As businesses increasingly rely on data and AI to drive decisions, many data and AI leaders are looking for an optimal way to organize data roles. Many teams struggle to achieve their mission due to outdated organizational models, poor collaboration, and rapid technological advancements. While there is no universal solution for structuring data teams, data leaders can use rules of thumb and benchmarks from analogous companies along with the unique characteristics of their organization to set an organizational path. Adopting flexible, adaptive strategies and fostering cross-functional collaboration will make teams resilient and capable of navigating complexity and rapid change to serve enterprise data and AI needs.