Databricks Turns Genie Into an Autonomous Enterprise AI Coworker

Databricks on November 11, 2026, introduced a new Genie that it describes as an autonomous AI coworker for continuous, long-running enterprise work. The assistant can run scheduled or event-triggered jobs, follow up on missing information and manage several assignments at once, while users decide which actions require approval.

Databricks says thousands of customers already use Genie in production. The new version is intended to take responsibility for the work around an analysis: monitoring changes, requesting input and acting as new information arrives. Its examples include routing insurance claims that move outside underwriting guidelines and proposing marketing budget changes for approval.

Business Context and Search

At the center is Genie Ontology, now generally available. It automatically builds reusable knowledge snippets from dashboards, SQL queries and notebooks, while Unity Catalog Pages and Metric Views preserve explicitly governed definitions. Databricks’ OntoRank system weighs source authority, certification, user relevance, popularity and recency to select context and resolve conflicting definitions.

Genie Search is also generally available for Google Drive, Jira, Confluence and Workday, with SharePoint in beta. It indexes content from those systems, enforces their permissions before returning results and can combine the index with SQL and MCP connectors, which retrieve live information and take actions in external tools. Organizational directories, also generally available and beginning with Workday, add reporting relationships and collaboration signals to help rank relevant knowledge.

Not every component is generally available. External BI knowledge sources are in beta, initially supporting Power BI, and Ontology Manager for reviewing and curating the ontology is coming soon in beta.

Genie Agents Add Documents and External Sharing

Alongside the core assistant, Genie Agents can now analyze PDFs, slide decks and other documents alongside governed tables in Public Preview, returning page-level citations. Native MCP connectors are generally available, allowing agents to retrieve context and take actions such as creating tickets, updating records and posting messages. OpenSharing and Genie Clean Rooms are in beta for use with partners and customers.

OpenSharing provides a governed agent preloaded with data, instructions and knowledge across Databricks accounts. Clean Rooms instead lets recipients ask questions without seeing the underlying data or proprietary logic, with conversation and output-size controls. Databricks reports that General Motors has deployed more than 1,000 Genie agents across sales, engineering, supply chain and HR operations, illustrating the multi-department model the company is pursuing.

Administrative Controls and Benchmark Results

The autonomy is paired with Unity Gateway controls. Traces capture the question, answer, cited objects, response time and actions, giving administrators a queryable record of Genie’s work. Administrators can restrict MCP tools, require approvals, set budgets and spending caps, and review usage. Genie acts under each user’s identity and can prepare an access request, but administrators and data owners retain approval authority.

Genie One, the interface for this work, also creates slide decks, dashboards and interactive pages, with scheduled refreshes and shared skills for repeatable workflows. Databricks says Genie One is free for users through January 31, 2027, and that more detailed cost controls will be available before then.

To support its emphasis on context, Databricks released a benchmark developed with Turing. In the company’s evaluation, Genie passed 91% of task runs, compared with 58% for the stronger of two anonymized frontier agents, while averaging 431,829 tokens and 100.3 seconds per run. Each agent ran every task five times in the same workspace for a fictional UK energy supplier containing tables, notebooks, dashboards, saved queries and documents, including outdated and duplicated assets.

Databricks cautions that the test reflects an established deployment with accumulated business knowledge; differences may be smaller in new deployments or when table schemas alone are sufficient. That limitation defines the central enterprise requirement in this launch: broader autonomy depends on governed, accessible institutional knowledge, with administrators deciding which jobs and actions Genie can take on.