Bringing an AI Product to Market

Get a free trial today and find answers on the fly, or master something new and useful. Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Product managers for AI must satisfy these same responsibilities, tuned for the AI lifecycle. If you're an AI product manager (or about to become one), that's what you're signing up for. In this article, we turn our attention to the process itself: how do you bring a product to market? The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you've succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Though these concepts may be simple to understand, they aren't as easy in practice. It's often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Politics, personalities, and the tradeoff between short-term and long-term outcomes can all contribute to a lack of alignment.