Marketing AI – plenty of use cases, but we’re just getting started
Paul Roetzer, founder and CEO of the Marketing AI Institute, said that marketing AI is the “science of making marketing smart.” Notice he didn’t say “automate things.” Marketing AI is not marketing automation, and therein lies an important point – a lot of marketers still don’t understand what AI brings to the table for marketing.
Roetzer’s Institute, in partnership with Drift, a provider of conversational AI solutions, recently published 2021 The State of Marketing AI. It’s a survey that looked at how marketing AI is in use today, the most common use cases, and where companies see themselves using AI in the next five years.
Yes, we’ve been having lots of conversations around AI (Artificial Intelligence) for years. But marketing is slow to catch up, and the report makes that clear. Fifty percent of respondents considered themselves beginners in terms of understanding AI terminology and capabilities. Another 37% said they were intermediate in their knowledge of marketing AI. It’s a similar story when evaluating AI-powered martech – 64% have medium to low confidence in their ability to assess and select AI technology.
For the study, 38% of respondents were C-suite, primarily the CEO or CMO, and most were B2B, with some doing both B2B and B2C marketing. In addition, the bulk of the respondents were involved with content marketing (69%), marketing analytics (60%), and email marketing (58%).
Most companies are just getting started with marketing AI; 65% categorize their stage of transformation as “researching.” These companies are building their awareness of the importance of AI and how it can transform their talent, tech, and strategy. However, they aren’t doing anything because they don’t yet comprehend what they really can do with it – all they know is that it exists in different forms.
The next biggest stage is “understanding.” This group of respondents is learning how AI works and exploring the various use cases and technology. There are three other stages of transformation: piloting use cases, humanizing by integrating AI and human capabilities and scaling for wider adoption.
Respondents were asked what the barriers to adoption of marketing AI were for them. Seventy percent said a lack of education and training, another 46% said awareness and resources, followed by talent, skillsets, and strategy. Technology infrastructure was number 7 on the list at 35%. These barriers make sense if most companies consider themselves in the research and understanding stages of AI transformation.
Something else that aligns here: 77% have less than one-quarter of all marketing tasks automated, yet 80% believe more than 26% of tasks will be automated within the next five years. There is an expectation that things will change – and by the looks of it, they will change fast. The technology is available today to make the shift to marketing AI, but each one supports different use cases.
