As we enter the agentic AI era, applications that were once human-driven are now powered by autonomous agents that perceive, reason, and act on our behalf. This introduces three major shifts that flip the script on data strategy in the age of AI.

We are witnessing a non-linear explosion in demand as agents extend human abilities. A single employee can now create agents that trigger thousands of queries a minute. Agents do work humans cannot sustain. They monitor business data 24/7. They act in real time. Systems must now support the velocity and scale of the agent and amplify the intuition of the human.

It is no longer enough to analyze the past, or even predict based on it. An agent executes in the moment. In the agentic era, systems must close the loop between signal and resolution, allowing data to act on the world as fast as the world changes.

Agents need total access to your data estate, including the 90% of untapped information hidden in dark data, such as contracts, images, and emails. Yet data alone does not yield understanding. To turn this raw material into knowledge, agents need rich semantic context.

When you build on Google Cloud, you benefit from the same technology that runs Google. Your agents are grounded in DeepMind research. You get native access to Earth Engine, Weather, and Google Trends, so your agents can correlate business data with global signals to understand the real world. Instead of merely observing your business, your data becomes a proactive System of Action—powered by the Agentic Data Cloud.

Agents require access to 100% of your data to function effectively. We tear down silos, bringing multimodal AI to data, regardless of where it lives. With Google Cloud Lakehouse, and support for open formats like Apache Iceberg, we are delivering the best of Google and open standards, allowing agents to activate data on AWS, Azure, and on-premises without movement. This Open Lakehouse approach delivers a 117% ROI with a payback period of under six months.

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The bridge between intelligence and action is trust. Our Knowledge Catalog evolves beyond simple permissions to provide active, universal context across unstructured data, ML models, and agentic tools that power AI, improving agent effectiveness and accuracy. By integrating Looker and our semantic knowledge engine, we ground your agents in truth, improving dataset identification accuracy by 50% and reducing gen AI hallucinations by up to 66%.

Unlock trustworthy AI

With Google, AI is built in, not bolted on. We’re the only provider uniquely engineered across the entire AI supply chain—owning everything from the global fiber network and TPUs to the Gemini models and Gemini Enterprise Agent Platform. Because we own the stack, we create intelligence 8–16x more cost-effectively than competitors. Gemini integrates directly into the stack to solve problems in fewer steps. BigQuery advanced runtimes deliver 6x faster queries, Apache Spark runs 4.5x faster than open-source Spark with Lightning Engine, and AlloyDB handles transactional workloads 4x faster than standard PostgreSQL.

Read the GigaOm report

The Agentic Data Cloud transforms the core disciplines of your data estate. Supercharge your data team productivity and streamline how AI agents interact with your data.

This role shifts from model training to agent building. By integrating Gemini Enterprise and Spark, data scientists build reasoning engines that sit right next to the data. Instead of batch predictions, they build agents that use our knowledge engine to reason over live data and react instantly.

Analytics becomes a trusted conversation rather than a SQL retrieval task. Agents sit between the user and the data, generating queries and visualizations through BigQuery and Looker. These agents can be made securely accessible through the Gemini Enterprise app. This gives employees a tireless team of data analysts.

To move from thinking to doing, developers need a database that can handle an agent’s thought process. We merge transactional and analytical worlds through AlloyDB and Spanner. Developers can now build agents that read history and take action in a single logical loop. By standardizing how agents connect to tools via the Model Context Protocol (MCP), we enable direct execution, bridging perception and action.

The Data Agent Kit bundles secure MCP tools, native IDE plugins, and pre-codified data science skills into a single open-source package. By bringing these capabilities directly into tools like Antigravity, VS Code, and Claude Code, it empowers you to shift from manually writing pipeline code to intent-driven development across your entire data estate.

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