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The author is a financial journalist and author of ‘The Economic Consequences of Mr. Trump’.
It is a mug’s game to try to predict the end of the boom with any accuracy. They last much longer than anyone expected. This is true in bull markets as well as economic growth. This is because markets and economies find ways to support themselves. Renowned investor and philanthropist George Soros has a word for it: reflexivity.
In an October 2009 article in the Financial Times, Soros defined the concept quite briefly in terms of its impact on the market. He wrote, “The thoughts of the participants affect the course of events, and the course of events affects the thoughts of the participants.”
It is a positive feedback loop. The same idea was at the root of what the great economist John Maynard Keynes described as “animal spirits”; If businesses are confident, they will invest money and hire more workers, and this investment will spur economic growth.
In the context of asset markets, the most obvious example of sensitivity comes from the relationship between banking and asset prices. In the beginning, for whatever reason, banks start lending more money to people buying property. The availability of additional finance increases demand for property – be it office blocks or houses – and increases property prices. This makes bankers more confident about lending money to the property sector, as the value of their collateral is increasing. And this makes investors and speculators more willing to borrow money to buy the property, because it seems like a very good bet.
Doesn’t have to involve debt. For most of the life of cryptocurrencies, the price of digital assets like Bitcoin and Ethereum have remained high due to the belief among some investors that they represent the wave of the future. Thus any weakness is a buying opportunity. And rising prices are a great way to proselytize crypto; More people are tempted to adopt this belief.
Another way that a boom can maintain itself in both economic and asset-market terms is through spending on goods and services. This is clearly the case at the moment with the investment rush in artificial intelligence.
This spending has done little to boost US economic growth, at a time when job creation has stalled and consumer confidence has declined. In the first half of the year, JPMorgan estimated that AI spending contributed 1.1 percentage points to US GDP growth. In market terms, this plays a key role in reassuring investors about the persistence of the AI boom, not least in demand for chips made by Nvidia, the world’s most valuable company.
The discussion around this expenditure also creates a kind of FOMO (fear of missing out) among other officers. If AI is the wave of the future, any company that doesn’t adopt it risks being left behind. And, in line with the principle of reflexivity, the race to invest makes the AI boom more important to investors. The obvious parallel is to the late 1990s when spending on fiberoptic cables, routers, and telecom equipment soared, inflating the dotcom bubble.
The intoxicating nature of bullish sentiment indicates how this bullishness can ultimately sow the seeds of its own destruction. In the late 1990s, it seemed like every twenty-year-old was either launching their own website or joining a start-up Internet company with the hopes of cashing in on their stock options. The attractiveness of the technology was so obvious that many businesses were set up; Only a fraction of them will ever be profitable. When it became clear in the spring of 2000 that some businesses were running out of cash, sentiment changed.
The AI boom is different because it is focused on a few large players with strong existing business models, rather than many start-ups. This means that financial pressures are unlikely to increase so quickly.
On the other hand, AI may not be as immediately useful as many executives hope; a mckinsey Study found that 80 percent of companies that have started using AI have not yet experienced any increase in their profits. Many consumers – especially students – are enthusiastic users of AI for summarizing reports and preparing business proposals or essay plans. Useful stuff, but hardly the basis for a productivity miracle.
Of course, in the past, the effects of innovations like electrification have taken decades to show up in productivity numbers. However, until that stage, history suggests that the market boom, even if driven by reflexivity, will be long-lasting. At some point, the growth rate of AI spending and Nvidia’s revenue will slow down; And then the ratings that investors want to apply to corporate earnings will decline along with stock prices. The bandwagon will develop a strange wheel.
Arguing that the boom must end is not the same as saying that the underlying technology is crap. AI will be useful, like internet is useful and railways was very useful. This did not prevent the other two booms from crashing. A reflex action can prolong the blow but it can also deliver a painful kick.
This article has been amended to correct statements on JPMorgan’s forecast of the contribution of AI investments to US GDP growth
