While nearly every company has adopted digital transformation buzzwords in recent years, the actual implementation of these disruptive technologies remains another story. For a variety of reasons, new technologies often fail to meet expectations. One example is artificial intelligence, which is an advanced technology that companies cannot ignore in an era of increasing digitalization and remote work. Many organizations deploying AI projects through tactical initiatives that seek to deliver an immediate payback have learned that this approach rarely delivers meaningful value. AI is a powerful tool, one that has the capacity to redefine entire industries.

Owing to the data deluge and the Cambrian explosion of machine learning techniques over the past decade, one might have expected the transformation of marketing strategy into a predominantly quantitative discipline by now. The fact that it hasn't happened yet, and the observation that marketing is still influenced by a lot of qualitative inputs can be ascribed to two reasons, in my opinion. The first and principal reason continues to be institutional inertia. Second, there is a significant communication and knowledge gap between data scientists and marketers, owing to their relative lack of familiarity with the other side's perspectives and paradigms. The successful marketer of the next decade is someone who is conversant with management theories of Kotler[1] as well as machine learning advances by Hinton[2]/LeCun[3]/ Ng[4].