ModelOps Can Build AI and ML With Business Results

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A recent report by MIT Sloan Management Review and SAS called for a relatively new method called “ModelOps,” which is seen as critical to the successful delivery of artificial intelligence (AI) and machine language (ML) to businesses.

ModelOps, which stands for Model Operationalization, is a way to help IT executives bridge the gap between analysis and production teams, making the lifecycle of AI and ML “repeatable and sustainable.”

To get ModelOps to manage AI and ML, IT leaders and professionals must bring together four key elements of the business value equations, including ecosystems, data, platforms, and people.

For more information, read the original story in ZDNet.

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