Google updates Workspace to make AI your new office intern

Google's Workspace Intelligence introduces automated functions driven by its AI system, shifting LLM capabilities into the enterprise workflow. This moves AI from isolated RAG applications into deeply integrated operational tools. The change is in how LLMs handle data access and operational automation at scale.

Implementing this requires redefining data governance. The cost of maintaining reliable context for agents running on proprietary data can escalate rapidly if data indexing is not architected correctly. A system built on GPT-4 for internal knowledge base search must account for potential context leakage if the underlying RAG pipeline is not hardened.

Teams running RAG in production must treat enterprise AI not as a feature, but as infrastructure. The core principle is context isolation. Do not rely solely on API calls for enterprise knowledge retrieval; implement a local vector store using Haiku to maintain control over the 500,000 tokens of internal data.