Make Machine Learning Work for You

IBM reveals that nearly half of the challenges related to AI adoption focus on data complexity (24%) and difficulty integrating and scaling projects (24%). While it may be expedient for marketers to "slap a GPT suffix on it and call it AI," businesses striving to truly implement and incorporate AI and ML face a two-headed challenge: first, it's difficult and expensive, and second, because it's difficult and expensive, it's hard to come by the "sandboxes" that are necessary to enable experimentation and prove "green shoots" of value that would warrant further investment. In short, AI and ML are inaccessible. History shows that most business shifts at first seem difficult and expensive. However, spending time and resources on these efforts has paid off for the innovators.