What to Ask When Implementing Machine Learning

Successfully operationalizing machine learning models in production environments can be incredibly difficult, as the industry has already seen. In fact, Gartner has predicted 85 percent of AI projects in the next few years will fail to produce results. So how do you set your AI projects up for success? ML implementation requires a unique approach that is a complete shift from the traditional approach to IT projects. Data and analytics are the centerpieces of ML projects.