The recent surge in artificial intelligence (A.I.) stocks has drawn comparisons to past technology booms and busts, particularly the dot-com bubble of the late 1990s. However, these comparisons fail to capture the unique characteristics of the A.I. industry. While the dot-com era saw a broad-based rally in internet stocks, the current A.I. rally is more focused and specific, with the majority of companies benefiting from A.I. technologies not being pure artificial intelligence companies.
To understand the current A.I. boom and its potential implications, we should look back at the 1980s when the computer industry transitioned from mainframes to personal computers (PCs). During this time, investors recognized the transformative power of PCs, but were unsure which companies would emerge as winners in this evolving landscape. This brings us to the present situation with A.I., where we can foresee the revolution it will bring, but are uncertain about the specific companies that will succeed.
The stock market in the 1980s was characterized by a handful of home runs and numerous losers. Similarly, the current A.I. evolution is expected to follow a similar pattern. In this context, investors are advised to focus on baskets of stocks rather than individual names. By diversifying their investments, they can mitigate the risk of backing the wrong horse.
Although the technological cycles in the past took 15-20 years to play out, the speed of technological advancements today has accelerated. However, investors should still examine the historical challenges faced by early computer companies in identifying winning technologies. The swift changes in the A.I. space make it difficult to predict winners accurately.
In the 1980s, IBM and Xerox struggled to keep up with the competition and the waves of change. Similarly, despite the current dominance of tech giants like Apple, Alphabet, and Microsoft in the A.I. space, it is too early to assume that they are invincible in the face of a long evolutionary cycle. A.I. is still in its early stages, and companies need to adapt and invest continuously to stay ahead.
Investors should learn from the past and focus on technology cycles, understanding that the A.I. revolution will go through phases that may not be obvious until they pass. By diversifying their investments and staying informed about the latest developments in the field, investors can position themselves for potential success as A.I. continues to reshape industries and economies.
