The biggest mistake leaders can make with AI is confusing what the technology is capable of with what organizations are capable of.
Over the past two years, we've watched AI capabilities advance at an astonishing pace. Every week seems to bring a more powerful model, a smarter agent or a new application that promises to transform how businesses operate. It's tempting to assume organizations will evolve just as quickly.
They won't.
Enterprise transformation has never worked that way. Technology can move overnight. Organizations change through leadership, incentives, operating models and people. That's why the companies creating real value from AI today aren't necessarily the ones with the most advanced technology. They're the ones redesigning how work gets done.
I was reminded of that at Cannes Lions this year.
Most people think of Cannes as a marketing festival, and it is. But it's also one of the few places where founders, technology companies, investors and global brands come together in one ecosystem. The most valuable conversations I had weren't about the latest AI product launch. They were with entrepreneurs building capabilities that most executives haven't heard of yet—but that offer an early signal of where business is headed.
This year, one trend stood out.
Marketing is becoming one of the first major business functions to reorganize itself around AI-native capabilities.
The lesson isn't about marketing. It's about leadership.
Recent McKinsey research identifies five capabilities that are reshaping how organizations connect with customers: continuously translating customer signals into decisions, generating personalized content at scale, tailoring every customer interaction, ensuring brands are discoverable by AI agents, and orchestrating those capabilities as an integrated system rather than a series of disconnected campaigns.
The specifics matter less than what they represent.
These capabilities don't fit neatly into yesterday's organizational chart. They cut across traditional roles, require new decision rights and demand different ways of working. Marketing happens to be where many organizations are confronting that reality first. Every function will soon follow suit.
That's why I worry when AI conversations focus primarily on technology adoption.
Across industries, I still see companies experimenting with AI, deploying point solutions and testing pilots. Those are necessary steps. But very few have begun redesigning workflows—or reimagining entire business domains—in an AI-native way.
That helps explain why so few organizations have captured meaningful value from AI at scale. It’s not because the technology has fallen short. It’s because enterprise change is hard. Too often, boards ask for visible AI progress. Technology teams respond by building impressive tools. The business inherits them later and struggles to integrate them into the way work actually happens.
Transformation rarely works in that direction.
The most successful AI efforts are business-led. They begin with a strategic question: What problem are we trying to solve? How could AI fundamentally change the way we create value? Only then does the technology become part of the answer. That distinction matters because AI's greatest opportunity isn't simply to improve productivity.
Productivity is important. Every company should pursue it. But you can't cut your way to prosperity.
Long-term value—for companies and for society—comes from growth.
The organizations that pull ahead will be the ones that use AI to understand customers more deeply, personalize experiences more effectively, develop new products more quickly and create business models that weren't previously possible. They'll leverage technology not just to optimize existing work, but to fundamentally improve the way they compete.
That's ultimately what I took away from Cannes.
The most interesting thing I saw wasn't a breakthrough demo or a clever new application. It was a preview of what organizational transformation actually looks like.
Because AI strategy isn't ultimately about deploying better technology. It's about building an organization that can continuously adapt, learn and grow alongside it.