Rob Jones

AI initiatives don't fail because of models. They fail because of weak data foundations. For AI leaders, the real challenge is ensuring their organization has the data literacy, governance, and operating discipline required to move from experimentation to production. This session focuses on how to assess and upgrade your organization's data readiness to support reliable, scalable AI systems.

• Assess and benchmark your organization's data & AI readiness - Identify gaps in data quality, accessibility, ownership, and literacy that are blocking AI deployment 

• Design a practical data literacy strategy for AI adoption - Define what different roles (execs, operators, engineers) need to understand, and how to scale that capability across the business 

• Build governance frameworks that enable AI - Develop aligned data and AI governance models covering quality, access, risk, and compliance, without creating bottlenecks