Workday embeds Google Cloud AI agents into enterprise finance workflows

Workday is embedding Google's Gemini AI into its finance apps, automating expense requests, spend management, and reporting through natural language prompts. Financial data stays put via zero-copy sharing between Workday and BigQuery.

Categorized in: AI News Finance
Published on: Jun 01, 2026
Workday embeds Google Cloud AI agents into enterprise finance workflows

Workday Embeds AI Agents Into Finance Workflows With Google Cloud

Workday is integrating Google Cloud's Gemini AI directly into its finance applications, letting teams automate spend management, expense requests, and monthly reporting without switching tools. The partnership makes Gemini the default AI model for Workday's Sana Self-Service Agent, giving finance staff access to conversational AI for policy queries and corporate card eligibility checks.

Employees can now ask the system questions about financial policies and generate expense requests through natural language prompts. The AI maintains existing security permissions and approval chains, so no process gets bypassed.

Data stays in place

Workday Data Cloud now connects to Google Cloud's BigQuery using zero-copy data sharing. This means both platforms query financial data where it already lives instead of copying or moving sensitive records between systems.

For finance teams, the benefit is faster analysis of financial risks and business trends without creating duplicate datasets or exposing data in transit.

Deployment underway

Workday and Google Cloud are working with KPMG, Deloitte, and Accenture to roll out the technology. The system integrators will help companies identify where AI agents can have the most impact.

The Sana Self-Service Agent in Gemini Enterprise is currently in early access for eligible Workday customers. The data integration feature reaches general availability later this year.

For finance professionals looking to understand how AI for Finance and AI Agents & Automation apply to your workflows, these tools represent a practical shift toward embedded AI rather than standalone applications.


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