The struggles of Business Intelligence (BI) serve as a warning for the challenges that Artificial Intelligence (AI) may face when scaling. Despite significant investments and technological advancements, BI adoption has stalled due to issues such as data access not being enough, complexity overwhelming self-service initiatives, trust being fragile, people and processes lagging behind technology, and speed without strategy leading to waste. To avoid repeating these mistakes with AI, organizations need to focus on building a strong data foundation that ensures consistent, governed, and accessible data. A universal semantic layer is crucial in unifying data from multiple sources, standardizing business logic, and providing governed access to both AI and BI. By getting the data right, organizations can improve the success of their AI initiatives and avoid repeating the struggles of scaling BI.