New data agents across the Agentic Data Cloud

The rise of AI agents is fundamentally disrupting applications and analytical systems. Generic AI platforms don’t usually have access to the context stored within enterprise databases. This is because traditional data architectures often lack context for agents across the data estate, which can lead to agents being inaccurate. They’re also prone to security gaps due to a lack of granular access controls. 

Google’s Agentic Data Cloud is an AI-native system of action that includes both operational and analytical systems. By infusing AI across the entire stack — from custom silicon to frontier Gemini models — we provide a deterministic, template-driven developer framework that allows agents to ground their reasoning in real-time enterprise data with near-100% accuracy, as well as unified governance.

Today, we’re making it easier to develop agents, with a whole host of new data agents and tools: for business analysts within Conversational Analytics; for data scientists, engineers, and database admins with a series of Google-built Data Agents that provide greater automation and intelligence; and finally, for developers, with Data Agent tools that help you better integrate with today’s open agentic ecosystem.

1. Conversational Analytics

To support developers building agents using natural language, we’re announcing expanded support for Conversational Analytics across Data Cloud.

• Conversational Analytics in BigQuery, in preview, integrates a sophisticated AI reasoning engine directly into BigQuery Studio, helping data and business teams go beyond writing manual SQL, leveraging business context to ground answers using multimodal synthesis and deep-dive research. Agentic workflows, in preview for select customers, automate root-cause analysis, and schedule actions — turning enterprise data into proactive, actionable intelligence.