The literal definition of future-proofing is the process of anticipating the future and developing methods of minimizing the effects of shocks and stresses of future events. Just like the underlying concept of the smart car is to free the driver from many of the mundane tasks associated with driving, machine learning in the programmatic space aims to shield advertisers and publishers against decisions made today that will no longer be relevant in the future.

This week we learn more about how we keep small optimizations continuously relevant, and the three major components that are essential to future-proofing in programmatic advertising. The ultimate goal is free up time to focus on the big ROI optimization opportunities while machine learning can focus on the never ending micro-optimizations that are never, ever done.