The opportunity to double revenue would seem like a good reason to deploy technology, but despite 85 per cent of B2B marketers believe artificial intelligence could accomplish this in two years less than 20 per cent have formally started using it, according to a study from DemandBase and Salesforce Pardot.

Based on an analysis of just over 110 B2B marketers late last year, the findings released Wednesday showed 55 per cent cite cost overruns as their biggest barrier to AI adoption. This was followed closely by issues around skills, and “being unsure how to start.” Of those using or planning to use AI in marketing, 64 per cent said their top priority was identifying the right accounts of individuals to target, while 54 per cent wanted to improve the reach of their digital ad spend.

DemandBase CMO Peter Isaacson suggested these are still early days for AI in B2B marketing, and that greater adoption will be driven by the need to stay competitive.

“Business now have terabytes of data to mine. But actually synthesizing that data and gleaning insights that will impact your business requires AI, machine learning and natural language processing. It’s just too overwhelming for humans to handle it,” Isaacson told B2B News Network. “Those that can’t leverage AI to improve the speed and effectiveness of their decision-making will get left behind.”

Of course, AI doesn’t always involve spending on a point product or an entirely separate set of services. Yet 40 per cent of the survey respondents admitted they either weren’t aware of AI capabilities in their existing martech stack or weren’t currently using them. DemandBase and Salesforce Pardot, for instance, both have AI capabilities (Disclosure: I offer content marketing services to Salesforce in Canada but did not discuss this news with my client or received payment to cover the research). While 70 per cent of those surveyed employ at least one data scientist today, Isaacson wasn’t sure that would be the case for the majority as the technology matures.

“While some very large B2B companies are hiring data scientists on the marketing team, we think this will be the exception rather than the rule,” he said. “Most sophisticated AI and machine learning will simply be integrated into the solutions marketers are buying from third-party vendors and will be almost invisible to the end-user.”

Top-of-funnel applications, meanwhile, may make the most sense for B2B marketers adopting AI, given the increased interest in account-based marketing, Isaacson added. Examples include using intent data signals to build your target account list, gaining precision in targeting your accounts, website personalization to engage your audiences, giving your sales teams insights, or full-funnel measurement.

“Ultimately, it’s about reaching the right people at the right time with the right message regardless of where they are in the funnel. And AI is uniquely suited to help marketers deliver on that age-old promise,” he said. 

The early adopters of AI in B2B marketing are bullish about their return on investment (ROI). Eighty four percent, for example, said they expected to see value within a year or less of an implementation.