The hedge fund industry is at an "inflection point", according to titans in the sector, which could see the idea of "star managers" take a back seat to artificial intelligence (AI) and data-driven strategies.
Efficiency in markets and the wider availability of financial data has helped make it harder for hedge funds to produce returns beyond a benchmark, a new report from Aberdeen Standard Investments and trade body the Alternative Investment Managers Association (Aima) has found.
As hedge funds are driven towards more quantitative techniques of investing, based on the use of algorithms and computer programming to make investment decisions, the report found that key figures at some of the world's largest hedge funds will be increasingly relying on AI and data.
"Theres an arms race around how asset management firms collect data and how they slice and dice it," said Blackstone's vice chair Tom Hill.
But machines can take things only so far. You need humans to make judgements on what correlations make sense with a particular investment.
The Aima and Aberdeen Standard report found that hedge fund heads believe machine learning, which uses algorithms that automatically "learn" in order to solve a problem with little or no human intervention, will become steadily more important until it is a necessity for all firms.
But the more futuristic-sounding "deep learning", which uses "layers of artificial neurons" to solve more complicated problems, is seen to be of less use to hedge fund experts. This technique will require exponentially large amounts of data, which may not yet be available in finance and economics.
Luke Ellis, the chief executive of Man Group, explained: "When we at Man Group focus on human discretionary investment, we try to concentrate down to a small number of things where we believe we have a potential edge, which is what humans are good at.
"But if you want to build a portfolio of a thousand stocks, then we believe a computer is going to beat a human every time."
The growing necessity of technology may even have the effect of causing consolidation in the hedge fund industry, according to Duke University professor Campbell Harvey.
He believes many hedge funds will be able to outsource machine learning, but those focused on systematic trading will have to develop their own in-house capabilities.
This will be expensive – and Harvey added that only the larger firms may be able to manage it.