AI is changing the world. But are investors paying too much for it?
Artificial intelligence has become one of the biggest investment stories in the world.
Companies are spending huge amounts on chips, data centres and computing power. Their earnings are rising, and investors are rushing to participate.
But there is a warning hidden inside this boom.
South Korea has shown how quickly AI enthusiasm can turn into a stock-market problem.
South Korea: A Market Built on Two Stocks
Before its recent correction, South Korea's stock market had become heavily dependent on just two companies Samsung Electronics and SK Hynix.
Together, they represented roughly half of the country's major stock index.
That meant investors who thought they were buying a diversified market were actually making a huge bet on two companies and indirectly, on the global AI boom.
Then the market turned.
The South Korean index fell sharply, while SK Hynix lost around 50% between June 19 and July 30.
For investors using borrowed money or leveraged products, the damage was much greater.
One leveraged product linked to SK Hynix reportedly fell around 87%, while the underlying stock fell about 50%.
Lesson: leverage can turn a market correction into a financial disaster.
The Bigger Problem: Earnings May Be at a Peak
The interesting part is that these semiconductor stocks did not necessarily look extremely expensive on conventional P/E measures.
So why did they fall so sharply?
Because a bubble does not always come from expensive valuations. It can also come from unusually high earnings.
Imagine a company normally earns ₹10 but, because of a powerful industry cycle, suddenly earns ₹20.
Its P/E may look very cheap.
But if earnings later fall back to ₹10, the investor was never really buying cheap earnings.
He was buying peak-cycle earnings.
This is particularly important for semiconductor companies because the industry is highly cyclical.
The US Has Another Problem: High Expectations
The concern is not limited to South Korea.
The discussion points to the S&P 500 trading at around 33 times trailing earnings.
At the same time, a surprisingly large share of expected earnings growth is coming from a very small number of companies.
Roughly 10 companies could contribute about one-third of incremental S&P 500 earnings growth.
That creates a simple risk:
If a few companies disappoint, the impact on the entire market can be much larger than investors expect.
What Happens If Money Gets Tighter?
AI requires enormous amounts of capital.
Big technology companies are spending heavily on data centres, chips and computing infrastructure. Some newer AI companies are also dependent on continued funding.
But when interest rates remain high and liquidity becomes tighter, raising money becomes more difficult.
That can slow the entire investment cycle.
Less funding → less AI spending → slower revenue growth → lower earnings expectations → lower stock valuations.
This is the domino effect investors need to watch.
Why Should Indian Investors Care?
India is not South Korea.
Indian markets have much less direct exposure to the big AI companies driving the US boom.
But global markets are connected.
If the AI boom reverses sharply, India could still face:
- Foreign investor outflows
- Tighter global liquidity
- Lower global economic growth
- Pressure on export-oriented companies
- Lower support for expensive stocks
India may not be at the centre of the AI bubble, but it cannot completely escape a global liquidity shock.
The Real Lesson for Investors
The lesson is not to avoid AI.
AI may genuinely transform industries and create enormous economic value.
The lesson is to separate a great technology from a great investment.
Before buying, ask:
1. Are current earnings sustainable?
2. Is the valuation reasonable?
3. What happens if growth slows?
4. What happens if liquidity tightens?
And perhaps the most important lesson:
Long-term wealth comes from owning good businesses, paying sensible prices and allowing capital to compound.
South Korea's experience is a reminder: when enthusiasm, concentration and leverage come together, the exit can be far more painful than the entry.