Databricks launches always-on Genie AI agent for firms

Databricks has launched the second generation of Genie, positioning it as an always-on autonomous AI agent for enterprise work. The update expands its push to embed AI agents in existing corporate data and software environments.

The new version is designed to run continuously in the background and handle longer-running tasks without repeated user prompts. Workers can assign a goal, set boundaries, and let the system track progress, follow up on missing inputs, and return when a person needs to make a decision.

The launch also includes Genie Search, intended to give staff and software agents a single governed search layer across structured and unstructured information, and new features in Genie Ontology, Databricks' framework for capturing business definitions, metrics, reporting lines, and processes.

The product operates within a customer's existing Databricks environment and remains subject to security, permissions, and approval controls already set through Unity Catalog and Unity Gateway. Every action is auditable.

Databricks is targeting a common point of tension in the adoption of AI agents by large organisations. While many companies are experimenting with tools that can answer questions or complete tasks, concerns remain about giving those systems access to financial planning data, customer records, and internal documents.

Under the new model, Genie can be used for operational work such as monitoring quarterly forecasts, tracking revenue trends, analysing employee survey responses, and identifying changes in customer usage patterns. The system can delegate work to sub-agents, present outstanding issues in a priority inbox, and send email alerts when user input is required.

Search layer

Genie Search extends the product beyond the Databricks lakehouse to business applications including Google Drive, Jira, and Confluence. Teams can either index content where it already sits, ingest it through Lakeflow Connect, or query applications live through MCP.

Databricks now offers more than 100 connectors to support those approaches. Instead of searching each application separately, users and agents can search once across multiple sources, reducing tool calls and token usage, according to the company.

That search function is tied to Genie Ontology, which Databricks describes as a way to maintain an up-to-date understanding of how a company defines its data and how its people and processes fit together. The latest release adds support for business logic from external business intelligence tools and introduces an organisational structure connector.

Databricks also introduced Ontology Manager, a new interface for teams to manage and govern business context. The tool can recommend areas for refinement by flagging concepts that are frequently queried.

Broader access

Another part of the update is wider distribution of Genie across third-party AI and workplace tools. Users will be able to access Genie through a web browser, mobile app, email, and collaboration and AI products including ChatGPT, Claude, Microsoft Copilot Cowork, and Grok Bot.

The release also broadens the content Genie agents can work with. Agents can now operate across PDFs, contracts, and slide decks in Unity Catalog volumes alongside governed tables, without the need for a separate vector index.

Databricks is also adding dynamic slides, dashboards, and interactive reports that remain tied to governed data and update as that data changes.

Ali Ghodsi, Co-founder and Chief Executive Officer of Databricks, said the product is already changing how he works. "Genie has made me a 10x more productive CEO, and now it doesn't wait for me to ask," Ghodsi said. "Every day, Genie keeps up with my inbox, preps me for meetings, and runs in the background, coming back only when it needs a decision. It can do that because it knows how our company works: what we mean by revenue, which numbers are official, and who can see what. That's the power of horizontal context, and Genie delivers it."

Partners and customers also described governed business context as central to adoption. "Teams make their best decisions when trusted context shows up in the flow of work. With Genie Agents now connected to Slack, sales, finance, and operations teams can go from question to action without leaving the conversation. We're thrilled to work alongside Databricks to bring governed, reliable insights to where the work happens," said Jaime DeLanghe, Chief Product Officer of Slack.

Headspace pointed to the role of agreed definitions in reducing ambiguity in AI outputs. "AI is only as good as the definitions behind it, so we built our Genie Agents on agreed, governed definitions, and now every answer matches. We expanded self-service analytics by putting plain-language access to our data in the hands of teams across the business, not just analysts, so people can act on numbers they trust," said Marlissa Wong, Director of Data Engineering at Headspace.

HelloFresh cited a measurable effect on advertising decisions. "With Genie constantly analysing performance signals, we've improved programmatic ad ROI and reduced the time to identify ad winners on Meta by 75%. Unity Gateway gives us the flexibility to use the best model for each job without managing separate integrations," said Alan Khalil, Associate Director of Data Science and Engineering at HelloFresh.

Databricks said Genie and Genie Ontology are generally available, while Genie Search, Ontology Manager, and the always-on version of Genie are being rolled out through preview and beta programmes.