Article on Judge of the Day: Gabie Boko o...

Gabie Boko, chief marketing officer at NetApp and a juror for The Drum B2B Awards, has a blunt diagnosis for marketing teams frustrated with their AI results: the technology isn't the problem. The data feeding it is.

"The most overlooked issue in B2B marketing right now is how much of our AI disappointment is really a data problem in disguise," Boko said. "Teams roll out a new model, get weak results, and blame the technology. Usually, the technology is fine. The data underneath it is scattered, poorly governed, or stuck in systems that were never built to talk to each other."

Boko, who has spent more than 25 years at HPE, SAP, and Sage, joined NetApp in 2022 to build what she describes as a customer-first, AI-powered marketing organization. Her warning is aimed at teams that treat AI adoption as a front-end problem when the real bottleneck sits in the infrastructure.

Spend on the foundation, not the dashboard

Boko's investment strategy runs counter to the current trend of buying visible tools. She argues that campaign platforms and content engines only work if the data underneath them is trustworthy.

"If I only had one dollar to spend, I would spend it on the foundation, not the front end," she said. "Every AI tool we want to build only works if our data is governed, easy to reach, and trustworthy in the first place. I would invest in the layer nobody sees, because that is the one that decides if everything on top of it actually works."

That foundation includes cyber resilience. A data breach doesn't just cost a company its information; it erodes the trust that an AI strategy depends on.

Speed is a gift, judgment is the edge

Boko acknowledges that AI has delivered real acceleration. Her team can now test ten ideas in the time it once took to test one. But she cautions that speed alone doesn't create competitive advantage when every rival has access to the same models.

"When everyone has access to the same tools, the difference comes down to judgment: knowing which pattern in the data means something to a customer, and which one is just noise wearing a good outfit," she said. "That is still a human call. I tell my team the goal is not to produce more content faster. It is to decide what is worth saying at all, and that takes a point of view AI does not have on its own."

That perspective aligns with broader shifts in how marketing leaders are approaching AI for Marketing, where the emphasis is moving from production volume to strategic discernment.

Brand and performance are not rivals

On the tension between brand building and commercial accountability, Boko rejects the framing that they compete for the same budget. Brand work earns the permission to be believed later; performance work proves the budget was justified.

"There is an element of what we do that doesn't have an immediate performance metric attached, because that is where trust gets built over years, not quarters," she said. "Everything else needs to answer to pipeline and revenue, and I hold my team just as accountable there."

For B2B brands trying to stand out, Boko's advice is to stop imitating competitors. She sees too many companies chasing the same ideas and hoping repetition makes them true.

"Say something only you can say, built on a real customer story or a hard lesson you learned yourself," she said. "Confidence in your own voice reads as skill. Copying someone else's words, even good words, reads as doubt, and buyers can tell the difference."

She also pushes back on the assumption that B2B buyers are purely rational. Their jobs and budgets depend on getting the decision right, which makes the psychology behind B2B purchases just as human as consumer behavior, often more so. The brands winning now, she said, are the ones speaking to the person making the decision, not just the title on their card.

For the next generation of leaders, Boko wants people who understand both technology and human need. "Technical curiosity matters more than technical skill," she said. "You do not need to build the model. You do need to understand how data moves and where it lives, so you can ask good questions of the people who do."

Why this matters for marketing professionals

If your AI initiatives are underperforming, audit the data pipeline before blaming the model. Check whether your information is governed, accessible, and connected across systems. That work isn't glamorous, but it determines whether every tool you build on top of it delivers value. For a deeper look at how these strategic decisions are reshaping leadership roles, see AI for Executives & Strategy.