The Web Data Infrastructure Layer for AI
As AI demand scales, enterprises require robust data foundations. The MIT Technology Review piece positions data infrastructure as the backbone of reliable AI—governing data quality, accessibility, and security. For practitioners, this underscores the need to invest in data catalogs, schema governance, and scalable storage architectures that support retrieval-augmented generation and advanced analytics. The piece also highlights the risk of data silos, latency, and governance gaps when building AI-native platforms. The practical implication is to treat data infrastructure as a strategic product with clear owners, SLAs, and ongoing optimization loops to unlock AI value at scale.