While traditional applications tolerate messy data, advanced AI agents demand real-time precision. Data entropy – the natural degradation of information value over time, is the leading hidden bottleneck in enterprise AI deployment. To build systems that can truly compress decision cycles and act independently, enterprises must shift from reactive storage to proactive data management.