CMOs often err by presenting the board with operational marketing metrics. Instead, they should emulate a manufacturing leader, focusing reports on the final output: the number of profitable customers acquired. Tactical KPIs are for managing the team, not for the boardroom.
To succeed with AI, CMOs should avoid a scattered approach. Instead, they should apply AI to four fundamental marketing tasks: recognizing opportunities with precision, reaching customers on their journey, informing relevance for true personalization, and seeing the results.
When reporting on AI experiments to the board, avoid using "learning" as a primary KPI, as it can sound like an excuse for failure. Instead, translate those learnings into tangible outcomes and demonstrable progress toward goals, showing what impact the learning has and promises.
Stalled AI projects often stem from cultural issues. Leaders rush for big wins instead of adopting an experimental "build to learn" mindset. They fail to address poor data quality and the organizational fear that leads to automating old processes instead of innovating new ones.
The CMO's job isn't fundamentally changing but expanding in a "yes, and" fashion. While new responsibilities like driving enterprise-wide change are added, the core function remains creating profitable customers, shifting focus from advertising or communications back to P&L impact.