The Doppler Quarterly Winter 2018 | Page 62

Getting the Right People This third challenge may well be the most difficult to deal with, as there are a few factors at play. First, AI involves numerous skill sets. As we looked at all the moving parts, we saw that there are many different skills needed, including cloud services, data storage, data transformation, third-party data sources, mathematics, statis- tics, programming, graphics, etc. Enterprises often seek the mythical “Data Scientist Unicorn” who has all these skills, but such folks are few and far between. It is often more productive to define the specific skills needed for your particular effort, and then seek to build a multi-disciplined team of people who individually have expertise in one or two of the skills. Second, these disciplines are relatively new, so it is difficult to find experienced personnel to work in AI. Given the speed at which we have begun to generate and accumulate data, our educational system has only just started producing formally educated data scientists that have exposure to the many skills required. Those people are inherently inexperienced in large enterprise cul- ture, so we often have to turn to people that are self taught. This group is also 60 | THE DOPPLER | WINTER 2018