As AI investments scale, many organizations struggle to clearly demonstrate business value beyond technical performance metrics. Model accuracy, experimentation velocity, and adoption rates rarely answer the questions executives and boards actually ask.

This session focuses on how enterprises can design AI ROI metrics that translate directly into financial impact, risk reduction, operational efficiency, and decision quality. We’ll explore why traditional analytics KPIs fall short for AI initiatives and share practical frameworks for measuring value across real-world use cases such as automation, fraud detection, personalization, and decision intelligence.

Attendees will learn how to align AI metrics with business strategy, communicate impact to senior leadership, and build the measurement foundations needed to scale AI responsibly and confidently.

Key Takeaways:

Why most AI ROI metrics fail in the boardroom

Practical frameworks for measuring enterprise AI value

How to communicate AI impact to executives