Artificial intelligence—you've heard the term, you know it's a trend, you know you're "supposed" to be using it, but if you were asked to explain what it means for marketers in a few short sentences, could you do it? If not, then you've come to the right place.

A quick Google search of "marketing AI" returns 950,000,000 results. And although Google does its best to surface the most relevant content to the first page (using AI to inventory, categorize and label, and recommend content, might I add), I doubt you have time to sift through each mention until you find a piece that actually gets down to brass tacks.

As a marketer, the things you likely want to know are these:

  • What new, AI-powered marketing technology should I spend budget on?
  • What time investment are we talking about in relation to implementing AI?
  • Which marketing functions are best suited for AI? Which should I just leave alone?

AI sometimes feels like "the man behind the curtain"—elusive, complex, and a little scary. Instead of skimming by with surface-level knowledge, marketers should learn more. So here are a few questions, definitions, and tactics for evaluating marketing technology solutions that claim to be "powered by AI."

Breaking Down the Buzzwords

Artificial intelligence (AKA intelligent automation)

My all-time favorite definition of AI for marketers (and there are many definitions) comes from Paul Roetzer of the Marketing AI Institute: "AI is technology that automates a task previously done by a person." Pretty simple, right?

Every time you see AI in the context of martech, just substitute out the term "artificial intelligence" for "intelligent automation," which can mean one of two things in marketing:

  1. Recommending. Some marketing software predicts which action will have the most positive outcome in order to recommend a next step in a series of events. Think of these small recommendations as stepping stones on the way to fully automating a given task. A few examples include offering content topics for a blog post, or suggesting email subject lines.
  2. Automating. Automating builds on recommending. To qualify for being automated, a task needs to be routine and repeatable; the goal needs to be specific; and the steps to achieve that goal must follow an exact set of rules. Tasks that fall under this umbrella include running programmatic ad campaigns and triggering the next email in a journey-driven series.

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image of Bart Frischknecht

Bart Frischknecht PhD is the vice-president of product strategy at content intelligence platform Vennli. His background consists of a blend of design, marketing, and engineering.

LinkedIn: Bart Frischknecht