IDC research shows 72% of US public sector leaders struggle to scale AI from pilot to production. The core challenge is data readiness, not model selection. Governments need a governed retrieval layer — federated knowledge access — that connects authoritative, often unstructured data to AI agents while preserving sovereignty, auditability, and compliance. Key architectural priorities include hybrid retrieval (lexical + semantic search), open integration protocols like MCP, and built-in security controls such as permission filtering and audit logs. The post outlines how agencies can meet regulatory requirements (EU AI Act, NIST AI RMF) and achieve mission outcomes including faster case management, cybersecurity, and citizen services.
Table of contents
What is next-generation knowledge access?Why governments are under pressure to scale AIOperationalizing AI is really a data readiness problemWhy agentic AI raises the stakes on retrieval qualitySovereignty and governance are now architecture decisionsWhat next-generation knowledge access actually looks likeMission outcomes agencies can expectWhat public sector leaders should prioritize nextTake the next stepShare73 Impressions