Every marketing leader feels the pressure to do something with AI, especially when the board is demanding a plan. The easy response is to add one more tool to a stack that already covers a dozen small pieces of the funnel. But a bigger tech stack rarely translates to a smarter marketing organization.

In this episode of Marketing in Progress, Gayle Kalvert spoke with Ray Wizbowski, Chief Marketing Officer at ECI Software Solutions, to dig into what it actually takes to make AI pay off in B2B go-to-market (GTM) strategies without losing the human side of marketing.

AI has outgrown the content shortcut

Most teams started with AI the same way: a little ChatGPT here, a writing assistant there, and the hope of producing more content without adding headcount. That was a unit economics play, and for many marketing organizations, it's still where AI lives.

Ray's team has moved on to agentic processes that pick up market signals, guide messaging, and work around the clock. As a result, ECI adjusts its GTM motion monthly instead of yearly and refines its ICP every two weeks instead of every quarter. 

If you still plan in annual cycles, that pace should get your attention.

Start with the problem, then train the model

Most teams buy AI tools to get more insight into the funnel, but they end up with information that lacks context. Strategically, this approach is backward. You need to flip the order:

• Define the problem you're trying to solve

• Figure out what data the AI can actually use

• Layer in the technology

That data piece is really important because AI is only as good as the data you feed it. No one has pristine CRM data, so the smartest teams take the human element out of data capture wherever they can (like call recordings that write straight into Salesforce).

Expertise matters just as much. ECI's messaging engine learned the language of manufacturing floors and lumber yards from the people who know those industries, not from whatever the public internet says about them. As Ray puts it, you want to be the one training your model, not Wikipedia or Reddit.

He also has a simple test for separating real capability from a polished demo. Listen to the podcast to learn it before you sign your next AI contract.

Put people and process before technology

Ray leads through three lenses in a deliberate order: people, process, and then technology. He invests in his team first, ensures the process isn't getting in their way, and brings in AI only after that foundation holds.

This order is intentional; it has a direct impact on effectively shaping the culture of the team. In fact, his team works under a "fail fast and fail cheap" mindset, so people experiment without worrying that a failed test will count against them. 

The real power of AI is removing the administrative work teams hate. This allows marketers and sellers to focus on what only humans can do: build relationships, shake hands, and close business.

What this means for marketing leaders

So what separates the leaders getting real value from AI from the ones collecting tools? Strong leaders treat AI as a way to sharpen what already makes their business valuable. They speak the language their board speaks, tie every investment to pipeline, bookings, and growth, and build teams curious enough to keep learning as the technology leaps ahead. 

The full conversation goes further, including the Salesforce pick list fix that stopped sellers from gaming win-loss data, the 68-page book Ray recommends to his entire team, and the end-to-end agentic “go-to-market cube” his team is building right now.

Listen to the full episode on Spotify, Apple Podcasts, or YouTube, and subscribe to Marketing in Progress so you never miss a conversation with the leaders reshaping B2B marketing. Know a marketing leader under pressure to "do something with AI"? Send this their way.

At Creo Collective, we help B2B marketing leaders turn AI and go-to-market strategy into results, from messaging and content engines to AI search optimization and campaign systems tied to pipeline. Learn more.