Organizations are racing to deploy artificial intelligence, committing billions in investments while struggling to articulate clear returns. Finance leaders face mounting pressure from boards demanding accountability - yet many lack the frameworks, metrics, and methodologies to quantify AI's business impact. This session addresses the critical gap between AI ambition and financial reality. Explore how to establish rigorous evaluation criteria before AI investments begin, ensuring alignment with strategic objectives and measurable outcomes. Learn to build business cases that withstand board scrutiny, track meaningful KPIs beyond cost savings, and communicate progress in language that resonates with executive leadership. Discover why traditional ROI calculations often fail for AI initiatives—and how to adapt your measurement approach for emerging technologies with longer time horizons and diffuse benefits. Key Takeaways - Build Strong Business Cases: Frameworks for evaluating AI investments before deployment, including risk assessment, benefit mapping, and realistic timeline modeling. - Measure What Matters: Move beyond vanity metrics to identify and track KPIs that demonstrate real business value -productivity gains, revenue impact, risk mitigation, and competitive advantage. - Communicate ROI Clearly: Strategies for translating complex AI outcomes into compelling narratives for boards and executives, tracking benefits realization, and maintaining investment discipline.