Venture capital managers invested more than $24.6 billion in artificial intelligence and machine learning companies last year – but less than a quarter of those managers actually used machine learning technology themselves.
That’s according to a new survey of 391 venture capital and angel investors globally by private equity data firm PitchBook. While the surveyed asset managers had some appetite for data-driven investing, they continue to rely heavily on their personal relationships to source and evaluate potential investments.
Fifty-nine percent of respondents cited their personal networks as their most valuable resource when doing deals, making it far and away the most popular answer, followed by financial databases. Close to two-thirds of angel investors and early-stage VCs reported leaning on their connections when sourcing and evaluating deals, compared to just under half of late-stage VCs and corporate venture capitalists.
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While the vast majority of venture capital investors said they used data to source at least some of their investments, only about 38 percent actually used data all the time.
About 69% of respondents considered both the use of data and their own gut feelings and personal relationships as important to evaluating deals. The data points they were asked to consider included deal history, valuations, compensation, and founder history.
Still, the survey indicated that at least some respondents planned to increase their use of data and advanced technology, with just under half planning to either ramp up or begin using machine learning technology in their investment process.
“While the majority of respondents believe VC investing will always involve the human element, there’s enthusiasm to explore how machine learning can automate traditional VC,” said Steve Bendt, PitchBook’s VP of marketing, in a statement Thursday.
