🔍 AI Is Exposing How Much Work We Never Defined
AI is often described as disruptive because it is new. In reality, it feels disruptive because it refuses to operate inside ambiguity we have quietly relied on for years. When AI struggles, it is rarely because the task is too complex. It is because the work was never clearly defined in the first place. ------------- Context ------------- Most organizations run on a mix of formal processes and informal understanding. Some work is documented, standardized, and repeatable. Much more work lives in habits, conversations, and “the way we usually do things.” Humans are remarkably good at navigating this ambiguity. We fill in gaps without noticing. We infer intent. We compensate for missing steps. We rely on experience and social cues to keep things moving. AI does none of that naturally. It needs clarity. Inputs, rules, definitions, boundaries. When those are missing, AI does not quietly adapt. It fails visibly. That failure is uncomfortable, but it is also diagnostic. AI is showing us where work has always depended on tribal knowledge rather than shared understanding. ------------- The Hidden Dependence on Tacit Knowledge ------------- Tacit knowledge is what people know but rarely write down. It includes how to prioritize when everything is urgent. Which requests can wait. Who really needs to be looped in. What “good enough” means in different contexts. These judgments are learned over time, often through mistakes. Because tacit knowledge works, it feels efficient. Writing it down feels unnecessary. Until someone new joins. Or until work scales. Or until we ask AI to help. When AI enters the picture, tacit knowledge becomes a bottleneck. The system asks questions humans never had to articulate. What counts as complete? Which exception matters? When do we escalate? AI exposes how much of our work relies on shared assumptions rather than shared definitions. ------------- Why Informality Has Been Carrying More Weight Than We Admit ------------- Informal work has always absorbed complexity.