Thursday, April 2 | 12:00 PM Eastern Time (ET) |
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| Managing Director, HBR-AS |
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| Managing Director, HBR-AS |
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Agentic artificial intelligence (AI) promises faster decisions, autonomous action, and material productivity gains. As a result, many organizations have raced to deploy it in an effort to capture its potential.
Yet for all their investment and executive sponsorship, many enterprise AI and agentic AI initiatives struggle to deliver reliable outcomes at scale. The reason is not model quality or executive support. It is data. In this webinar, Harvard Business Review Analytic Services and Quantum Metric will explore: |
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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; and
- how gaps in data completeness, context, and continuity undermine confidence in AI-driven insights after initial deployment.
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