AI and disruption: history’s lessons for investors

This article was originally published in The Telegraph.

AS investors, we know we should focus on the long term, but we spend much of our time fixating on the here and now. Next quarter’s earnings, or whether the Fed will raise rates next week, take on a greater significance than they deserve. In part that’s because it’s easier than thinking about the real future - years not weeks ahead.

It is this short-termism that leads to the market’s volatility. Every minor change in, say, inflation expectations is extrapolated way beyond what we can actually see. For a perpetual asset like a share, with no fixed redemption date, or a long-dated bond, maturing years or decades hence, short term changes in the outlook can take on an outsized importance.

More rarely, however, something comes along that really will affect the long-term outlook. Everyone agrees that this new something is going to change the world out of all recognition. Canals, railways, radio, space travel, the internet - all looked, and turned out to be, transformative. The latest in this line of revolutionary technologies is AI.

Generative artificial intelligence is both thrilling and terrifying. As the International Monetary Fund’s number two, Gita Gopinath, said this week, breakthroughs in AI, especially large-language models like ChatGPT, have the potential to boost productivity and economic growth but also to cause massive disruption to labour markets and perhaps to fuel mass unemployment and social upheaval.

It was interesting that the example she used to illustrate the dangers ahead should have been the automation of car production lines and the false assumption that workers laid off by that technological shift would quickly find better opportunities in other sectors. The more interesting case study, I think, is what happened decades earlier when those same factories full of people were themselves the bright and shiny future, replacing in just a handful of years a whole horse-based economy.

As late as 1908 there were 120,000 horses in New York, 8.6 million in the US as a whole. It is hard to overestimate the degree to which economies such as America’s were dependent on them. The nation’s farmers prospered by growing the hay to feed those millions of animals, one horse for every five people in the country. When a strain of equine flu spread through the north-east US, city life came to a juddering halt as streetcars stopped, shops ran out of supplies and construction workers were forced to down tools.

Within a generation, all that had changed. In 1890 there were nearly 14,000 companies in the United States making carriages to be pulled by horses. By 1920 there were only 90. When Henry Ford built his first car in 1903 just 11,000 were sold in America. Ten years later when his first assembly line cut the time required to make a car from 12 hours to under three, sales had reached 3.6 million. A decade after that, production had hit 20 million a year.

The transition from horse to car was transformational. It’s estimated that nearly 7 million new jobs were created by the auto industry in the 40 years from 1910, 11% of the country’s workforce in 1950. But the real economic impact was felt downstream and would have been hard to predict.

Take all that hay, for example. The rapid decline in demand for animal feed led to an agricultural depression in the 1920s which created a massive drag on the entire US economy during the Great Depression of the 1930s. Elsewhere, cars played a part in creating whole new industries. In the mid-1920s three quarters of all cars were bought on instalment credit. The consumer finance industry fed off cars and vice versa.

With Goldman Sachs predicting that AI could lead to the automation of 300 million jobs and a 7% increase in global economic output over a decade, it is not hard to see why investors should be simultaneously excited and fearful about the potential for AI to reshape the global economy. And why they should be busy looking for the winners and losers. The 27% bounce for the tech-heavy Nasdaq index year-to-date has been fuelled by the search for AI beneficiaries and, just as happened 25 years ago in the early days of the dot.com bubble, individual investors are chasing the market higher. FOMO is back.

AI chip maker Nvidia’s shares have risen 164% so far in the first half of 2023 and the company is now priced at 200 times expected earnings. That’s four times its already punchy valuation multiple of under 50 just six months ago.

Three months ago, investors were pulling money out of equities as what looked like a nascent banking crisis and rising interest rates boosted the appeal of money market funds. Today, those risk-free but pedestrian returns look dull. If you think we have been here before, you are right.

If we are in the early stages of a re-run of the TMT bubble, then it will be worth reminding ourselves of what happened a generation ago. The mania was indiscriminate. An unexciting business could engineer a re-rating by adding .com to its name and many did just that. Fundamentals were forgotten, as investors found ever more inventive ways to persuade themselves that profits didn’t really matter. Newbie investors were sucked in too late when they could no longer bear the sight of friends and family making life-changing amounts of money while they sat on the side lines.

But there is a difference between an industry changing the world and it changing the fortunes of investors. The really salient comparison from the 20th century may not be the arrival of the motor car and the end of the horse-drawn economy that preceded it. Rather it may be the growth of the air travel industry. That really did transform our lives but, as Warren Buffett is fond of pointing out, it has probably lost money in aggregate for investors since the Wright Brothers first took to the air at Kitty Hawk. AI is likely to change the world. The jury is out on whether investors will benefit.

For more on AI, Nafeesa Zaman's latest article explores 3 smart ways to invest in the AI revolution.

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