Key takeaways
- People across every business have questions that data can answer.
- We’re introducing a new Data agent in ChatGPT Work(opens in a new window) to help more people answer those questions themselves.
- The Data agent connects to approved data sources including Amazon Redshift, Datadog, Google BigQuery, ClickHouse, Databricks, MongoDB…
What happened
People across every business have questions that data can answer. Why did sales slow down? Where is spending rising? Which issues threaten renewals in our largest accounts, and what should we fix first? Getting those answers often means waiting for a report or asking someone else to run the analysis.
Ask ChatGPT Work to recommend next steps and identify who needs to be involved. It can share the findings through Slack or email and carry out the actions you approve through connected tools. We use the capabilities behind the Data agent broadly across OpenAI. Nearly all of our product team and over two-thirds of our GTM organization use data agents in ChatGPT Work to analyze company data themselves.
Our data team made this possible by creating shared business definitions, setting access rules, and putting safeguards in place for sensitive data. Learn more by reading this post(opens in a new window) and attending our webinar(opens in a new window).
Why it matters
We’re introducing a new Data agent in ChatGPT Work(opens in a new window) to help more people answer those questions themselves. It connects to your company data, investigates what changed, and builds interactive dashboards you can share. Direct and refine the analysis in one conversation, without writing queries or learning a new analytics tool.
The Data agent connects to approved data sources including Amazon Redshift, Datadog, Google BigQuery, ClickHouse, Databricks, MongoDB, Snowflake, and more. It can also bring files and documents from Google Drive and SharePoint into the analysis. It uses your organization’s business terms, metric definitions, custom calculations, and data relationships to interpret the data.
This context comes from semantic layers and trusted sources such as Databricks Genie Ontology, dbt, GitHub, Snowflake Horizon, and BI dashboards. Enterprise administrators choose which data connections are available and which roles can use them. Queries enforce the connected account’s existing permissions, including table, row, and column restrictions. Ask follow-up questions to investigate the results and review the evidence behind each finding.
Turn the analysis into an interactive dashboard with built-in visualizations. Your team can edit, share, and refresh it as needed. Share your brand guidelines to tailor outputs to your organization’s look and feel. The Data agent can also build and interact with dashboards in Omni, Oracle BI, Power BI, Sigma, Tableau, and ThoughtSpot. Direct the work in plain language in the tools your team already uses.
What to watch
NTT Data, Thermo Fisher, ServicePiston, and other organizations in our Alpha program are using the Data agent in ChatGPT Work to analyze sales and spending, catch reporting errors, and decide which opportunities to pursue and how to staff them. You’ll find the Data agent listed as Data(opens in a new window) in the Plugins directory in ChatGPT Work.
Administrators can make it available or install it for their teams through Workspace settings > Plugins. They can also enable and configure the relevant data-source plugins, such as Databricks and Snowflake, and manage who can use them. If Data isn’t already installed, find it in the Plugins directory and select Install plugin, or go directly to the Data listing(opens in a new window). Complete any required account-connection steps, then start a conversation with @Data and ask your business question.




