Enzai MCP server
Connects to your AI.
Any MCP-compatible agent gets the same governed connection, right where your teams already work.
Some of our integrations
Workflow tools
Jira, ServiceNow
Model providers
Anthropic, OpenAI
Agent tools
Copilot Studio, Claude Enterprise
Development environments
Azure AI Foundry, Amazon Bedrock, Databricks

Glossary

Responsibility Assignment Matrix

Responsibility Assignment Matrix

Responsibility Assignment Matrix

A tool (e.g., RACI) that clarifies roles and accountabilities for each governance activity: who’s Responsible, Accountable, Consulted, and Informed.

A tool (e.g., RACI) that clarifies roles and accountabilities for each governance activity: who’s Responsible, Accountable, Consulted, and Informed.

Updated

A governance artifact that maps activities (risk assessment, validation, monitoring) to stakeholder roles, identifying which team performs the work (Responsible), which role signs off (Accountable), who provides input (Consulted), and who receives updates (Informed). RACI matrices ensure clear ownership, avoid gaps or overlaps, and facilitate smoother governance execution.

Example

A technology division’s AI governance RACI chart assigns: Risk Assessment (R: Risk Team, A: Chief Risk Officer, C: Data Science Leads, I: Business Unit Heads); Model Validation (R: Validation Team, A: Head of Compliance, C: External Auditors, I: Data Scientists). This clarity streamlined handoffs and reduced review delays by 30%.

Govern the AI you actually use.

Govern the AI you actually use.

Govern the AI you actually use.

Start with what’s in use.

Start with what’s in use.

Start with what’s in use.

Book a demo and we’ll show you how Enzai finds the AI in use, gives each system an owner and keeps the record.

Book a demo and we’ll show you how Enzai finds the AI in use, gives each system an owner and keeps the record.