Lessons from finance’s experience with artificial intelligence

Who areaiaqraiai the earliest adopters of new technologies? Cutting-edge stuff tends to be expensive, meaning the answer is often the extremely rich. Early adopters also tend to be incentivised by cut-throat competition to look beyond the status quo. As such, there may be no group more likely to pick up new tools than the uber-rich and hyper-competitive hedge-fund industry.This rule appears to hold for artificial intelligence () and machine learning, which were first employed by hedge funds decades ago, well before the recent hype. First came the “quants”, or quantitative investors, who use data and algorithms to pick stocks and place short-term bets on which assets will rise and fall. Two Sigma, a quant fund in New York, has been experimenting with these techniques since its founding in 2001. Man Group, a British outfit with a big quant arm, launched its first machine-learning fund in 2014. Capital Management, from Greenwich, Connecticut, began using at around the same time. Then came the rest of the industry. The hedge funds’ experience demonstrates ’s ability to revolutionise business—but also shows that it takes time to do so, and that progress can be interrupted.