Powering Agentic AI with AI-Ready Data Platforms That Turn Data Into Intelligence
Agentic AI demands a new enterprise data category—agent context—forcing storage to become systems of context.
“Storage needs to evolve. It needs to move from being what we've always known as a system of record, to now a system of context.”
NVIDIA's VP of Storage Technology argues that agentic AI creates a third enterprise data category—agent context (KV cache, memory, embeddings, scratch)—alongside structured and unstructured data, requiring storage systems to serve agents operating 24/7 at machine speed rather than human pace. This reframes enterprise storage from passive record-keeping to active context management, a significant architectural shift for legacy infrastructure. The framing positions data readiness—not model capability—as the primary bottleneck for enterprise AI adoption at scale.