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Today's AI developers struggle to predict which algorithms will work. AI lacks a basis for inference: a solid foundation on which to base predictions and decisions. This makes AI tough to explain, creates mistrust, and dooms many AI models to fail in deployment. However, help for AI teams and projects is available from an unlikely source: classical statistics. This article explains how business leaders can apply statistical methods and engage statistics experts to improve results.

At many companies, gaps in organizational structure get in the way of data science success. A new type of role, connectors, can bridge those gaps to help line-of-business and data science professionals work together better and deploy more projects. This article examines examples of organizations that created connector roles and explores the management challenges for this valuable group of professionals.