Why agentic AI breaks without decision-grade data.

As agentic AI gains momentum, many organizations are still struggling to turn investment into reliable outcomes at scale. The issue is not executive buy-in or model quality. It is the strength of the data behind the decisions. Organizations need data that is complete, contextual, and trustworthy enough to support AI over time. Without it, even confident answers can be hard to verify.

In this on-demand webinar, Harvard Business Review Analytic Services and Quantum Metric explore:

• How senior leaders evaluate whether their data foundations can support advanced AI use cases, particularly in areas involving complex real-world customer and digital experience data.
• Why partial, siloed, or deteriorating data sets create risk for executive decision-making.
• How gaps in data completeness, context, and continuity undermine confidence in AI-driven insights after initial deployment.