AI Bubble About Burst
- Kanopy Content Team
- Aug 22
- 3 min read
Updated: Aug 25
AI Bubble Jitters, Market Overreactions, and What It Means for India’s Tech Capital
Wall Street is rattled. The very backbone of the last 18 months’ market rally—the so-called Magnificent Seven—is now under scrutiny.
Who are they?
Meta, Microsoft, Amazon, Alphabet, Apple, Nvidia, and Tesla.
These seven tech titans make up nearly 40% of the S&P 500, the main scoreboard for the U.S. economy. But more critically, they’re each other’s biggest customers in a closed loop of AI infrastructure spending.
Microsoft uses Nvidia chips.
Nvidia’s compute runs on Azure.
Meta spends billions on AI tools powered by Nvidia.
It’s not an ecosystem—it’s a high-stakes feedback loop. And now, Wall Street is asking hard questions.
The Slide Begins: A Perfect Storm of Panic
Two days ago, the NASDAQ fell 1.5%. The S&P 500 dipped 0.6%, despite the fact that 70% of its stocks were in the green. The reason? The big seven were bleeding. That’s how top-heavy the market has become.
Today, the tremors continue:
NVIDIA shed 3.5% in a single day—this is a $4 trillion company.
Palantir collapsed by 10%.
ARM, Oracle, and AMD lost between 5%–6%.
And the trigger?
A blunt MIT study stating:
“95% of AI pilot projects fail.”
The message hit the market like a punch. Then came a second blow—reports that Meta is downsizing its AI team after aggressively hiring at premium salaries. The result? Meta stock suffered its worst two-day fall since April.
The Harsh Economics of AI
AI is not free. In fact, it’s obscenely expensive.
Training next-gen models costs billions.
Scaling them requires power-hungry data centers, vast cloud infrastructure, and elite engineering talent.
AI Bubble, Big Tech is projected to spend $400 billion on AI infrastructure in 2025—that’s as large as the entire GDP of South Africa.
And yet, the key question remains unanswered:
Is this AI spend translating to revenue?
If not, then this is a bubble. Even OpenAI CEO Sam Altman has publicly admitted we may be in one.
Impact on Indian IT – Especially Bangalore
1. Short-Term Caution from Global Clients
Many Indian IT firms—from TCS and Infosys to mid-tier companies like Mindtree or L&T Infotech—are heavily reliant on North American tech clients. The slump in AI enthusiasm could result in:
Delayed contracts for AI-related services
Freezing of experimental projects
Tighter tech procurement budgets across Fortune 500 companies
This especially affects AI and cloud service verticals, where Bangalore-based firms had started building dedicated delivery pipelines.
2. Impact on Hiring and Talent Demand
Bangalore’s talent pool, especially in AI/ML, had been witnessing an artificial boom:
Engineers were being offered crore-level packages by Meta, Amazon, and Google.
Startups raised large rounds only on the promise of “AI transformation.”
That wave will now slow down. Expect to see:
Hiring freezes or comp package corrections
A shift in focus from “moonshot” hiring to cost-efficient delivery teams
Layoffs or reallocation in experimental AI units
3. Pressure on Indian Tech Startups
India’s AI startups—many of them funded by Silicon Valley or U.S.-based VCs—will feel the pinch.
Follow-on funding may slow down
VCs will demand clearer monetization
The “hype narrative” around AI startups will be replaced with proof-of-revenue
Bangalore’s startup scene will need to realign its pitches—investors are now looking beyond just “AI-powered” as a selling point.
4. The Silver Lining: Cost Arbitrage & Offshoring
Ironically, this correction may benefit Indian IT in the mid-term. As global firms look to reduce AI infrastructure costs, they will seek cost-efficient delivery centers.
More offshoring of AI maintenance and ops work
Reprioritization of Indian teams to optimize existing AI stacks
Bangalore may become the backend hub for AI, rather than its innovation lab
Final Word: Revolution vs Reality
This isn’t the death of AI. Far from it.
But it is a sobering reminder that:
Technological revolutions do not run on quarterly schedules.
Markets overreact, then stabilize.
Budgets inflate, then shrink.
And through all of it, real innovation survives—but only if it proves its value.
For Bangalore and India’s IT ecosystem, the lesson is simple:
Adapt quickly. Focus on real outcomes. Don’t sell dreams—deliver results.
