Gartner predicts that by the end of 2024, 75% of enterprises will shift from piloting to operationalizing artificial intelligence (AI), and the vast majority of workloads will end up in the cloud in the long run. For some enterprises that plan to migrate to the cloud, the complexity, magnitude, and length of migrations may be daunting. The speed of different teams and their appetites for new tooling can vary dramatically. An enterprise's data science team may be hungry for adopting the latest cloud technology, while the application development team is focused on running their web applications on premises. Even with a multi-year cloud migration plan, some of the product releases must be built on the cloud in order to meet the enterprise's business outcomes.

While there are only a few companies using artificial intelligence in production, it's certainly where the future lies. In this wide-ranging episode of The New Stack Makers podcast, we talk with Ted Dunning, chief application architect at MapR and author, along with Ellen Friedman, of the new O'Reilly book "AI and Analytics in Production." We all have an image in the back of our minds of computers taking over the world, but the truth for the short-term, said Dunning, is that some of the best value for artificial intelligence (AI) is going to be some of the most boring stuff. AI, at least in the beginning, will replace boring repetitive tasks and mine massive amounts of data in ways not previously imaginable. As you accumulate data, said Dunning, it begins to have interesting synergistic effects, so that the raw value can go up in unexpected ways.