Companies are making big investments in machine intelligence, including automation and machine learning to boost efficiency.

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For example, during Tyson Foods, Inc.’s Q1 2022 earnings call last month, CEO and President Donnie King doubled down on the company’s plan to spend $1.3 billion over the next three years to increase automation in meat plants.

But implementing machine intelligence successfully can be complex, according to new research. To learn more, I had a conversation with Vijay D’Silva, a senior partner at McKinsey & Company. He is co-author of the firm’s report, in collaboration with the MIT Machine Intelligence for Manufacturing and Operations program, about what it takes to succeed. The findings are based on an in-depth survey of 100 companies in manufacturing and industrial operations.

Companies defined as “leaders” have captured the largest gains from their machine intelligence efforts. The 12 highest-performing companies in the survey achieved significantly larger improvements than the rest in 20 of the 21 KPIs evaluated, such as efficiency.

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