In June, EverString and Heinz Marketing surveyed about 300 business-to-business (B2B) marketers from North America and found that less than one-fifth of them had a strong understanding of the differences between AI, machine learning and predictive modeling. About four in 10 admitted they were not clear what the differences are.
The confusion over these terms is unlikely to go away anytime soon. Part of this confusion likely comes from how marketing tech vendors and advertisers use these terms in all sorts of ways to pitch products they’re peddling. Sometimes AI and machine learning are used interchangeably. Sometimes they’re not.
These buzzwords have become a go-to for companies seeking press. InsightSquared found that press releases from marketing automation vendors typically mention AI and machine learning, but rarely mention analytics features even though marketers prioritize analytics and reporting features when shopping for vendors. And GlobalData concluded that AI gets mentioned much more during discussions on Twitter than other emerging technologies like blockchain and augmented reality do.
The amorphous use of AI by marketers creates confusion, even among AI experts. In a Digiday Research survey of 37 marketers, about half of the respondents gave themselves a “C” rating when it comes to their understanding of AI.
Courtesy of eMarketer