The recent discussions on the “AI Bubble” seem to be really picking up now and for good reason. We have tried to dissect this topic in a simple way for everyone to understand.

Early signs of a Bubble?

1. Big Short Warning
   
   

   • Legendary investor Michael Burry ( “the Big Short” guy) recently placed bearish bets (shorts) on major AI-related stocks like Nvidia and Palantir.

     
     

   • His message: some of the AI excitement is disconnected from real earnings or sustainability.
     
     

2. Valuation Disconnect
   
   

   • Analysts (e.g., at Kotak Institutional Equities) say valuations in many AI plays are “mind-boggling”, future revenue expectations are very high, and current fundamentals may not support them.

     
     

   • According to some, AI companies might be priced for perfection (“all upside”), leaving little room for error.
     
     

3. Warnings from Big Names
   
   

   • Sridhar Vembu, founder of Zoho: he’s calling the AI boom a financial bubble, warning that speculative funding is distorting the real value of innovation.

      

   • Sundar Pichai (Google CEO) admitted there’s “irrationality” in AI spending and likened it to a dot-com style bubble.

     
     

   • Mark Mobius, veteran investor, said a correction of up to 40% could hit top AI names because of overly aggressive AI capex and valuation froth.

     
     

   • The Bank of England has also warned that if AI valuations collapse, the shock could spread globally. 

4. Structural Risk
   
   

   • There's concern over AI washing, companies branding any product “AI-powered,” even when it's superficial.
     
     

   • High spending on data centers, cloud infrastructure, and AI compute: if demand slows or overcapacity builds, companies could be left with expensive overhead.
     
     

   • An academic model (Capability Realization Rate) suggests that market valuations may be anchored to potential future capabilities rather than realised performance, which risks a misalignment.

Why Is It Considered a Bubble?

Putting together the above points, here’s why many feel this isn’t just hype:

1. Speculative Money: A lot of investment seems to be driven by expectations of future AI adoption, not current cash flows or profits.
   
   

2. Over-Extrapolation: Investors are projecting today’s AI excitement far into the future, assuming massive revenue growth that may not pan out as cleanly.
   
   

3. Capex Intensity: Building AI infrastructure (servers, data centers, chips) is very capital-­intensive. If demand slows or growth is overestimated, these investments can underperform.
   
   

4. Market Concentration Risk: A few AI-related companies (especially in the U.S.) dominate. If they falter, broader market impacts could follow.
   
   

5. Leverage / Debt Risk: As noted by the Bank of England, there could be rising reliance on debt to fund expansion. If returns don’t justify that debt, risk multiplies.

There’s a gap between the promise of AI (huge) and what is actually being monetized today (still limited for many firms). That mismatch is the core of the bubble argument.

What Does This Mean for India?

This is where things get really interesting for Indian markets and the Indian tech sector:

1. India as a Relative Safe Haven
   
   

   • According to Kotak, because India has relatively fewer pure-play AI companies (especially compared to U.S.), it might be less exposed to a global AI stock correction.
     
     

   • Some analysts suggest that if money rotates out of overheated AI plays, capital could flow into Indian equities, especially non-AI sectors.
     
     

   • Indeed, there’s talk that a bursting AI bubble could attract investments to Indian stocks, as global investors look for value in less-hyped markets.
     
     

2. Impact on AI Proxy Stocks
   
   

   • But it’s not all rosy: Indian “AI-proxy” companies (those indirectly linked to AI) are already feeling the heat. Netweb Technologies (high-performance computing systems) has seen a sharp drop.
     
     

   • Some of these companies trade at very high P/E ratios (e.g., Netweb at ~138× earnings, per analysts).
     
     

   • If global AI risk-off continues, smaller Indian firms that rallied purely on AI story (without strong profitability) could be vulnerable.
     
     

3. Sector Rotation
   
   

   • Analysts expect possible “sector rotation”: investors may move money out of high-flying AI / digital names and into more traditional sectors in India such as financials, consumer goods, capital goods, industrials.
     
     

   • For Indian tech, the risk is mixed: firms focused on services, automation, analytics may be more insulated compared to those chasing pure-play AI product development.
     
     

4. Long-Term Opportunity
   
   

   • Even if there is a correction, some see it as a buying opportunity for India. The idea: once irrational exuberance cools, real AI technologies that add value (e.g., in healthcare, agriculture, logistics) could be adopted more gradually in India.
     
     

   • Moreover, if infrastructure (like data centers) becomes cheaper post-bubble, Indian companies could adopt proven AI solutions at lower costs. Some commentators draw parallels with how India benefited after the dot-com crash.

Potential Scenarios -  What Could Happen Next

Here are a few possible futures, depending on how things play out:

1. Soft Landing / Controlled Correction
   
   

   • AI valuations correct moderately (“sentiment reset”) rather than collapse.
     
     

   • Investors who get shaken out are those with aggressive bets or weak business models.
     
     

   • Indian markets benefit as global money rotates in, especially to non-AI or semi-AI plays.
     
     

   • Long-term AI adoption continues, but more sustainably, with real use-cases winning out.
     
     

2. Sharp Bubble Burst
   
   

   • If confidence collapses (e.g., disappointing earnings, slowing AI capex), a big sell-off could happen.
     
     

   • Highly speculative AI companies (especially cash-burning ones) could face liquidity trouble.
     
     

   • Indian AI-proxy companies could suffer if they are too exposed; broader tech index could drop.
     
     

   • But once the dust settles, real winners (with solid product-market fit) might rebound or be acquired.
     
     

3. Regulatory / Macro Shock
   
   

   • Increased regulation (on data, AI ethics, compute) or macro pullback (rising interest rates, credit stress) could exacerbate a downturn.
     
     

   • AI investments could dry up, affecting infrastructure companies.
     
     

   • In India, this could slow down AI-driven transformation in services or digital adoption.
     
     

4. AI Supercycle (Long-Term Boom)
   
   

   • What if this is not a “bubble” but the early stage of a transformative cycle?
     
     

   • Some firms may be overvalued now, but AI adoption may quickly scale up making them good value in the near term.
     
     

   • Indian companies that build real capabilities (AI consulting, generative AI for enterprise, automation) could benefit strongly in the mid-to-long term.
     
     

   • As AI matures, valuations might stabilize around more sustainable growth metrics.

At ARKa, We Believe

• Jobs & Economy: A correction might slow down AI spending, which could impact job growth in AI-services, but also moderate disruption (automation risk) in the short term.
  
  

• Innovation: If speculative money exists, the focus might shift to real innovation and monetization, rather than hype.
  
  

• Capital Flows: For India, a rotation of global capital away from overvalued AI plays could be a big opportunity, especially for sectors that are cheaper or undervalued.
  
  

• Policy & Infrastructure: This moment could influence how India plans investments in data infrastructure, AI regulation, and its broader digital policy.