Some people are keen to label every investment trend that has seen great success as a bubble that will have to burst.
The reality is much more nuanced that that.
While comparisons between artificial intelligence (AI) and the dotcom internet stocks bubble of 1995-2000 are often made, this is misleading for a few reasons.
Here, The Independent takes a look at what makes for a concerning bubble in the stock markets, and how that translates to the AI boom we’re witnessing.
What is a stock market bubble?
A stock market bubble does not have a single, exact definition that is widely agreed on, but there is a consensus on the main factors that can create one. First and foremost, share prices will have risen very quickly over a sustained period.
Share prices are supposed to go up over time, so that in itself does not mean a bubble is in play. The people running companies are specifically tasked with getting the share price to climb as the business develops new products or services, and earns more money.
Where the question of a bubble arises is when the price rises do not appear to have an adequate link to the development of goods or services by companies, or the earnings they are generating versus their spending.
A bubble can be described as a scenario where prices are being driven largely by speculation about what the future may hold, and something called reflexivity.
This is where people buy stocks simply because they have seen them go up. The more stock prices go up, the more people want to buy them, and a feedback loop is formed. It can also be referred to as market euphoria or FOMO (fear of missing out).
The big fear around this is that eventually, investors lose confidence in the companies’ ability to live up to the hopes, and large numbers of people panic-sell at once, causing a market crash.
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Who are the top AI companies?
One helpful way to think about the AI investment landscape is to split it into the companies developing AI models or services, and those which design and manufacture the computing components needed.
In terms of the companies at the forefront of AI model development which are currently publicly listed on the stock market, we are mainly talking about Google (Alphabet), xAI (SpaceX), Microsoft and Meta Platforms.
The two firms leading AI model development alongside Google and xAI are OpenAI and Anthropic.
They are both unlisted, privately owned companies – for now. The pair are expected to float shares on the stock market through an initial public offering (IPO) in the coming months, in a similar way to SpaceX.
On the components and infrastructure side, the leading names include GPU chipmakers Nvidia and AMD. More recently, Intel has emerged as a major player due to the other main kind of chip, CPUs, becoming a bigger factor in AI.
The dotcom bubble
It is widely accepted that the early years of internet adoption, in the late 1990s, saw a stock market bubble develop.
Known as the dotcom bubble due to the website URL format used as the company name by so many businesses then, it saw prices of hundreds of newly launched internet firms with low or non-existent earnings rocket to high levels.
The rises in value were often based purely on speculation that the internet would be ‘the future,’ and these companies would make a lot of money one day.
Indeed, the internet did turn out to be the future of the global economy, but most of the companies trying to tap into it failed to do so successfully to deliver on investors’ hopes.
The Nasdaq index containing many of these internet-based companies hit a peak in March 2000. As people lost faith and realised most of them would never make money, the index fell close to 80 per cent in the ensuing panic.
Is AI in a stock market bubble too?
This is a hotly contested question. While the rise of AI industry stocks bears some similarities to the dotcom boom, there are very important differences.
There is clearly some degree of speculative, momentum-driven buying, but the share price rises are coinciding with huge revenues being raked in by the likes of Nvidia.
Other tech giants at the cutting edge such as Google, Microsoft and Meta Platforms are large, long-established companies with many different sources of revenue, and billions of dollars of cash on their balance sheets.
AI is also already being put to work to generate money. While we are still in the early days of this, there are encouraging signs, such as how good AI has become at writing computer code and in medical diagnoses.
Another important difference is that in the dotcom bubble, investing was spread thin across hundreds of new, small companies which were making no money and did not have assets on their books. In contrast, the AI boom, rather than bubble, is so far centred on a handful of already successful companies.
On the other side of the argument, undoubtably elements of hype and rose-tinted hope are involved.
There is a lot of talk about AI revolutionising industries, changing the world and making vast sums of money for the companies offering it. While it is very feasible that much of this will be delivered upon, none of it is guaranteed.
It is yet to be proven that the sums of money being spent by the likes of Google, OpenAI and Anthropic will deliver the revenues to justify it.
Another risk is a ‘winner takes all’ scenario where a single or very small number of companies dominate AI and the others end up failing. The dotcom boom certainly offers parallels here.
Cut-price competition from Chinese firms could see them become the eventual AI winners, rather than the US firms loved by investors now.
Perhaps the biggest concern is simply the reflexivity, which can work in both directions. The more AI stocks go up, the more people want to buy them. At some point this must reach a limit and a correction to prices will be triggered, at least in the short term.
We already saw something along these lines last year when the introduction of US tariffs spooked the stock market.
That said, there is a big difference between a healthy correction that the market soon recovers from and the enormous crash of 2000.
When investing, your capital is at risk and you may get back less than invested. Past performance doesn’t guarantee future results.
