ATechReview

Before the Model Context Protocol (MCP), enterprise AI governance faced a fundamental architectural problem: AI agents accessed data through dozens of custom integrations, direct database connections, REST API calls, and SDK-based queries—each with its own authentication, its own data retrieval logic, and its own (usually absent) governance configuration. Enforcing consistent access controls, masking, lineage capture, […]

Every enterprise transformation initiative of the past decade has included “AI” somewhere in its vision statement. Very few have included a serious accounting of the data infrastructure transformation that AI production actually requires. The result is a growing gap between AI ambition and AI reality—a gap that is becoming more visible, more expensive, and more […]

Enterprise analytics has gone through three generations in forty years. Operational reporting. Business intelligence and OLAP. Self-service analytics and machine learning at scale. Each generation delivered genuine productivity gains—but each also arrived with a hidden constraint: it was built on a data platform designed for the workloads of its era, not the workloads of the […]