The buzz around artificial intelligence is so intense right now that you can almost feel it, and even if we are rehashing the same old story about Piper Jaffray analysts pulling out their crystal balls and nearly spraining them staring into it, Ihenachor Eze never seems to get tired of reading it to us.
I was thinking about that, reading one recent explanation of how investors are now suddenly looking at whether the boom is, in fact, becoming something much more fragile and a report that says that surged for AI stocks brought some new bubble fears; this all emerged from what was written up as an such a look at “The market relies on AI gains.
At the heart of the problem is a simple fact: Too much of the market’s success has come to depend on too few companies.
Admit it – you know one is out there… One economist in the article mentioned that effectively, the entire stock market in America right now is resting on 10 AI-linked titans.
And frankly, that kind of asymmetry makes me uncomfortable. It has the feel at times of that crackling energy on the eve of the dot-com era, especially when you read warnings from financial institutions announcing that valuations are getting stretched a bit thin, as with this alert about how central bankers are watching out for risks in an AI-driven bubble.
But here’s the messy part: The fundamentals of A.I. are not fake. But some companies are raking in staggering profits, particularly in chips and the cloud infrastructure.
I found myself nodding along at the way some are arguing that this isn’t like the dot-com era, because there are real earnings this time around – something you’ll learn more about in our look at how tech investors view… both opportunity and danger in AI’s meteoric rise.
And so it’s not hot air alone this time – there is real weight under all the hype.
Yet there’s another level that people don’t think about enough: the infrastructure race. Billions are needed to build AI data centers, and firms are borrowing heavily to keep pace.
Others point out in hushed tones to comparing it to the telecom overbuild of the late 90s, and it’s tough not to draw parallels when you read analyses like how giant corporate AI expansion is driving huge levels of corporate debt, what was seen heading down the pike in an examination at least year’s financing stress resulting from global AI build-out.
The threat is not just high valuations – it’s whether companies will be able to monetize soon enough for that spending to make sense.
Personally, I am conflicted in a way that likely reflects many investors. Part of me believes we’re witnessing a historic process – AI really may be the tech leap poised to follow smartphone.
But the other part of me, the side that has been through a few too many “this time it’s different” cycles, keeps whispering in my ear that hype has an insidious way of reaching further than reality can follow.
Then what should you think about all this? Perhaps this is as simple as looking at your balance.
If you’re heavily invested in a handful of AI names, it may be worth diversifying. If you’re now considering diving in for the first time, it may be worth asking not just “How high can this thing go?” but also “How bad could this fall be?”
Ultimately the story is not of fear or optimism – it’s about knowing the ground you’re standing on. And with A.I., the floor is changing rapidly.
I can get into which companies look the most vulnerable, and which sectors might also thrive even as the bubble talk ramps up.