machine learning

machine learning

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Farhad Manjoo, technology columnist for the New York Times, went to the Google I/O conference earlier this year and joked, “I have been counting occurrences of the phrase ‘now, we use machine learning’ and I got to 70 trillion.’”

This has certainly been a watershed year for machine learning and the overall AI arms race, particularly in marketing technology.

Salesforce recently released a study that AI-powered CRM activities could increase global business revenues by $1.1 trillion and create 800,000 net-new jobs. In the next 4 years, they also predicted that the global market for AI in CRM would leap from $7.9 billion to $46.3 billion.

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And yet the level of understanding for AI among marketers is mixed. Some believe AI can solve every kind of marketing problem and others have no idea what it can do. The CMO Council recently put together research showing marketers’ impressions of AI that showed marketers widely split between “excited about the possibilities”, “feels far off”, and “not quite sure what it is.”

As we head into a new year, it will be interesting to see how organizations continue to take advantage of AI and machine learning marketing. Here’s how Adobe VP Anil Kamath put it:

“People used to be very wary of machine learning. It was a black box, and they didn’t know whether to trust it—and that’s changed now. It’s become more like table stakes. Everybody needs to have machine learning in order to compete effectively.”

Here are a few related cartoons I’ve drawn over the years:

“Big Data” January 2014

“Targeted Advertising” December 2014

“Predictive Analytics” December 2016

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