At the Cannes Lions International Festival of Creativity last month, InMarket CMO Natalie Bastian engaged in conversations with CMOs from global brands about how AI is reshaping the advertising industry. She expected to hear excitement about AI-driven wins, but in actual conversations, much of the discussion turned to accountability and how far the industry lags in this area.

AI is maturing rapidly, and strategies are already in place. But most organizations still lack the ability to act on the information AI provides, and without the right inputs, that capability cannot be built. Quality data is the protein for building capability; without it, everything is just going through the motions. The gap between what AI can make possible and what businesses can actually apply it to is the most important takeaway Bastian brought back from Cannes this year.

The New AI Reckoning

Last year in Cannes, people were still asking how to use AI: running pilots, exploring internal use cases, and figuring out how to pitch it to clients. This year, the questions have changed.

"The pilots are over, and everyone has moved into production," said Sanjna Parulekar, Senior Vice President of Product Marketing at Salesforce, during a panel discussion in Cannes.

From Bastian's perspective, this is exactly the shift taking place. AI is no longer about experimenting for its own sake, but about building accountability mechanisms, coordination capabilities, and measurable outcomes to turn intelligence into business impact. Amazon Ads has built a conversational planning interface that allows marketers to go from insights to activated campaigns without writing a single SQL query. PMG, meanwhile, has repositioned itself from a media services company to a technology and transformation company.

But moving into production does not mean progress. Most brands have far more data than they can handle, and they are still optimizing by channel rather than designing outcome-driven strategies across the business.

Naming the Accountability Gap

According to data released by Forrester in 2024, 64% of B2B marketing leadersdo not trust their organization's measurement systemsfor decision-making. When the data itself is not trusted, the intelligence built on that data will not be trusted either. This is a simple fact Bastian repeatedly emphasized: you cannot blame AI for the output; it is only as good as the questions you ask. AI does not eliminate the accountability gap; it makes it more visible. If we do not have clear ownership of data, inputs, and outcomes, AI will only accelerate the production of answers that no one fully trusts.

AI can improve efficiency, whether in media buying or audience targeting, but it also raises the stakes. The real risk is not just poor automation, but scaled automation built on weak inputs, vague accountability, and measurement systems that still cannot prove business value.

Causality Becomes the New Currency

AI-driven speed only becomes an advantage when you can prove its output. CFOs are asking marketing the same questions they ask other functions: What causal impact did this drive? Most of the CMOs Bastian spoke with in Cannes could not give a definitive answer.

For years, impressions, reach, and clicks have been the currency because they are easy to produce and easy to defend. Proving causality is slow and expensive, so correlation became the default. But that excuse no longer holds. Brands investing in causal measurement now are building their own competitive moat.

"The goal is to position marketing as a growth engine, not a cost center," Julia Fedor, Head of Brand Marketing Operations at United Airlines, told Bastian.

That is the standard marketing now needs to meet, and it requires building metrics that measure causality rather than correlation.

Actions CMOs Can Take

This gap is not just a technical issue. Here is a starting point for addressing it as an organizational problem to maximize AI return on investment:

  • Eliminate one vanity metric this quarter.Choose a KPI that a team tracks but no one acts on. Remove it to signal that the standard of accountability has changed.
  • Audit what you actually act on.Review business reviews from the past few quarters and identify which metrics truly drove decisions that changed the situation or proved impact. If you cannot find any, fix that problem before buying more tools.
  • Bring the CFO in earlier.CMOs who build the strongest organizational trust do not wait until budget season to prove marketing value. Before campaigns even launch, they involve the CFO in discussions about what success should look like.
  • Separate the AI roadmap from the decision roadmap.Most organizations invest heavily in AI but not in the change management around it. Technology can accelerate output, but it must be used correctly to drive outcomes.
  • Define what "growth engine" specifically means in your business.AI can only drive growth when the definition is specific. Choose a metric that truly impacts the big picture—incremental sales lift, revenue contribution, new customer acquisition—and make it your proof.

Takeaways from Cannes

The best conversations Bastian left Cannes with were not about new AI use cases, but about how to build an organization capable of acting on intelligence.

The brands winning now are those with the clearest path between learning and action. They have not only decided that AI will move the business forward, but more importantly, they have built the structures to turn intelligence into measurable outcomes.

That is how you cross the threshold into an outcome-driven era and bridge the gap between data and decisions. Speed gets you a seat at the table, but proof is what keeps you there.