Use Case

AI Governance

A robust framework for supporting AI governance and tracking AI initiatives

Ensure AI governance enables AI innovation

AI and AI agents are rapidly spreading across organizations — embedded in more applications and business processes every day. To stay ahead, robust AI governance must be a cornerstone of enterprise architecture management.

This requires full visibility into your entire IT landscape so you can assess AI potential, put effective governance practices in place, and stop risks from spiraling across countless AI and agent deployments.

Gain that visibility and control with the AI governance extension to the SAP LeanIX meta model, designed to cover any AI technology. For AI agents specifically, the AI agent hub delivers dedicated discovery, management, and governance capabilities. Read on to learn how these capabilities help you maximize the value and minimize the risk of your AI initiatives and agents.

98 %

of companies have deployed or plan to deploy AI agents — but only 17% have visibility into agent performance or conformance

48 %

have no clear roles or responsibilities for AI agents

63 %

say EAs should lead AI agent governance — yet only 34% are actually involved today

Report

SAP LeanIX Agentic AI Survey 2026

International study reveals high adoption of AI agents – but gaps in effective management

Get your free copy

How it works

Discover AI in use across your landscape

Use our out of the box integrations to discover AI agents and MCP servers
Review discovered AI agents and MCP servers for architectural relevance, and review suggested linkages to factsheets in your inventory
Once imported, connect AI technologies to related architectural elements, such as business capabilities, applications, and IT components
Streamline the linking process and leverage reference catalog data for SAP AI agents

See how the AI Agent Hub in SAP LeanIX gives you full control over your AI agents — from discovery to retirement.

Learn more

Comprehensively evaluate AI

Capture AI-related information on business capabilities and applications including AI usage, AI risk, and AI potential, giving you a complete understanding of where the technology is implemented across your IT landscape
Categorize where AI has the potential to enhance productivity, user interactions, or transform existing processes
Identify which applications benefit the most from introducing AI technologies and prioritize your initiatives accordingly

Track AI-associated risks

Gain full visibility of your potential AI risk exposure for all applications
Cross-reference AI risk with AI usage and potential AI benefits
Identify the applications scored with the highest AI risk to prioritize further investigation and mitigation actions

Chart AI adoption and standardization

Add AI technologies, such as LLMs, to your lifecycle visualizations, capturing the maturity and adoption of different AI technologies in your organization
Leverage the maturity and level of adoption assessment to identify AI technologies that are candidates for standardization
Track the approval status of AI agents throughout their lifecycle with the predefined AI agent governance report

Envision and plan your AI-related transformations

Plan your AI initiatives and document key information such as timeline, resources, and associated applications or IT components
Create detailed roadmaps for transforming business capabilities and applications with AI and ensure alignment with all relevant stakeholders
Maintain an overview of your AI projects and track progress

Track and report on AI adoption and governance

Monitor KPIs for AI agents via the Architecture Executive Dashboard
Provide centralized visibility into all relevant reports and visualizations by creating a dashboard for AI governance
Guide AI governance policy and support AI technology management by surfacing insights to key stakeholders