Workday Builds a Shared Data Layer for Its Enterprise AI Agents

Workday says it has partnered with Databricks to build a universal data layer for enterprise AI agents, using Apache Iceberg for data storage and Unity Catalog for governance. The aim is to have agents query a shared foundation instead of copying data into separate stores—a design Workday says is necessary to avoid an explosion of hard-to-monitor connections as agents spread through the business.

The architectural problem is simple, even if the implementation is not. An organization with many agents and many data systems can give each agent its own direct connections. Workday describes that as a multiplicative M×N problem. Its alternative is an additive M+N model: add a data system or an agent to the common layer, rather than build another set of point-to-point links.

Apache Iceberg supplies the transactional properties beneath that setup, including ACID compliance and snapshot isolation. In plain terms, those are intended to give agents a consistent view of data while multiple agents may be reading the same datasets. Unity Catalog sits above it as the control layer for permissions, lineage and audit records.

That governance boundary matters most when an agent answers a request that crosses organizational lines. Workday says Unity Catalog provides fine-grained access controls, policy enforcement, observability and monitoring alongside lineage and auditing. Its example is a sales employee asking for account information outside their assigned territory: the agent should recognize the employee’s entitlement and withhold data they are not authorized to see.

The company is also treating memory and explanations as part of the data architecture. Workday says it keeps short-term session memory in vector stores, while preserving long-term memory in Iceberg and retaining reasoning traces. That approach is meant to let operators reconstruct why an agent produced an answer when its output is questioned.

• Accelerating finance close cycles and identifying attrition risk earlier.
• Improving supply-chain management and procurement negotiations.
• Supporting retention modeling and sales planning.

Workday says it has moved from single-agent pilots to coordinated multi-agent deployments across functions including finance, HR, procurement, supply chain, marketing and sales. It says that progression has not required replicated data stores because agents consume the shared layer. The deployment progress is a company account, not an independently published measure of accuracy or business impact.

The next challenge is interoperability. Workday says it plans to expand support for increasingly complex and varied organizational data, develop agent registries and communication protocols including MCP servers, and automate more governance and observability. Its bet is that agents will need shared rules and shared records before they can work coherently with one another at enterprise scale.