One of the first things I learned as an anthropologist was that observing people is not the same as understanding them.
Anthropologist Clifford Geertz called this “thick description.” The task is not simply to record behavior; it is to interpret what that behavior means within the context of a person’s life. A wink and a twitch may look identical to an outside observer, yet one carries social meaning and the other does not. That distinction is easy to miss when we focus only on what is visible.
I think about that often when I hear executives describe AI-powered customer insight. Our models have become extraordinarily good at detecting patterns. They know what customers click, buy, abandon, compare, and search for. They can predict with impressive accuracy what someone is likely to do next.
But prediction is not interpretation.
AI can tell you that millions of customers hesitate before completing a purchase. It cannot tell you whether that hesitation reflects financial anxiety, decision fatigue, fear of making the wrong choice, or a family ritual of discussing significant purchases before buying. Those behaviors may look identical in the data while representing very different human experiences.
That is the strategic risk I see emerging for innovation leaders. As AI systems become more powerful, many organizations are becoming better at observing customers while becoming less practiced at interpreting them. The danger is not that companies will stop being customer-centric. The danger is that they will become customer-centric in a way that is increasingly behavioral and increasingly detached from meaning.
Anthropologist Mary Douglas spent much of her career showing that people do not make decisions as isolated individuals. Their choices are shaped by culture, identity, ritual, social norms, and ideas about what is appropriate, admirable, safe, or aspirational. AI is becoming excellent at recognizing individual preferences. It is still far less capable of explaining the cultural systems that give those preferences significance.
This is why storytelling remains a strategic capability, even in highly data-driven organizations. Stories reconnect behavior to context. They help us understand not only what customers do, but how they make sense of their world. They reveal motivations that rarely appear in dashboards because they are rooted in identity rather than transaction.