Worried about an AI bubble? Explore investor-focused AI bubble prediction strategies, risk signals, and smart ways to protect your market portfolio today.
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Specialists admit that this technology will make some very rich, but many others will suffer the consequences of exorbitant expectations.
It seems like an open secret that artificial intelligence may end up becoming a bubble. Not only have many experts been warning about it for some time, but also those who were initially all enthusiastic about it, such as Bill Gates or Sam Altman, have ended up qualifying their speech. It no longer gives the feeling that everything is going to be joyful with this fashionable technology.
At least, not for everyone. Many companies are betting heavily on AI, hoping that, thanks to it, all their problems will be solved, if they have them, or that their profits will increase, if they already have them. On the other hand, if you pay attention to what a new study says, the opposite will happen: most of them will have a problem.
The AI bubble, inevitable
Months ago, some compared the situation that AI is currently experiencing with that of the dot-coms of the late 90s. The large investments that are being made in artificial intelligence are too generous, and far from all of them can be justified. In fact, there is no shortage of those who warn that big tech companies could fall, or at least suffer.
A new study by the prestigious firm JPMorgan is also aligned with these lines of thought. As various media point out, research does not start from intuitions or predictions but from something much more precise: data. Its specialists have done the math and, judging by the results, they are nowhere to be found. As far as being positive is concerned, of course.
To get an idea, JPMorgan estimates that to achieve a 10% return on investments made so far in AI alone, the industry would need to generate about $650 billion a year before 2030. In other words, an unattainable figure. By way of analogy, they have given an example. If AI were Netflix right now, each user would have to pay $180 a year to make it profitable.
The main problem, the bank says, is in AI infrastructures, which are especially expensive for developer companies. That is why they have sought an analogy: a situation similar to that of the telecommunications bubble (fibre optics) could be repeated: a lot of investment in infrastructure and capacities that may not find demand at the necessary pace.
Goodbye to data centers
What would happen then if his forecasts came true? Well, as they themselves claim, many data centers built on a large scale for AI would end up being unusable. Come on, a ruin. And if the big tech companies were to fall (or at least some of them), many others would follow, like a snowball.
Experts admit that AI will have winners; many companies will make gold thanks to it, but that will not be the norm. Many others will take tremendous hits, with all that this will entail for the global economy.
FAQ from Content
Q1. When did the AI bubble start?
A1. The AI bubble began when rapid advancements in artificial intelligence led to widespread excitement, increased investment, and rising expectations around AI technologies and companies.
Q2. What is an AI bubble prediction?
A2. AI bubble prediction refers to estimating when the current surge in AI interest, investment, and valuation may slow down, correct, or deflate due to over-hype or unmet expectations.
Q3. When is the next AI bubble expected?
A3. The next AI bubble is expected when market enthusiasm peaks again, driven by breakthroughs or investment trends, leading to inflated valuations followed by a potential correction.
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