How AWS helps education leaders prioritize AI investments

This article provides a framework for education leaders to evaluate and prioritize AI investments by connecting spending to measurable business value rather than just managing costs.

• Most organizations exceed AI budgets because spend is unmanaged and loosely tied to outcomes
• AI spend spans four areas: customer-facing features, internal solutions, employee tooling, and infrastructure—rarely viewed together
• Visualize the entire AI portfolio on one page using AWS Cost Explorer, cost allocation tags, and Amazon Bedrock cost attribution
• Tie spending to value by assessing which investments drive outcomes and are actually used
• Use a shared grid showing cost, value, and flexibility to make cross-functional prioritization decisions
• Apply the same evaluation lens to both existing investments and future roadmap plans
• Build repeatable mechanisms for ongoing AI investment evaluation as technology and costs evolve
• AWS helps through portfolio consolidation, data-informed roadmap decisions, and accelerating build-to-production cycles

Education leaders can optimize AI ROI by implementing a disciplined, repeatable process to see their complete portfolio and make strategic investment decisions together.