This chapter explains how AI can help those with education system level leadership responsibilities make better, faster choices. It starts by examining four big governance problems: unclear accountability, limited capacity, weak/slow data, and poor resource allocation. It then shows how AI can help—by letting people ask questions in everyday language (NLP), by analyzing and forecasting with large datasets (ML), and by speeding up feedback loops so action is more rapidly informed by evidence. Real-world examples include smarter budgeting and teacher placement, early-warning systems to prevent dropout, skills-needs planning, citizen feedback platforms, and automated service desks. The chapter also warns about risks—poor data, bias, privacy, equity gaps—and says strong foundations, clear rules, human oversight, and capacity-building are essential. It closes with practical takeaways for policymakers and developers, plus research questions on inclusion, accountability, capacity, and regulation.