STRATEGY - HONG KONG–BASED investment firm Deep Knowledge Ventures made headlines in 2014 by appointing a computer algorithm to its corporate board. The firm, which has about 100 million euros under management, wanted a way to enforce a data-driven approach to investing, rather than relying on human intuition and personal interactions with founders. Managing partner Dmitry Kaminskiy says the algorithm served mostly as a veto mechanism —if it spotted red flags, Deep Knowledge wouldn’t invest.
In the five years since Deep Knowledge’s A.I. got its board seat, there hasn’t exactly been a stampede of companies following suit. In fact, Deep Knowledge itself shifted focus and no longer uses the algorithm. “Today, big strategy decisions are based on intuition”—that is to say, by humans—“because we have a data shortage,” says Brian Uzzi, a professor at Northwestern University’s Kellogg School of Management. Firms simply don’t make enough of these major decisions to train an algorithm effectively.
However, as more data is gathered, or models that can account for a lack of data gain commercial traction, it is only a matter of time before A.I. takes on more strategic roles: providing insights on which M&A deals to pursue, which geographies to enter, or whether to match a competitor’s product offering.
この記事は Fortune の October 2019 版に掲載されています。
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この記事は Fortune の October 2019 版に掲載されています。
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