A.I. has upended the playbook for modern brands, promising to flatten geography, automate insight and make physical presence obsolete. But here’s the dangerous paradox: local, cultural understanding isn’t less important in the age of A.I., it’s more vital than ever. That’s the tension branding and marketing teams everywhere are wrestling with right now.
The tech is dazzling. A.I. is fast, efficient and gives the illusion that you no longer need boots on the ground. With endless dashboards and algorithm-driven predictions, it’s tempting to think every market can be decoded from HQ. It echoes how wars are increasingly being fought: drone operators in remote control centers, dropping bombs as if they were playing video games. Yet military leaders will insist that being on the ground is critical to having a complete picture of the battlefield.
The same is true in the brand world. Today, centralized branding and marketing teams leaning heavily into A.I. for their strategic and creative needs are putting their companies at risk. Strategic plans generated from cloud dashboards and clean data sets only paint part of the picture. Data tells us what people are doing, but not why they’re doing it, what their choices signal about shifting values and trends or how to speak to them in ways that feel authentic. Algorithms can model behavior, but they can’t interpret cultural meaning.
Here’s a true story, and a case in point. A prominent, multinational beauty conglomerate contacted our agency to bring one of its key skincare brands to the U.S. market. Their research showed a major opportunity with Black and Latina consumers. I knew enough about the brand to know their core demographic back home did not resemble those audiences. Keeping an open mind, I asked how much the marketing team knew about the communities they wanted to reach.
“Are you familiar with the skin concerns consumers in these markets often talk about—like ashy skin?” I asked, referring broadly to how consumers describe experiences with skincare culturally, linguistically and even generationally.
“Umm, no,” came the reply.
I followed up with: “Does your line include ingredients these consumers often look for, like cocoa butter or certain natural emollients?”
Again: “No.”
The issue wasn’t ignorance; it was distance. Their global-first thinking had led them to pursue an opportunity that they didn’t yet understand. This isn’t about calling anyone out. It’s a cautionary tale about what happens when teams mistake demographic data for cultural understanding. Surface-level “insight” becomes a substitute for genuine cultural fluency.
No amount of data sophistication can replace the nuanced understanding that comes from being physically present, embedded in the cultural fabric of the markets a company serves. While A.I. excels at pattern recognition and efficiency optimization, it fundamentally lacks the cultural literacy required to navigate the subtle complexities that define successful market entry and sustained growth. This is especially critical for categories where identity, beauty, language and trust are intertwined—food, apparel, personal care—where lived experience and cultural nuance shape product expectations far more than broad behavioral trends.
Nearly two decades ago, I met with prolific entrepreneur and investor Kevin Ryan, who founded and sold the early online ad agency, DoubleClick. He asked what my vision was for our agency.
“A boutique, global branding agency, with offices that never exceed 35 people in multiple locations.”
Eyebrow raised, he replied, “Wouldn’t it just be easier to put 1,000 people on Madison Avenue?”
He was right. It would have been easier. But coming off an eight-year stint of explosive growth at DKNY—when it went from a small, domestic fashion brand to a global powerhouse—an enduring message lesson emerged: how we acted and communicated with Japanese consumers was far different than with, say, French or Brazilian audiences. This need for localization would only become more pronounced as the internet took hold. This is increasingly proving to be true.
Today’s winning global organizations don’t cling to rigid hierarchies. They work more like ecosystems, balancing shared infrastructure like tech platforms and brand frameworks with real decision-making authority and strategic autonomy for local teams. That’s how you get strategies with global reach and local context.
One promising way forward? Some firms are turning to models based on licensing, not just acquisition. This allows new partner teams to plug into bigger networks but still operate with independence and, most importantly, with in-market expertise. Consider the many global brands that spent years forcing centrally produced creative into regional campaigns. Performance lagged until they shifted to a local-operator model, empowering small in-market teams to adapt messaging, imagery and pacing. The results are often immediate: higher conversion rates, sharper sentiment and a sudden ability to compete with regional upstarts that had been eating their lunch. When global brands partner with teams who speak the language, understand the customs and have skin in the game, they dramatically improve their odds of making a real mark.
Brands can possess the most sophisticated data infrastructure, the most advanced A.I. models and the most efficient centralized operations. Without understanding local cultures, the chances for success are greatly reduced. Simply put, culture determines whether a brand is embraced or rejected, if a message resonates or falls flat and if it is seen as authentic or opportunistic. When paired with creativity—real creativity, not algorithm-generated variations on existing themes—something magical happens.
But this is also where A.I.’s limits become clear. A.I. can remix aesthetics, generate variations and approximate tone, but it cannot originate cultural references responsibly. It doesn’t understand humor that lands differently in Mumbai than in Manchester. It can’t intuit symbolism or avoid local taboos, and it certainly can’t feel the textures of lived experience that make creative work resonate. Left unchecked, A.I. defaults to the generic middle—safe, pattern-driven and culturally sterile.
Local presence is now a strategic differentiator. Leaders who pair the efficiencies of A.I. with empathy and feet on the ground will shape the future of global commerce—zip code by zip code, neighborhood by neighborhood, customer by customer. The rest now risk being left behind, and faster than they think.
