Knowing when not to use AI will save you from overinvestment, underachievement, and a round of embarrassment. Sometimes, a coin toss is the right tool. Sometimes, an AI point solution is just the ticket. Then there are situations that call for a full-on data science department. 

Data quality and quantity, the anticipated impact on the business, and corporate culture are just a few of the variables to evaluate before resorting to the most powerful tool in your toolbox. Considerations also include an organization’s need to move from descriptive analytics, through diagnostic and predictive to prescriptive analytics and beyond, project complexity, and a firm grasp of data bias and ethics. Sterne offers a framework for choosing the right tool for the job.