Almost two years into the AI hype, a looming market correction may soon separate true innovators from those who are trying to capitalize on the hype. The burst of the bubble could pave the way for a more mature phase of AI development.
Amidst recent turmoil on the stock markets, during which the 7 biggest tech companies collectively lost some $650 billion, experts and media alike are warning that the next tech bubble is about to pop (e.g.: The Guardian, Cointelegraph, The Byte). The AI industry has indeed been riding a wave of unprecedented hype and investment, with inflated expectations potentially setting up investors and CEOs for a rude awakening. However, the bursting of a bubble often has a cleansing effect, separating the wheat from the chaff. This article examines the current state of the AI industry, exploring both the signs that point to an imminent burst and the factors that suggest continued growth.
Since the release of ChatGPT started a mainstream hype around AI, it looks like investors jumped at the opportunity to put their money into AI-related projects. Billions have been spent on them this year alone, and analysts expect AI to become a $1 trillion industry within the next 4-5 years. OpenAI alone is currently valued at $80 billion, which is almost twice the valuation of General Motors, or four times that of Western Digital. The list of other AI companies with high valuations has been growing quickly, as has the list of failed AI startups. At the same time, the progress visible to end-users has slowed down, and the hype around AI has been overshadowed by an endless string of PR disasters.
Here are three key reasons why the AI bubble might pop soon:
- AI doesnt sell. A study led by researchers of Washington State University revealed that using 'artificial intelligence' in product descriptions decreases purchase likelihood. This effect most likely stems from the emotional trust people typically associate with human interaction. AI distrust might have been further fueled by various PR disasters ranging from lying chatbots to discriminatory algorithms and wasteful public spending on insubstantial projects.
- AI investments aren't paying off. Most AI companies remain unprofitable and lack clear paths to profitability. For instance, OpenAI received a $13 billion investment from Microsoft for a 49% stake. Yet OpenAI's estimated annual revenue from 8.9 million subscribers is just $2.5 billion. Even with minimal operational costs (which isn't the case), Microsoft faces a long road to recouping its investment, let alone profiting.
- Regulation is hampering progress. End-users have seen little tangible improvement in AI applications over the past year. While video generation has advanced, ChatGPT and other LLMs have become less useful despite boasting higher model numbers and larger training data. A multitude of restrictions aimed, for example, at copyright protection, preventing misuse, and ensuring inoffensiveness have led to a "dumbification of LLMs." This has created a noticeable gap between hype and reality. Nevertheless, AI companies continue hyping minor updates and little new features that fail to meet expectations.
It's also crucial to remember that technology adoption takes time. Despite ChatGPT's record-breaking user growth, it still lags behind Netflix by about 100 million users, and has only about 3.5% of Netflix's paid subscribers. Consider that it took 30 years for half the world's population to get online after the World Wide Web's birth in 1989. Even today, 37% globally (and 9-12% in the US and Europe) don't use the internet. Realistically, AI's full integration into our lives will take considerable time. The burst of economic bubbles is much more likely to occur before that.
A potential counter-argument to the thesis that AI development is slowing down, lacks application value and will struggle to expand its userbase, is that some big players might be hiding groundbreaking developments, which they could pull out of their metaphorical hats any moment. Speculations about much better models or even AGI lurking on OpenAI's internal testing network are nothing new. And indeed it is a fact that tech that is being developed usually surpasses the capabilities of tech that has already been thoroughly tested and released such is the nature of development. While AI development certainly might have the one or the other surprise in stock, and new applications arise all the time, it is questionable if there's a wildcard that can counteract an overheated market and hastily made investments in the billions. So anyone who's invested into AI-related stocks might want to buckle up, as turbulent quarters are likely to be ahead.
Now forget your investment portfolio and think about progress. Here's why a bursting AI bubble might actually benefit the industry:
The thing about bubbles is, they don't say much about the real-life value of a new technology. Sure, the bursting of a bubble might show that a useless thing is useless, as was the case with NFTs, which got hyped up and then quickly lost their "value" (NFTs really were the tulip mania of the digital age). But the bursting of bubbles also does not render a useful thing useless. There are many good examples for this:
- During the .com-bubble of the late 1990s countless companies boasting little more than a registered domain name were drastically overvalued and when the bubble did burst their stock became worthless from one day to another. Yet, .com-services are not only still around, they have become the driving force behind the economy.
- The bursting of the crypto bubble in early 2018 blasted many shitcoins into oblivion, but Bitcoin is still standing and not far off its all-time high. Also, blockchain tech is already applied in many areas other than finance e.g. in supply-chain management.
- The crash of the housing market in 2007 worked a little differently, as it was not a tech-bubble. Property was hopelessly overvalued and people couldn't keep up with rising interest rates. The bursting of the bubble exposed a dire reality of financial markets where investors bet on whether you will be able to pay your mortgage or not. And today? Well, take a look at the chart on average, housing in the US costs almost twice as much now as it did at the height of the bubble of 2007. Even when adjusted for inflation, buying a house is now more expensive than ever before.
In case of the housing market, the bursting of the bubble had the effect that mortgages became more difficult to access and financial speculations became a little more regulated. In the case of the .com- and crypto-bubble, however, the burst had a cleansing effect that drove away the fakes and shillers, and left the fraction of projects alive that were actually on to something. It can be suspected that a bursting of the AI bubble would have a similar effect.
While the prospect of an AI bubble burst may cause short-term market turbulence, it could ultimately prove beneficial for the industry's long-term health and innovation. A market correction would likely weed out ventures that lack substance and redirect focus towards applications with real-world impact.
Investors, developers, and users alike should view this potential reset not as an end, but as a new beginning. The AI revolution is far from over it's entering a more mature, pragmatic phase.