Picking up new technology in an increasingly digital world is harder than it looks.
More companies may be turning to artificial intelligence, but many have yet to master the transition of integrating A.I. into their business models. As reported by TechTalks, Stanford professor Erik Brynjolfsson recently spoke about some of the challenges that A.I. and machine learning present.
Despite the productivity promises of A.I. technologies, actual efficiency gains are unlikely to be immediate, according to Brynjolfsson. « Often, there’s a period where productivity declines, where there’s a lull, » he explains. « And the reason there’s this lull is that you need to reinvent your organizations, you need to develop new business processes. »
It triggers a kind of stasis, or what he dubs a « Productivity J-Curve. » While time will tell how long the J-curve will last, companies can take steps now to minimize their own lag time. Here are three tips to consider when bringing in new technology: