The arrival of AI has exposed a growing organizational fault line. Although AI and IT are often grouped together as “technology,” they typically operate with very different priorities: IT emphasizes control, standardization, and risk reduction, while AI depends on experimentation, flexibility, and rapid learning. Through three case studies, the authors show how these competing logics create conflict over data, capabilities, and infrastructure, slowing AI adoption and limiting business value. Organizations that succeed do not force one function to dominate the other. Instead, they clarify roles, expand governance to encompass new forms of data, align AI ambitions with IT readiness, and establish shared accountability for business outcomes. The result is less friction, stronger collaboration, and greater competitive advantage from both AI and IT.