Machine learning offers huge potential across digital products but it continues to come with so much hype that it leaves us with more questions than answers. What new thing can we build we couldn't before? How do we introduce intelligence into existing products? How much data do we really need? In this talk we've given an overview of practical concerns regarding building machine learning powered products through a set of standard product management lenses including customer value, commercial viability, technical feasibility and end usability. We step back and consider the strategic implications of Machine Learning and the potential to build sustainable competitive advantage, before diving into the practicalities of establishing ML product teams.