At Cannes Lions last month, CMOs from major global brands shifted their AI conversations from pilot excitement to a pressing concern: a widening gap between what AI can produce and what organizations actually do with it. The technology is moving into production, but measurement, data trust, and accountability are not keeping pace.
Pilots are over, production is not progress
Sanjna Parulekar, senior vice president of product marketing at Salesforce, said during a panel, "Pilots are over, everyone is in production phase." The industry has moved past experimentation. Amazon Ads built a conversational planning interface that takes a marketer from insight to activated campaign without a single SQL query. PMG repositioned itself from a media services company into a technology and transformation company.
But production volume does not equal business progress. Most brands still have more data than they know how to use. They optimize channel by channel instead of designing for cross-business outcomes. AI speeds execution, but speed without proof of what it produced only widens the accountability gap.
The data trust deficit
Forrester data published in 2024 found that 64% of B2B marketing leaders don't trust their organization's measurement for decision-making. When the underlying data isn't trusted, intelligence built on top of it won't be either. AI doesn't create the trust problem - it makes it more visible.
"You can't blame AI for the output. It's only as good as the question you ask," the source said. Without clear ownership of data, inputs, and outcomes, AI accelerates the production of answers no one fully trusts. The risk is scaled automation built on weak inputs and measurement that still can't prove business value. For teams looking to strengthen that foundation, AI for Marketing Courses can help build skills in data-driven decision making and campaign measurement.
Causation is the new currency
CFOs are asking marketing the same question they ask every other function: What did this cause? Most CMOs at Cannes could not give a definitive answer. For years, impressions, reach, and clicks were the currency because they were easy to produce and defend. Proving causation was slow and expensive, so correlation became the default. That excuse no longer holds.
Julia Fedor, head of brand marketing operations at United Airlines, said, "The goal is to position marketing as a growth driver, not a cost center." That requires metrics built for causation, not correlation. Brands investing in causal measurement now are building a competitive moat.
What CMOs can do now
The accountability gap is an organizational problem, not just a technology one. Here are the steps to start treating it that way:
- Retire one vanity metric this quarter. Pick the KPI your team tracks but nobody acts on. Removing it signals that the accountability standard has changed.
- Audit what you act on. Review your last several quarterly business reviews and identify which metrics drove a decision that changed something or proved impact. If you can't find one, fix that before buying more tooling.
- Get your CFO in the room earlier. The CMOs building the most organizational trust don't wait for budget season to prove marketing's value. Bring the CFO into the conversation about what success looks like early on, before a campaign runs.
- Separate the AI roadmap from the decisioning roadmap. Most organizations invest heavily in AI but not in the change management that surrounds it. Technology accelerates output, but it needs to be used correctly to drive outcomes.
- Define what "growth driver" means in your business. AI can only drive growth when the definition is concrete. Pick the metric that moves the needle - incremental sales lift, revenue contribution, new customer acquisition - and use it as your proof.
For CMOs looking to close this gap systematically, an AI Learning Path for CMOs offers structured guidance on building accountability into AI strategies and aligning teams around measurable outcomes.
Why this matters for marketing professionals
The brands winning right now are those with the clearest line between what they learn and what they do. They have decided not just that AI will drive the business forward, but that they've built the structure to convert intelligence into measurable outcomes. For marketing professionals, the message from Cannes is direct: speed gets you to the table, but proof keeps you there. If you can't show causation, your AI investments will be viewed as a cost rather than a growth driver.
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