AI has been a buzzword for quite some time now and is highly ubiquitous. The AI-enabled applications have extensively increased in the market. We have also been'blessed' with powerful infrastructure and advanced algorithms. However, that does not make the journey of taking your ML project to production any easy. The issue in data quality is not new, it has gained attention since the onset of machine learning (ML) applications.

Booking.com is the world's largest online travel agent where millions of guests find their accommodation and millions of accommodation providers list their properties including hotels, apartments, bed and breakfasts, guest houses, and more. During the last years we have applied Machine Learning to improve the experience of our customers and our business. While most of the Machine Learning literature focuses on the algorithmic or mathematical aspects of the field, not much has been published about how Machine Learning can deliver meaningful impact in an industrial environment where commercial gains are paramount. We conducted an analysis on about 150 successful customer facing applications of Machine Learning, developed by dozens of teams in Booking.com, Following the phases of a Machine Learning project we describe our approach, the many challenges we found, and the lessons we learned while scaling up such a complex technology across our organization.