As organisations push to scale AI, many are finding that legacy data foundations are not fit for purpose. Siloed architectures, inconsistent standards and poor data quality are limiting the ability to operationalise AI and deliver measurable outcomes. The challenge is no longer building data platforms—but ensuring data is trusted, accessible and aligned to real business use cases. This panel will explore how leading institutions are evolving their data strategies to enable AI at scale. 

• How can you transform fragmented, siloed data into standardised, interoperable and trusted assets?
• How can you leverage metadata, lineage and governance to make data discoverable and usable at scale?
• How can you align data initiatives with clear business use cases to ensure AI delivers measurable value?