Those responsible for the JPMorgan banking entity they have done numbers. For AI companies to achieve a 10% return on their capital expenditure In 2030, they will need to collectively earn $650 billion. That’s like saying that the 1.4 billion iPhone users will pay $400 a year to use those models. It’s not impossible, but certainly it doesn’t seem simple.
Many use it, few pay. Above all, because today the number of paying users is very small. According to the data from the consulting firm Menlo Venturestoday 1.8 billion people use AI around the world, but only 3% of them (54 million) are paying customers of some subscription.
ChatGPT as an example. OpenAI esteem that in 2030 that percentage will rise to 8.5% for its user base, which they project will be 2.6 billion a week. That is to say: 220 million people will be subscribed to one of ChatGPT’s payment plans, which will probably have different prices than the current ones in 2030. They do not seem sufficient, at least a priori, to make the firm profitable as promised.
Advertisements. It is more than likely that the advertisements they end up being the other great resource to earn revenue from AI models. Although Sam Altman indicated in the past that advertising would be “the last resort” to monetize, recent data reveal that those ads are about to be part of the user experience on ChatGPT.
A very risky bet. JPMorgan’s estimate points to a future in which billions of people will pay a lot of money a year to use the best AI. Apple account with 1 billion subscribers to its services, Netflix with 300Spotify with about 280and Google account with 150 million subscribers on Google One alone. It is evident that there are many users willing to pay for services that are useful and entertaining. The question is whether AI will be for so many people. And AI companies, of course, are confident that they do.
The non-surprise of the bubble. In The Economist indicate that a potential explosion of the AI bubble already it’s not going to surprise anyone. The curious thing is that there is no excessively notable concern for the consequences. In recent years the economy seems to have recovered surprisingly well from disasters such as the European energy crisis after the start of the Ukrainian War or the tariffs imposed by the US. Recessions, this economic newspaper points out, they are becoming rarer.
Everyone has jumped on the bandwagon. Mass vulnerability exists, however. Stocks today represent 21% of Americans’ economic wealth —more than in the dotcom bubble—, and investment in AI companies is responsible for half of the increase in that wealth over the past year. And therein lies the danger.
Recession in sight? People have earned more money and saved less: if the bubble bursts in a similar way to what it did with dotcoms, The Economist believes that net worth will fall by 8%. That in turn would cause a notable decrease in consumer spending. It is estimated that the US GDP would decline by 1.6%, enough to push the country into recession.
The difference with dotcoms. In this case that global recession It might not be so deep for a clear reason: the root would be in the investment markets, and therefore it could be overcome with a little more room for maneuver. Central banks could cut interest rates to boost consumption, a good thing on that front but dangerous for vulnerable economies.
The shock wave of the explosion. If the bubble bursts, what could also occur is a painful reconfiguration of global trade. Lower US demand would reduce its trade deficit, but would worsen the excess China production capacity. By not being able to sell (as much) to the US, it would flood other markets with its products, which would probably cause some protectionism in Europe and Asia. The world is preparing for the stock market crash, but not so much for the economic and geopolitical consequences that will follow.
In Xataka | OpenAI has no problem inflating the AI bubble – it has a problem with it bursting too soon
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