Assembling a Top-Notch AI Team

Tom Taulli,

Even though there are many great AI software tools on the market, you still need to assemble a strong team when it comes to putting together projects. The technology is complex and evolving. There are also the challenges of change management within an organization.

In terms of recruiting the technical talent, you need to be expansive. Look to your own network, say with LinkedIn. Get to know new graduates who have advance degrees, even those that are not just for computer science. “Traditional data scientist backgrounds–statistics, math, computer science–are more commonly being augmented with engineers, physicists, economists, psychologists, and so on,” said Justin Silver, who is a data scientist manager and AI strategist at PROS. “Recruiting from a pool of candidates with varying technical backgrounds can yield an AI team comprised of a wide, rich set of perspectives for solving problems. This technical diversity also makes collaboration more interesting and fun and encourages team members to effectively communicate their ideas, even at the earliest phases of research when ideas can be very fluid. When faced with solving a problem, an economist might have a very different view than a physicist, and that collaboration can be a beautiful thing.”

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