 new jobs!" That money isn't reaching the same people or communities, and the timing is completely misaligned with the unemployment.
The Reskilling Lie
Everyone says the answer is reskilling. Take Coursera courses. Learn AI. Upskill. Pivot to data science. It's this comfortable narrative that lets policymakers feel like they're doing something without actually having to spend real money or make hard choices.
It's also mostly nonsense. Let me explain why:
First, age discrimination is real. A 45-year-old engineer with 20 years of solid experience is technically capable of learning new things. But try getting hired at a company that's explicitly hiring "AI-native engineers" who are 26 and graduated from IIT Bombay two years ago with a focus on machine learning. Your GATE score from 2001 doesn't matter. Your experience maintaining banking systems doesn't matter. What matters is they want someone cheaper and someone they don't perceive as a "legacy" hire. This isn't explicit, it's just how recruiting works. And it's brutal.
Second, time and money. A decent AI certification program costs real money—₹50,000 to ₹2 lakhs for quality training. For someone suddenly without income, that's not happening. Even the free stuff requires 6-12 months of study while not earning. If you have a family and savings are burning through, you can't just take a year off to "reskill."
Third, it's not actually equivalent. Doing an online course on machine learning is not the same as 5 years of actual ML work experience. Companies know this. So the displaced engineer gets the certification, applies for jobs, and finds that even with the credential, they're competing against people with actual production experience. It's a credential, not a guarantee.
Fourth, the pace of change is insane. Whatever you learn now might be different in a year. The frameworks change, the approaches evolve. By the time you finish a 6-month course, what you learned might already be obsolete or superseded by something better. You're chasing a moving target.
And finally—there's the psychological hit. When you've spent 15-20 years building expertise in something, being told to just start over isn't a neutral career pivot. It's a loss of identity. For a lot of professionals, their career is their sense of self and competence. Losing that doesn't just create an employment problem—it creates a depression and mental health crisis.
So when people tell you "reskilling is the answer," understand that they're usually people who aren't going through it themselves. It's a convenient solution that shifts the burden entirely onto the workers while letting companies off the hook and letting government avoid spending money on actual support systems.
Why Singapore Can Do It and India Can't (At Least Not Without Serious Choice)
Singapore's Minister of Trade and Industry talks about how they're protecting workers from AI disruption. Good for them. They've got unemployment insurance, subsidized training programs, government partnerships with companies. It works for them because Singapore has 5.6 million people and a massive government budget relative to its population size.
India has 1.4 billion people, a government budget that's stretched thin across poverty alleviation, infrastructure, healthcare, and defense. What Singapore can do with targeted intervention, India can't do the same way unless it makes a deliberate choice to prioritize this crisis.
That's the real question. Does the Indian government want to manage this transition proactively? Because it would cost serious money. It would require unemployment insurance, welfare programs, direct government training initiatives, industry incentives to hire displaced workers. It would require admitting that the market alone won't handle this.
I'm not optimistic it will happen. Not because it's impossible, but because it's politically easier to let workers absorb the shock while celebrating the "innovation" and "efficiency" happening in the tech sector.
What Actually Needs to Happen (And Probably Won't)
If India's government wanted to handle this responsibly, here's what it would look like:
Stop pretending unemployment insurance can wait. India needs a real, functioning unemployment system. Not the half-measures that exist now. Something that actually covers people for 6-12 months with replacement income while they're out of work. This is expensive, sure. But the alternative is letting millions of people burn through savings, go into debt, and stop spending.
Actually fund reskilling instead of talking about it. If the government is serious, it needs to pay for training—not expect workers to pay out of pocket. Partner with tech companies to create apprenticeship programs where people learn on the job. Make it financially viable for someone to take a training program without starving.
Stop being dependent on IT as the only high-skill, high-wage sector. Push investment into semiconductor manufacturing, biotech, advanced manufacturing, deep tech. Create options beyond coding. This takes 5-10 years of sustained policy, but it's necessary to not have all your eggs in one basket.
Maybe, actually invest in demand maintenance. This sounds weird, but it's the most important part. If you know millions of people are about to lose income, you could do targeted cash transfers, education subsidies for their kids, healthcare support. These look expensive on a spreadsheet, but they prevent demand destruction that would hurt the entire economy.
Build better support for small and medium businesses. Smaller companies create jobs with lower salary requirements. They're less exposed to massive AI disruption. Fund them, support them, get out of their way.
The core issue is this: all these interventions cost money upfront. But not doing them costs more money in the long run as consumer demand collapses, other sectors get hit, and economic growth slows.
Who Actually Suffers? Not the People at the Top
Here's something uncomfortable: the people most hurt by this are not in a position to influence policy or shape how the crisis is discussed.
A senior engineering director making ₹1.5 crore a year? If he gets laid off, he's got savings. He can take a year off and find another cushy role. He's got a network. He'll be fine.
A mid-level engineer making ₹20 lakhs? Less fine. If he's got 6-12 months of savings, he can weather a layoff. But if it drags on, he's in trouble.
A junior engineer making ₹8-10 lakhs or a business analyst making ₹12 lakhs? They're getting crushed right now. Most don't have the savings buffer to handle 2-3 months of unemployment. If they're in a place like Bangalore or Hyderabad where cost of living is high relative to these salaries, they're under immediate financial pressure.
And then there's geographic inequality. Bangalore depends on IT. Hyderabad depends on IT. Pune has a growing IT base. When 20-30% of the IT workforce in these cities loses jobs, it's not evenly distributed—it concentrates the pain in specific regions.
Meanwhile, the corporate executives and venture capitalists making money off this "efficiency" are fine. The shareholders are happy. The pain is entirely borne by workers and communities.
The kicker is that those same hurt people don't get media platforms. They're not quoted in business news articles celebrating productivity gains. They're not in rooms where policy gets decided. So policy will probably continue to assume the market will "adjust" while the people bearing the actual adjustment cost are pushed to the margins.
The Choice
India's government and business leaders have a choice to make. And honestly, I don't think they're going to make the hard one.
The easy choice is what's happening now: celebrate the innovation, talk about how AI will create new opportunities, point to GCCs adding 150,000 jobs, and let everyone else figure out how to adapt. Companies maximize profits, shareholders are happy, GDP numbers stay strong. The displaced workers? They reskill or they find something else.
The hard choice is admitting this is a crisis that needs intervention. Spending real government money on unemployment insurance and training. Creating policies that slow down mass layoffs while facilitating transition. Investing in sectoral diversity instead of remaining dependent on IT.
I think the easy choice wins. It usually does, because the people who benefit from the easy choice have power, and the people hurt by it don't.
But here's what I think everyone should understand: a consumer economy depends on consumers having money to spend. Millions of people losing income simultaneously is not a minor adjustment. It's demand destruction. It ripples through real estate, automobiles, education, restaurants, retail. It hits service sectors that employ even more people.
The irony is that reskilling and retraining and "adapting to AI" is completely possible in theory. Indians are capable, educated, ambitious. The problem is whether the country wants to invest in making it possible or whether it wants to let the market handle it while telling people it's for their own good.
Singapore chose to invest. India probably won't. And the people who bear the cost won't be the ones deciding.
