AI Governance Extension to the Meta Model

Overview

The AI governance extension to the meta model provides you with improved AI governance and adoption tools, allowing you to effectively track, manage, and categorize AI usage and risk. The extension enables you to adopt best practices for modeling AI in your workspace for both commercial off-the-shelf (COTS) and self-built software.

With the AI governance extension, you get the following benefits:

• AI integration and governance: Integrate AI technologies into your IT landscape, ensuring they align with your organization's policies and standards. Establish standards for assessing AI risk and business criticality.
• AI adoption: Create a shared understanding of where AI adoption can most benefit the organization and make AI adoption visible across the IT landscape.
• AI impact overview: Understand how AI technologies impact various aspects of your IT landscape.

By using the AI governance extension, you can get valuable insights, such as:

• Objective: How does generative AI contribute to your business objectives?
• Business capability: Which business capabilities have high potential for efficiency or automation?
• Applications: Which AI algorithms and large language models (LLMs) are available and applied for which use case in applications?

Activating the AI Governance Extension

Admins can activate the AI governance extension in the administration area.

Follow these steps:

1. In the administration area, select Optional Features & Early Access under Advanced Settings.
2. In the AI Governance & Adoption section, click Activate, then confirm your action.

Meta Model Extension

With the AI governance extension, the following changes are applied to the meta model:

• The Governance section is added to application fact sheets, with the AI Governance and Adoption subsection that contains single-select attributes designed to capture data on AI usage, type, risk, and potential. Use this section to track and manage applications and systems that use AI, evaluate associated risks and benefits, and ensure that AI usage aligns with your business strategy.

  

• The AI Potential Assessment subsection is added to business capability fact sheets, with the AI Potential single-select attribute that allows you to assess how the organization can benefit from the current state of AI for this business capability.

  

• The LLM subtype is added to IT component fact sheets, which enables you to create dedicated fact sheets for LLMs.

  

• The Technology Assessment subsection is added to IT component fact sheets, featuring the AI Radar Classification field within that section. This enables you to assess selected technologies effectively and establish clear technology governance, and it facilitates the visualization of AI classification within your IT landscape through the Technology Radar report.

Getting Insights through Reports

Once you have gathered the data, generate reports to gain insights into your application portfolio. This allows you to identify where new AI technologies are already in use and where there are opportunities for improvement and increased efficiency.

For example:

• Using an application landscape report, you can easily identify which key business capabilities are at risk arising from AI usage or which business capabilities can leverage AI better. To do so, in the application landscape report clustered by business capabilities, you can apply AI Risk or AI Potential as a view. To learn how to use reports, see Using LeanIX Reports.

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Tip

Apply the AI Available filter from the filter bar to display only those applications that use AI capabilities.

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Note

To avoid overwhelming users with too many view attributes and to keep the interface lean, many fields are hidden by default in the View drop-down menu in reports. In the meta model configuration, you can choose to include or exclude attributes based on your needs. To learn more, see Showing Fields in Filters and Views.

• You can also use a business capability landscape report to get a consolidated view to identify and prioritize business capabilities with high potential for AI adoption.

  

• With the IT component matrix report, you can assess which AI algorithms and large language models (LLMs) are supporting which applications. To do so, in the IT component matrix report settings, select Application for one of the axes and apply the necessary view for your analysis.

• Using the technology radar report, you can gain insights into your AI governance and adoption status. From the radar report settings, choose AI Radar Classification for the sector category. To learn more about radar reports, see Radar Report.