What a successful AI team really looks like


Forget the tech giants’ rosters of data science PhDs. As AI moves into the enterprise, blended teams with business skills become more important for driving business value.


As more companies scale AI projects, turning proof-of-concepts into drivers of business transformation, a clearer picture of what it takes to succeed with real-world AI is taking shape.

When it comes to AI teams, a broader set of skills are required than previously known, with a particular need for people with experience in operations and in translating AI concepts into business terms and vice versa. In other words, AI success no longer hinges on just a group of data scientists anymore.

In fact, enterprises need blended teams to succeed with AI, says Louise Herring, partner at McKinsey & Co. “If you look at the technical side, the emphasis is increasingly on how we can make sure we have production-ready code and we have elements available for reuse throughout the organization,” she says. “But the key area of emphasis that we see first of all is about translators: people who can make the connection between the business and the technical side.”

Here is a look at how several organizations are assembling AI teams to solve business issues — and how advances in AI technology are changing the baseline skills necessary for success. 

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