Will An AI-Bubble Repeat The Dotcom Crash Of The Year 2000?

Posted by Peter Rudin on 26. July 2024 in Essay

The Bubble Bursts     Credit: insider.com

Introduction

Experts are growing increasingly concerned at early signs that the frenzy which surrounds AI could collapse in itself –  a bubble which, if it bursts, could end in a disaster for many investors. For some analysts AI still remains completely unproven, highlighting growing concerns that the sheer amount of capital being poured into AI could lead to a dot-com-style crash we experienced in the year 2000. Even tech leaders in the industry are warning things could end badly. Some shortcomings with the technology, including ‘hallucinations,’ a term used to denote lies dreamed up by large language models like OpenAI’s GPT-4, is a problem that has persisted to this day, with some experts arguing that it is an intrinsic quality which cannot be solved.

Factors That Cause An AI Bubble

The following lists some of the factors likely to be responsible for the development of an AI bubble:

Hype: There is over-enthusiasm, sensationalism and excessive media coverage of AI, labelling it as the most important industrial revolution to-date. However, despite the problems associated with the technology, the overvaluation of AI assets leads to mindless investments.

SpeculationNot every investor or business is capable of understanding AI technologies and their implications at a profound level. Surface-level information and trend-driven investments can lead to an inaccurate assessment of its long-term viability.

FOMO (Fear Of Missing Out): Many businesses are investing in AI and trends continue to indicate rapid adoption of AI technologies. This is causing the fear of missing out and investors are rushing into investments without careful diligence.

High valuation: Market hype and enthusiasm can lead to high hopes among investors and lead to inflated valuations of inadequate assets. Unsustainable business models come with risks that may lead to a loss of investments and resources.

Ethical concerns: Concerns about data, privacy, bias, job displacement and uncertainty about future developments are some of the issues threatening the AI industry. Other than that, over-promising and under-delivering is also a huge concern. This can lead to scrutiny and regulations, causing the bubble to burst.

In addition, global economic conditions and regional laws related to AI or technical limitations to real-world applications can lead to the burst of an AI bubble as well. These factors induce uncertainty and mistrust undermining the progress of the AI industry and its potential for solving problems.

Consequences From The Crash Of The Dotcom Bubble

The dotcom bubble, also known as the internet bubble, was the result of a rapid rise in equity valuations of U.S. technology stocks fuelled by investments in internet-based companies during the late 1990s. At the start of the dotcom bubble, the value of equity markets had grown exponentially, with the technology-dominated Nasdaq index rising from under 1’000 to more than 5’000 between the years 1995 and 2000. The crash that followed saw the Nasdaq index tumble from a peak of 5’048.62 on March 10, 2000, to 1’139.90 on Oct 4, 2002, a 76.81% fall. By the end of 2001, most dotcom stocks had gone bust. Even the share prices of blue-chip technology stocks like Cisco, Intel and Oracle lost more than 80% of their value. It would take 15 years for the Nasdaq to regain the level of its dotcom peak, which occurred on April 23, 2015. The dotcom bubble developed from a combination of the presence of speculative investing, the abundance of venture capital funding for start-ups and the failure to return a profit. Record amounts of capital had started flowing into the Nasdaq in 1997. By 1999, 39% of all venture capital investments were going to internet companies. The breaking point was the AOL Time Warner megamerger in January 2000, which would become the biggest merger failure in history.

Back In 2019 First Signs Of A New Bubble?

The ‘Silicon Valley’ formula for success stipulates that massive funding of innovation will eventually lead to ‘winner-takes-all’ markets. The cash-burn is used to build branding and create network effects where a service gains more value the more people use it.  In order to enhance their monopolistic position Amazon, Facebook and Google succeed in building highly profitable monopolistic empires, reaping huge profits from advertising income and reinvesting these profits in new technologies. As a result, many not yet profitable but massively financed start-ups are suddenly faced with a very risky situation. SoftBank, and its USD 100 billion Vision Fund, one of the most dominant players in AI related ventures, is reportedly taking a USD 5 billion write-off because of its investment in WeWork and Uber. Uber, like many, has been able to tap readily available funds and has raised more than USD 22 billion from investors. Uber is not only developing the ride hailing model but also bike sharing, takeaway food delivery and autonomous vehicles. Since going public in May 2019 with an IPO price of USD 45, the stock has tumbled to USD 31 and lists now at USD 66. Snap Inc, owner of the social media app Snapchat, is also in trouble as it is rapidly running out of funds despite its USD 24 billion evaluation reported in 2017.  The stock is now trading at USD 15. China’s AI investment deals fell 63 percent in value during the first half of 2019. The only bit of good news is that the overall rate of decline in investment may have slowed from Q1 to Q2. The ongoing trade dispute between the U.S. and China certainly is not helping and remains an unsettling factor for some time to come. However, due to the sheer volume of activity in China’s emerging technology sectors, its global expansion and the rapidly growing number of leading AI development companies, the long-range outlook for the AI-sector remains positive. Of the USD 53 billion of fundraising deals in China during the first half of 2019, the largest are by far AI-driven.

An AI-Fuelled Bubble Will Bust In 2026, Research Firm Says

According to the research firm Capital Economics an AI-fuelled stock market bubble will burst in 2026. The research firm predicts  that a stock market bubble would drive the S&P 500 to as high as 6,500 by the end of 2025, a rise primarily led by technology stocks. But starting in 2026 those stock market gains should gradually diminish as higher interest rates coupled with elevated inflation start to weigh down equity valuations. According to Capital Economics returns from equities over the next decade will be poorer than during the previous one and the long-running outperformance of the US stock market may come to an end. This bearish stock market call is somewhat counter-intuitive, as the economists expect the growing adoption of AI will spark a boost in economic growth driven by an increase in productivity and innovation. Despite this trend, the bubble could burst after the end of next year, causing a correction in stock valuations. The dynamics of this scenario is similar to  the dot-com bubble of the late 1990s and early 2000s as well as the stock market crash of 1929 when USD 14 billion of stock value was lost, wiping out thousands of investors. The panic selling reached its peak with some stocks having no buyers at any price. Hence, the burst of the AI-stock market bubble should lead to a decade of investment returns that favour bonds over stocks.  However, there is a major risk of accurately timing the peak of the stock market and to assess how long the deflation of the bubble might last. Another downside risk is that once the bubble bursts, recovery might take longer than one year as was the case following the burst of the dot-com bubble.

Conclusion

The dotcom crash was basically the result of greed and unrealistic profit expectations taking advantage of global Internet connectivity through edutainment, infotainment and e-commerce. The ongoing proliferation and diversification of AI research, expanding into Neuroscience and Behavioural Analytics, leaves ample space to reboot AI and to recover after a market correction caused by the burst of an AI bubble.  We might experience a valley of disappointment. However, research is in progress that will fundamentally change the application of AI. Coupled with the strategic importance governments assign to AI, we are likely to see a massive surge in research expenditures, followed by a renewed influx of venture capital to reap the economic benefits of AI and at the same time intensify regulations against misuse.

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