Sector Watch: How IT Layoffs Are Rippling Across the Economy

Sector Watch: How IT Layoffs Are Rippling Across the Economy

The email subject lines are getting shorter, but the blast radius is getting wider.

A few years ago, an IT layoff still felt like a company-specific event: a product bet went wrong, a cost-cutting cycle hit, a division got shut. In 2025, it’s increasingly showing up as something else—a system update. When India’s biggest IT services firm, Tata Consultancy Services, said it would cut about 2% of its workforce (roughly 12,000 roles), the headline number was stark. What mattered more was what it signaled: the country’s most reliable white-collar job engine is being rewired around automation, and the ripple effects don’t stay inside office parks.

Because Indian IT isn’t just another sector. It has been one of the clearest “multiplier” industries in the economy: stable salaries that turn into EMIs, rent, cars, school fees, restaurants, flights home, new appliances, and the down payment that nudges an apartment from “maybe later” to “let’s do it.” Reuters described the IT industry as a pillar that helped build India’s middle class, and noted that it employed about 5.67 million people as of March 2025 and contributed over 7% of GDP—numbers that explain why even a modest-looking reduction can feel macroeconomic.

Now layer in the “why.” TCS framed the cuts as a skills mismatch, but multiple industry watchers interviewed by Reuters tied the moment to the spread of AI across coding, testing, and support work—and warned that this could become sector-wide rather than company-specific. One estimate cited put 400,000 to 500,000 professionals at risk over the next two to three years as client demands shift and efficiency expectations rise. That’s not a forecast you can quarantine. It changes how households behave even before they lose a paycheck.

You see it first in sentiment. A family that was about to upgrade a car holds off. A couple that planned a bigger flat decides to extend their lease. A mid-career manager who would’ve booked an international holiday quietly switches to a shorter domestic trip—or none at all. Reuters quoted an industry observer warning that fear around layoffs can reduce consumer demand for tourism and luxury shopping and delay long-term commitments like real estate. The key word there is “fear.” Consumption doesn’t only fall when income falls; it also falls when confidence cracks.

And confidence is exactly what broad, persistent tech layoffs erode—especially because the current cycle isn’t just “bad quarters.” It’s also a restructuring of what roles are valuable. Reuters points to particular vulnerability for people managers with limited technical depth, testing and QA roles, and infrastructure/support work—jobs that used to be safe stepping stones into stable careers. When the stepping stones wobble, the whole pathway looks less certain.

In India, that uncertainty concentrates in specific cities, and then radiates outward. Bengaluru is the obvious nerve center, but Hyderabad, Pune, Chennai, Gurugram, and parts of Mumbai all have neighborhoods where IT salary flows are the local weather system. This is why the stock market’s reaction to layoff news can look oddly emotional: it’s not just pricing builders, it’s pricing the confidence of the buyer base. After the TCS layoff announcement, Economic Times reported a broad selloff in real estate stocks and described worries that demand from software professionals could soften, particularly in IT-driven markets like Bengaluru, with spillovers to other metros.

What does that look like on the ground? Not an instant crash, but a series of micro-adjustments that add up. Landlords get a little more flexible on rent increases. New leasing decisions take longer. Tenants negotiate harder for furnished units, maintenance, or a longer lock-in at today’s price. Developers lean into offers—stamp-duty support, payment plans, “no pre-EMI” periods—to keep bookings moving. Brokers talk about “serious buyers” replacing “aspirational buyers,” which is a polite way of saying fewer people want to stretch.

Real estate is especially sensitive because it sits at the intersection of income security, interest rates, and expectations. Economic Times noted that realty analysts were explicitly connecting potential layoffs to sales risk, particularly in IT-heavy markets, while also pointing out that some investors saw value after the sector had already corrected significantly. That tension—fundamentals versus sentiment—is exactly what a layoff wave creates: the market can be “fine,” but the marginal buyer becomes cautious, and marginal buyers drive turning points.

Then there’s the second-order consumption story: the people who don’t work in IT but sell to IT. The restaurant owner near a tech park, the daycare, the cab driver, the gym, the interior designer, the electronics retailer, the weekend travel operator. When a high-income cohort tightens spending, a long chain of smaller enterprises feels it. That’s why Economic Times framed layoffs as “bad for everyone,” arguing that India’s consumption-driven growth model is exposed when tech hiring and wage growth flatten, because IT employees are a major urban consumer base.

Even if layoffs are “silent” rather than headline-grabbing, the effect can be similar. Economic Times reported estimates that “silent layoffs” could push total affected roles to 50,000 or more in a year, alongside more visible cuts. Quiet attrition pressures households in a quieter way: performance plans, bench policy tightening, delayed onboarding, slower increments, longer gaps between switches. You still have a job, but you stop acting like you can’t lose it.

Wages are the other half of the macro story, and they matter even when employment levels hold. Economic Times cited analysis suggesting employee costs for IT companies grew only about 5% in FY25 versus a much higher average pace in FY19–FY23, tying slower hiring and subdued raises to broader consumption risk. When raises shrink, “lifestyle inflation” reverses: premium becomes standard, standard becomes value, value becomes “do we need it?”

Zoom out further and you can see why this particular wave feels different: it overlaps with AI adoption. The traditional narrative of IT services—more projects means more people—weakens when automation lets firms deliver the same output with fewer workers, or shifts work toward smaller teams with different skill mixes. Reuters captured this plainly through analysts who said clients are demanding productivity benefits and cost efficiency, a trend reinforced by AI, which pressures firms to do more with the same or fewer employees. In that world, the economy doesn’t just lose jobs; it loses the predictability of job creation.

That predictability has been one of India’s quiet economic stabilizers. Families have planned around it for decades: engineering degree, first job, steady increments, the first apartment, then the bigger one. When that conveyor belt slows, the impact isn’t just GDP arithmetic. It’s a change in the country’s urban psychology—how comfortable people feel making long-term commitments.

None of this is to say the story ends in decline. Even the sources sounding the alarm also point to transition, not extinction. The same Economic Times piece that warns about layoffs also points to the upside case: reskilling, R&D investment, and the possibility of new AI-era roles if policy and industry move fast enough. The economic question is timing: will the new roles scale quickly enough, and will they be accessible to the mid-career workforce most exposed to displacement?

In the meantime, the ripples keep moving. A layoff in an IT campus becomes a pause in a housing search. That pause becomes softer demand for new launches. Softer demand becomes more incentives and thinner margins. Thinner margins change construction timelines and hiring. That hiring shift affects thousands of informal and semi-formal jobs tied to building activity. Meanwhile, cautious households trim discretionary spending, and local services feel it. The shock doesn’t announce itself like a recession. It shows up as a thousand small “not now” decisions—and by the time it’s visible in the macro data, it’s already been living in everyday life for months.