Your AI Strategy Has an Unstructured Data Problem: How to Build an AI-Ready Data Foundation for Enterprise AI Core
If your organization is struggling with AI success, you probably have a data problem. And you’re not alone: “Nearly half of enterprises say their AI projects have been delayed, underperforming, or outright failed because of poor data readiness.” Most enterprise AI strategies assume that if the model is good enough and the data is accessible, useful outcomes will follow. But accessibility is not the same as readiness. Information may technically be available to an AI system, but it often lacks the structure, metadata, context, governance, provenance, and quality signals needed for reliable enterprise use.
Join us for this webinar from Hyland, where you will be challenged to rethink AI-ready data as an enterprise data discipline that must include unstructured information. You’ll discover
- The critical steps for an AI-ready data architecture
- How to address the common barriers to data-readiness
- Why accessible data isn’t enough - and how insights, context, and intent make data AI-ready
- How to unlock the promise hidden in unstructured data
