Webinar | Navigating AI Shockwaves in Higher Education: Part 3

A Collaboration with Gartner | 2026 EDUCAUSE Mission Partner

AI-Ready Data: Beyond the Myths of Modern Data Governance

Early adopters of AI frequently focused on traditional data quality, assuming that standard cleanup efforts would ensure their data was ready for advanced modeling. However, many organizations that already possess data quality and master data management programs are discovering a surprising reality: existing data governance frameworks, as they are currently known, are not enough to achieve true AI readiness.

In this webinar, we will explore how AI operates as the ultimate data reuse case that fundamentally changes how data is revised, updated, and governed. We will address the common myths and misdirections that have historically plagued advanced analytics, and examine how these challenges resurface in the age of AI. Attendees will walk away with an understanding of two distinct approaches to AI-ready data: a fast path that accelerates implementation, and a more rigorous path designed for maximum confidence and reliability.

Learning Outcomes:

• Define "AI-ready" data by identifying the essential pillars of quality, structure, and compliance.
• Evaluate the "fast path" to AI readiness, weighing its speed against potential trade-offs and risks.
• Maintain data readiness over time by using an ongoing process for monitoring and governance.
• Bridge the gap to production by using AI-ready data to accelerate and scale your model deployments.