The short answer according to this study? Marketers see AI transforming marketing as we know it.
Marketing sees the need, but adoption is still in the works
Of the responses, 40% are either currently using or implementing AI, and another 44% are evaluating or planning AI. Over a third believe that AI is revolutionizing marketing and sales performance.
For the 25% currently evaluating AI for marketing and sales, I wondered what kind of capabilities they are looking for and if there is a certain tech area where they should focus initials evaluations. In an email interview, Peter Isaacson, CMO at Demandbase, provided some insights:
Generally speaking, AI is about providing a human-like type of decision-making to specific tasks. A good place to start with AI is to identify which business processes generate the most waste.
For example, your marketing and sales teams might be looking for more efficient ways to gather insights about target audiences so you can better reach them, influence the buying cycle and close a deal. Instead of conducting a time-consuming and manual process of understanding a company or target audience by researching all of their blog posts, social media posts, news stories, and contact databases, AI can automatically ingest that data and turn that information into a more complete and relevant picture of your prospects and customers - at scale.
Just because they see the potential doesn’t mean they are ready to adopt it and leverage it successfully. The typical challenges like budget and skill sets exist, as well as not being sure how to get started.
Source: The State of AI in B2B Marketing
The skills barrier is an important challenge, and I was curious to know what a marketing team needs to do to either up skill their team or what skills they need to bring into the team through a new role. Isaacson said:
What we’re seeing with AI adoption is simply the natural evolution of more data-centric marketing teams. Marketing is now more science than art, and teams are getting more and more comfortable with managing large amounts of data to drive their decision-making. The adoption challenges felt by companies are driven more by the pace of change, and less on a completely different skill set required by marketers - with the notable exception of data scientist.
Having data scientists on the marketing team is a new occurrence; typically you find them in IT groups or other parts of a company. Isaacson said that since marketing teams are dealing with increasing data sets, larger companies are hiring data scientists in the marketing team to help them make decisions - like building predictive models that will predict future behavior or indicate which marketing tactics are driving revenue:
But this is the exception rather than the rule. Most companies, most of the time, will incorporate AI through the technology they buy from third party vendors. And it will be almost invisible to the end user that AI is driving the insights and decision-making.
Where AI is best leveraged
The study also found that over 20% of marketers aren’t aware of the AI capabilities of their current tools and another 21% know they exist but aren’t leveraging them:
One out of five study participants aren’t aware of AI capabilities in the vendor technologies they use.
For those that are planning to use AI in their martech and sales tech, identifying the right accounts or individuals to target top the list of things they use AI for. The benefits match the uses closely:
- Higher lead quality (67%)
- Better engagement with customers and prospects (56%)
- Better understanding of buyer intent (52%)
Source: The State of AI in B2B Marketing
The final point in the study: martech has the highest perceived value overall by 27% of respondents, but of those that are using AI now, sales tech has the highest perceived value at 60% followed by martech at 45%. I found it interesting that adtech ranked lowest overall considering it has evolved to leveraging programmatic capabilities to improve advertising reach and conversion.
I mentioned this to Isaacson and asked what areas of martech are showing the most promise:
I think this data point reinforces the fact that AI, when operating effectively, becomes almost invisible to the end user. It’s not that ad tech isn’t a great use-case for AI, it’s just that many marketers don’t even realize that AI is in the background making programmatic advertising actually work. But the data also shows that both Martech and Sales tech hold a great deal of promise as well. One of the most promising areas of AI in Martech is in creating hyper-personalized experiences - in essence, eliminating spam. With AI, brands have the ability to understand their buyers’ interests at scale, which in turn allows marketers to scale personalized conversations to millions of buyers, whether it’s through dynamic ad copy, one-to-one emails or adaptive website content that’s tailored to your visitors.
The next phase of AI in B2B marketing is “next best action,” where AI will actually be able to tell marketers what the best channel is for the right stage of the buying cycle.”
How to get started with understanding the value of AI
For the 31% who don’t know where to get started, Isaacson offered this advice:
First, marketers should not think about “how can I get started with AI?” any more than they should say, how do I get started with Python or Java? AI is merely a means to an end. Marketers need to start by asking themselves what challenges they need to solve. Once they’ve identified those challenges, they need to evaluate the best, most effective way to solve them. For things like intent-based insights, hyper targeted programs, personalized experiences on the web, and others, AI will be the quickest path to success.
Sometimes, the whole AI conversation confuses me. But that’s because I don’t see it as a separate topic to discuss. It’s a part of technology, and every vendor is looking at how they can incorporate it to make their software work smarter. Maybe that’s what also confuses other marketers – when we talk about it like it’s a tangible thing you can see but it’s isn’t.
As Isaacson pointed out, we don’t go out and say “I need AI.” They say "I have a problem. What’s the best way to resolve it quickly, help me improve the customer experience and do better than my competitors." If AI capabilities are part of that solution, great, but I don’t think it’s the answer to every problem. Marketers just need to get smarter about where it can really help.