Existing data platforms suffice for AI
The guest argued that enterprises do not need to build exotic new data systems for AI, as existing modern data platforms serve as the ideal foundation.
The argument
George (CEO of Fivetran) noted that leading AI labs like Anthropic build typical data foundations using standard tools like Fivetran, Snowflake, Databricks, or BigQuery rather than exotic architectures, leveraging them to feed context into AI workflows.
The thesis, stress-tested
✓ What validates it
- ✓Increased enterprise adoption of Iceberg tables and Snowflake/Databricks for AI context retrieval
- ✓Public case studies of enterprises successfully deploying LLMs using existing SQL-based data warehouses
▸ Risks discussed
- ▸Emergence of highly specialized vector databases that completely displace traditional warehouses
- ▸High costs of running continuous data replication for real-time AI context
Hear it yourself
"The idea that they're going to use AI to value engineer the number of seats they have on Slack or something is ridiculous. They're going to use AI to go make their business work better in whatever it is that they do. They're actually going to. They're not trying to take that 5% software spend and turn it into four and a half. That is not the highest, best use of a I mean, I mean, famously, all the big AI labs, including, I mean, Andreessen Horowitz, and we're all very heavy users of AI, like, still use these SaaS tools. And so four years into this, we don't have a lot of evidence that, like As do we, as do OpenAI and Anthropic Exactly."
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