As data science and AI technologies become more integrated into everyday business processes, more and more companies are seeing their tremendous benefits. But there are challenges with successfully deploying AI in a manner that drives measurable business outcomes. I wanted to share with you some of the best ways to address those challenges and help your data science program succeed. For more than a decade, numerous companies have expanded their business intelligence resources, investing heavily in analysis of past customer behaviour. That investment enabled them to develop rules-based recommendation engines, create better-performing sales strategies, segment consumers for marketing and product design purposes, and so on. These types of descriptive and retrospective analysis have become table stakes for any growth-minded company – whether public or privately owned. Many even started dipping their toes into machine learning and AI with the goal of creating competitive di...