No one can price tech revolutions
History shows that investors find it tough, almost impossible, to differentiate between tech winners and losers. The same is true about artificial intelligence (AI). Hence, analysts are confused, indeed confounded. This is reflected in the tech stocks’ price volatility. As an article in The Economist magazine states, “For if stock markets are bad at pricing conflict, they may be worse at pricing tech revolutions.” Every blockbuster today may become tomorrow’s bust. Yesterday’s down-and-out stock may become today’s up-and-booming one. Everywhere you see, there is uncertainty, randomness, and lack of clarity.
Goldman Sachs’ share-price index of firms that are at most risk from AI is down by 20 per cent in the past 12 months. But the mirror index, which includes stocks that are likely to benefit from AI, is down, albeit by a lower five per cent. The broader stock market indices are at record highs. There is indecision among the investors. If one takes specific examples, Google was almost written off because it was possibly the last entrant in AI. Over the past 12 months, since its tech efforts took off, Alphabet, the parent firm, rose by an astounding 85 per cent.
According to The Economist magazine’s internal analysis of American and European equities over the past 25 years, there are 80 examples when industries, from luxury goods, telecom to media, turned bearish. Stock prices within them dropped “at least 20 percentage points over three months relative to the broader index.” This does not include the energy sector, which moves more energetically than the others. In such cases, since the prices stay down within an industry, the investors “correctly priced a long-term change in an industry’s circumstances.” Their bets paid off. They were on the right side of the odds.
Yet, the same analysis shows that in many industry-specific bear markets, the share prices bounce back. This proves that there are as many instances when the “early bets soured.” As the magazine explains, “Tobacco firms in America and Europe are a good example. Several times their share prices nosedived relative to the market, as investors worried about the effect of innovations in e-cigarettes and vaping. Time and again, tobacco stocks rose from the ashtray.” Clearly, the stock market and investors struggle to capture tech disruptions.
Coming back to AI, while analysts, experts, and investors overestimate threats to some firms, they invariably underestimate the dangers to the others. Some studies, like Song Ma’s of Yale University, indicate the second trend more visibly. Ma found that when firms’ tech bases become “obsolete,” or less cutting-edge compared to the others, experts remain unduly optimistic about their future growth and profitability. “This props up the shares of obsolete firms,” states the magazine. When the downfall finally arrives, the investors are left in the lurch. Although the tech changes happen over time, the share price drops suddenly.
According to the magazine, there may be two reasons for the confusion about AI-led transformations. The first relates to the tech. Although AI tools have improved in some areas and domains, like coding and legal work, the expanse is uneven. Even leaders and employees seem unsure about its effects and potential. There is a debate about the actual and possible gains. Indeed, the progress is fast, hectic, and supercharged, but it is uneven across segments, sectors, and hierarchies. Thus, good news is followed by bad, followed by another wave of good news.
“The second source of uncertainty concerns the economics of a superintelligent AI. No one knows to whom the profits of such ‘artificial general intelligence’ would accrue,” states the magazine. For instance, if AI allows more competition, existing firms’ margins will suffer. Revenue growths may not be commensurate with profits due to high computing costs. Savings in terms of the number of employees may be negated by the higher salaries paid to better-skilled workers, who are adept at multitasking, and forever seeking new opportunities. In any case, new tech, including AI, causes market bubbles that inevitably burst.
Bubbles are interesting, exciting, and painful. In the tech world, investors expect newcomers, start-ups, and unlisted firms to be the carriers of disruptions that will upset the apple cart for the incumbents. This pulls down the stock prices of the latter firms because the ones that are yet-to-be-listed may “gobble up the (future) profits.” As OpenAI (ChatGPT) and Anthropic (Claude) aim to launch IPOs (Initial Public Offerings), and get listed with valuations in hundreds of billions of dollars each, their promoters and potential investors feel the same.
If one goes back a few decades ago, investors started selling stocks of the video-rental “darlings” two years before their revenues peaked in 2004. Yet, in cases like Kodak and Blackberry, they failed to notice the signs of trouble “until the business was on its last legs.” As The Economist magazine explains, “Like economists and recessions, markets often anticipate a technological disruption that never happens,” or disregards one that does happen. In the case of Indian IT and software, both happened. Most people missed the initial train in the 1990s, and were caught up in the last millennium-end frenzy. Over the past year or so, they missed the mishaps due to AI.
However, as the markets have taught, there is no saying that some of the software stocks may bounce back, especially those that adopt, embrace, and embed AI tools, even if they are the latecomers like Google. If one goes back 150 years, Edison’s electric light was a revolution comparable to the AI one today. Big bucks and moneybags piled into the new tech, and gas use was sidelined, almost forgotten. But electric light remained more expensive than gas for years. When the former’s prices came down, gas found new and larger markets.
Of course, the gas versus light was the case of two tech that both survived in different ways and avatars. In another case that happened 150 years ago, Alexander Graham Bell offered the telephone patent to Western Union, the leading telegraph firm. The latter rejected the offer, and called the invention a “toy” with ‘no commercial potential.’ Telephones boomed but Western Union survived with a “niche in money transfers.” Some leading tech firms of today graduated from something unbelievable and unrecognisable. Korea’s Samsung earlier sold dried fish, and American Express was a freight-forwarder.
The truth is a simple and stark one: “Markets reflect only the collective wisdom of today’s investors. For as long as conversations between two Silicon Valley technologists produce three answers about AI’s impact on the world, no one will be the wiser.”
