Is Your Data Working For (or Against) You and Your AI Initiatives?

Is Your Data Working For (or Against) You and Your AI Initiatives?

With generative AI, it’s tempting to assume the model can “just find the answers.” In practice, the models are commoditized. What differentiates successful AI programs is how well they’re grounded in your company data. Most organizations that fail at AI do so because their data isn’t ready to support real decisions at real scale. Data lives in too many places, definitions vary across teams, quality issues get discovered late, and governance is either missing or so heavy it slows everything down. The result is that promising AI pilots that can’t be trusted, can’t be repeated, and can’t be deployed.  

In this webinar, Dr. Tim Oates shares a practical, business-aligned approach to making your data an asset for AI (and analytics) rather than a bottleneck. You’ll learn how to assess data readiness, strengthen the pipelines and controls that matter most, and build a lightweight operating model so teams can move fast and produce reliable, measurable outcomes.  

In this webinar, you’ll learn how to:  

- Diagnose whether your data is actually “AI-ready” (and what that means in practice)

- Define the few data standards that unlock consistency: ownership, definitions, lineage, and quality checks

- Build a pragmatic “minimum viable” data foundation: pipelines, documentation, access, and monitoring

- Prioritize the data work that drives ROI without boiling the ocean

- Set up governance that enables deployment: privacy/security, auditability, and change control