10 key roles for AI success

More companies in every industry are adopting artificial intelligence to transform business processes. But the success of their AI initiatives depends on more than just data and technology — it’s also about having the right people on board.

An effective enterprise AI team is a diverse group that encompasses far more than a handful of data scientists and engineers. Successful AI teams also include a range of people who understand the business and the problems it’s trying to solve, says Bradley Shimmin, chief analyst for AI platforms, analytics, and data management at consulting firm Omdia.

“The technologies and the tooling that we have available is skewing more and more toward enabling and empowering domain professionals, the business users, or the analytics professionals to take direct ownership of AI within companies,” he says.

Carlos Anchia, co-founder and CEO of AI startup Plainsight, agrees that AI success rests largely on establishing a well-rounded team with a diverse range of advanced skills, but doing so is challenging.

“Identifying what makes a highly efficient AI team may seem like an easy thing to do, but when you examine the detailed responsibilities of individuals on successful AI teams, you quickly come to the conclusion that building these groups is extremely hard,” he says.

To help you assemble your ideal AI team, here is a look at 10 key roles found in well-run enterprise AI teams today.

Read full article at CIO magazine.