The Dual Nature of AI Technology: Potential Gains and Bubbling Expectations

The two faces of AI technology

New technologies create both positive and negative impacts on society, and AI is no different. A recent McKinsey report on generative AI suggests that the technology will add $2.6trn to $4.4trn annually, adding roughly the economy of the United Kingdom. McKinsey is predicting that 60-70% of work activities today can be automated with AI, enabling 0.1-0.6% points to labour productivity growth. Long-term predictions on technology are difficult, but the McKinsey report encapsulates the zeitgeist perfectly, as the AI technology is becoming our new hope for a better and richer future, a bit like the space age during the Cold War and the Internet two decades ago.

Our view is that AI-related stocks have entered a bubble phase marked by ‘peak of inflated expectations’, following the logic of Gardner’s hype cycle model. Soon, we will likely begin to see companies disappoint against those elevated expectations and take investors downhill to the trough of disillusionment before entering the slope of enlightenment. In order for our clients to get the best overview of the companies that have reacted the most to the AI-hyped rally, we have created a theme around AI consisting of 20 stocks. This list is already our most accessed equity research by far, underscoring the interest in AI. It is worth noting in the table of AI stocks that many of these stocks trade close to their price targets, indicating that equity analysts have difficulties justifying current equity valuations against the outlook.

 

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The pessimists would argue that while AI will create economic gains in the longer run, the world is greatly extrapolating the current trend, creating a bubble in AI-related stocks. Google search volume in the US on ‘ChatGPT’ and ‘AI’ peaked in April and is already declining, suggesting that the initial hype is beginning to fade, although the hype has not yet ended in equity markets. The pessimists will also argue that generative AI will cause a flood of fake news, images and video, essentially polluting its own training data in the future, causing a natural stagnation in future systems, but even worse, that it will potentially break down trust in our information systems. This scenario could be a big comeback for traditional media as a trusted source of information.