Much has been said about how consumer brands, from Coca-Cola to Carvana, are activating AI tools to enhance their marketing. But the business-to-business space, whose primary customers are companies, also stands to benefit from this technology—in both similar and unique ways.

Toni Clayton-Hine, chief marketing officer at consulting firm EY Americas, spoke on this topic earlier this week at BrXnd’s Marketing and AI conference in New York. BrXnd is a newly launched organization focused on the convergence of brands and artificial intelligence. As CMO, Clayton-Hine understands the specific needs of businesses across categories, and the importance of marketing for delivering measurable value. 

After the talk, Ad Age caught up with Clayton-Hine to go deeper on some of the concrete advice she had for B2B brands interested in AI. Read on to learn what Clayton-Hine sees as the primary benefits that AI—generative and otherwise—can pose for B2B companies, as well as how the stakes may be higher for B2Bs than B2Cs and the value in allocating specific roles for AI exploration.

This interview has been lightly edited and condensed for clarity. 

On a broad level, how is EY thinking about integrating AI?

What I'm not advocating for is that we just take our data and transformation practice area, where we have all these experts who have all these perspectives, and say, “We are now the AI data transformation practice.” I think we need to create the philosophy of how AI is not just going to impact the work that we do, but impact the clients and then broader societies. For example, will the digital divide widen faster? What could we do about that?

How is integration of AI for B2B companies different from that of B2C companies?

For B2B, the work that we do does not empower the individual. If you have a bad can of Coke, that’s one thing. But we empower a company. What we're doing and the decisions and discussions that we have are impacting firms, and so it comes with more responsibility.

For example, let’s say somebody is going to spin off a portion of their company, and they work with us. What is that going to do to their entire back office? What is it going to do to their employees? Where they put their headquarters and how they manage their supply chain and where they put their resources are all multi-billion-dollar decisions. So if our AI is telling them that it's great [to relocate] to Chattanooga, but the supply chain isn't there, we just made a very costly recommendation.

How should B2B brands consider using AI for marketing versus internal business processes?

It's definitely a both/and [decision], because marketing is just one of the functions. If you looked across the business and said, ‘How is finance using this’ or ‘How is the supply chain using this,’ or sales or marketing, it just becomes yet another one of the pillars that runs the company. And that's why a human-centric approach becomes really important. You can't offload all these decisions, because every situation will have a level of nuance, and in the B2B world, that nuance impacts the infrastructure of a company often before it ever touches the end consumer.

Should B2B brands allocate employees that are solely focused on exploring AI use cases?

From my perspective, I need people to use AI in everything that they're doing, but we also need somebody to go fan out and figure it out. Do you use ChatGPT or Bard—what are all the different tools out there? So there’s got to be somebody that helps cull through [the options].

It’s like with a martech stack, there’s so many things that you could spend your money and time on. But the technical leader, the evaluator, the expert has to say, ‘Here's the functionality of these different tools,” and “Here's when and where and why you should use them—now go incorporate that into your job.”

How might a B2B company consider using generative AI, as opposed to types of AI technology that have been available for a while?

The lowest hanging fruit for B2B companies is to use AI and machine learning to improve basic processes or be more efficient in that respect. So that’s really a back-office use case. I think that generative AI gives you a more front-office use case, because it helps marketing and sales and it's creative.

It’s about what's the right use case, and then how do you find a use case that's repeatable? And then what do you build on top of that, so that the value that you create today, once you add some sort of AI, whether it's generative or not, that value equation moves up.