Viewpoint: Architecting a Flexible and Governed Data Foundation for AI
June 8, 2026
Organizations are expanding their use of generative AI, copilots, and agentic AI, but problems arise when you attempt to deploy agentic AI without sufficient data architecture discipline.
As enterprises move from experimentation to production, the focus is shifting away from simply deploying models toward building architectures capable of supporting AI at scale. Fragmented data environments, tightly coupled platforms, inconsistent governance, and siloed systems are increasingly becoming barriers to operationalizing AI.
To better understand these challenges, TDWI spoke with Jim Lebonitte, GTM platform & architecture AFE leader at Snowflake. According to Lebonitte, organizations need architectures that are flexible enough to evolve alongside a rapidly changing AI landscape.
Download this special Viewpoint today for advice on creating an environment that is flexible, interoperable, governed, and capable of supporting both structured and unstructured data at scale.