Is the AI boom a bubble waiting to burst? Our latest article dives into the key signs of a tech bubble and examines whether the current AI frenzy shares those characteristics.

 

The rapid advancement and widespread adoption of artificial intelligence (AI) have sparked excitement and investment across various sectors. From sophisticated language models to AI-powered healthcare diagnostics, the potential of AI seems limitless. However, earlier this week, two events gave the industry cause for pause.

First, OpenAI’s Chief Executive Officer, Sam Altman, warned that AI could be experiencing a bubble, as investors are “overexcited about AI” (Source:  CNBC). He also likened today’s situation to the dotcom bubble in the late 1990s and the stock market crash that ensued. However, that opinion is not new. Luminaries, such as Ray Dalio of Bridgewater Associates, Torsten Slok of Apollo Global Management, have all raised similar warnings.

Second, a report published by the Massachusetts Institute of Technology (MIT) observed that although the impact of generative AI in businesses is potentially high, most businesses have had underwhelming (and even disappointing) results. Though the study included some reasons for the findings, such as flawed integration and misaligned resource allocation, the report seemed to have triggered concerns among investors, resulting in stock prices falling for some of the largest AI firms.  

 Although this week’s hesitation may be transient and forgotten by next week, we are still left with a crucial question: Are we currently in an AI bubble?

 

Tech bubble characteristics

Historically, tech bubbles are considered these speculative frenzies, when investors become overly optimistic about the prospects of a particular asset or market, and current asset prices greatly exceed their intrinsic valuation. So how do we know when we are in a tech bubble? The following characteristics tend to be evident:

  • Rapidly inflating asset values: Companies’ stock prices, particularly those associated with the hyped technology, soar at an unsustainable rate, and often are disconnected from underlying fundamentals like revenue or profit.
  • Excessive investment and funding. A flood of capital pours into startups and established companies in the sector, driven by fear of missing out (FOMO) rather than rigorous due diligence.
  • Overly optimistic expectations. The transformative potential of the technology is often exaggerated, leading to unrealistic projections and valuations.
  • Lack of clear path to profitability: Many companies garner high valuations based on potential and future disruption, without demonstrating a viable and scalable business model or a clear pathway to generating profits.
  • Increased public participation: As the hype intensifies, individual investors, who often are less informed, enter the market, further driving up prices.
  • Market disconnect from reality. Finally, a disconnect emerges between the inflated valuations and the actual progress or adoption rate of the underlying technology. This realisation often triggers a sharp market correction.

 

So is this an AI bubble?

When the above factors are considered in the context of the current AI landscape, some parallels can be drawn. First, we have witnessed substantial investment in AI companies and a surge in valuations, particularly for those involved in generative AI. Second, the narrative around AI’s transformative power is undeniably optimistic, and third, there is a palpable sense of FOMO among investors.

However, there are also crucial differences from historical tech bubbles. Firstly, unlike some past bubbles where the underlying technology was nascent and unproven, AI has already demonstrated significant real-world applications and is generating tangible value in many areas. Secondly, although valuations are high, the investment is also driven by genuine advancements and increasing adoption across industries. Finally, the degree of scrutiny and understanding of AI, while still evolving, is arguably higher among institutional investors compared to some previous tech booms.

Ultimately, whether we are in a full-blown AI bubble remains to be seen. While there are certainly elements of hype and inflated expectations, the underlying technology is robust and its potential is increasingly being realised. A more likely scenario than a complete burst might be a period of market correction and consolidation, where valuations become more aligned with actual revenue and profitability. Hence, investors and businesses ought to exercise caution, focus on sustainable business models, and differentiate between genuine innovation and overblown hype in the rapidly evolving AI landscape.

 

 

Image credit:  Freepik