Today, marketing AI is a know-it-all with a short resume. Just like Big Data and personalization, it is also a catch-all phrase that is becoming harder to define. As a result, it is no surprise that most marketers are rolling their eyes at the topic. Nevertheless, this is also the time to take the topic seriously, unless you plan to retire into seclusion in the next few years.
New research by marketing automation provider Resulticks shows that 73 percent of marketers are either skeptical, neutral or simply exhausted by the hype around marketing AI. In addition, large numbers of marketers think that vendors using industry buzzwords are full of it. This is not surprising, considering how most vendors are probably over-selling their AI solution. In the same Resulticks study, only 18 percent of marketers claim that AI vendors are delivering the goods as promised and 43 percent felt they were over-promised.
However, for those of us who have lived through (and even reveled in) industry catchphrases, from “marketing analytics” to Big Data to “MarTech,” these statistics indicate that “Marketing AI” is on a strong growth trajectory. This is because the combination of huge industry-level investments and a few success stories is generally a recipe for a new frontier of innovation. Some time ago, I wrote an article on the VC investments being made in data-driven marketing technology and many of the technology solutions were still evolving innovations, like marketing automation. Today, the phrase “Marketing AI“ is also heading toward becoming broad and meaningless, with heavy investments in the sector. In a few years, underneath that generic umbrella will evolve smart, pragmatic solutions which will become part of the standard tool kit. For example, under the Big Data and MarTech labels, we now have well-adopted solutions, such as CRM, programmatic buying and marketing automation. While there are still bugs and varying degrees of success, there is also a large body of fruitful use-cases which demonstrate how these tools can be very effective.
So, what is a marketer to do in this environment where marketing AI has yet to evolve to a stage where it is a stable and valued marketing tool? The most important step is to set low expectations and begin to dip your feet in the water. Experimenting now is critical, as new skills sets and operating frameworks will be required to fully take advantage of the coming AI-driven innovations, and building those individual and institutional capabilities will take time.