Where Your MarTech Peers Are Really Investing in AI

I'm happy to see the hype ebb around Artificial Intelligence and Machine Learning as good ol' practical experience continues to emerge.

Messaging about AI has been dominated by vendors and self-styled futurists. Thus far the practical results within MarTech appear to be somewhat disruptive, but not transformational. For sure marketing leaders are beginning to adopt AI to accelerate some processes, ask different questions of data, and amp up their decision layers. Yet full-scale roll-outs remain episodic.

I'm basing this conclusion in part on input from MarTech leaders representing a dozen large enterprises at Real Story Group's latest MarTech Leadership Council meeting in Amsterdam. I can't share all the juicy details since these are private collaboration sessions, but some interesting trends emerged.

What We Did

In the picture above you can see enterprise MarTech leaders from across Europe marking up charts to show what AI capabilities they are actually adopting -- either planning, piloting, or rolling out.

RSG took eighteen common MarTech use cases for AI and divided them into three categories:

• Generative AI
• Insights AI
• Decisioning AI

Then we asked participants to indicate their actual level of adoption. The conversations about specifics were fascinating! But let's look at the results

What We Found

First, we found that, despite all the energy and keystrokes around Generative AI, it did not outpace the other categories in terms of use case uptake.

I thought this was revealing and confirmed RSG's argument that as MarTech AI matures, the benefits around Insights and Decisioning AI will prove more impactful than Generative AI. (You can learn more in this recorded half-hour webinar.) Some of the details also proved illuminating, including greater AI uptake in AdTech over MarTech.

When we dug deeper, the story intensified. It turns out that Generative AI use cases tend to be less mature, with a greater proportion in planning stages relative to actually piloting or rolling out. And keep in mind, these represent larger enterprises who tend to have more resources to experiment.

When the Council reflected on these results in a subsequent roundtable discussion, it turned out that issues of cost, risk, and workflow remained significant (if surmountable) challenges for Generative AI at scale.

What to Make of All This...

AI in MarTech has outgrown its infancy, but is still navigating adolescence. While effective content remains essential to marketing, at RSG we find that enterprise leaders tend to struggle more with the other two legs of the MarTech stool: customer data management and personalization / journeys. So perhaps we should not be surprised that AI may offer more usefulness there.

If this trend toward incremental adoption continues -- and I think it will -- major AI benefits going forward are going to center less on things like smarter bots and artificially-generated faces, and more on cracking the much harder MarTech challenges around how to better meet your customers where they're at.

If you personally are curious to join RSG's exclusive club of MarTech leaders to share and learn more, check out the application process. The Council meets privately twice a year in person and several times online in-between.

PS - to see some other topics the Council discussed in Amsterdam, see this previous article.