Step 4: Standardize AI Usage

Standardizing the usage of AI technologies is a critical step in effectively managing and controlling their adoption within your organization. By establishing common standards for AI usage, you can ensure consistency, improve interoperability, reduce complexity, and manage risks more effectively.

The Technology Radar report in SAP LeanIX is a valuable tool for this process, providing a clear overview of your technology landscape and helping you identify which AI technologies should be standardized. With this report, you can visualize IT component fact sheets of the LLM subtype and their lifecycle stages. To learn more about this report type, see Radar Report.

To adjust the Technology Radar report for this assessment, follow these steps:

1. Navigate to report settings by clicking Settings in the upper-right corner, then do the following:
   1. In the Ring Category list, select Assessment Review.
   2. In the Sector Category list, select Subtype.
2. Apply the Assessment Review view to the report by selecting it in the upper-left corner.

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Note

By default, some fact sheet fields are not included in report views to avoid overwhelming users with too many views. If certain fields don’t appear in views, adjust the corresponding settings in the meta model configuration. For more information, see Showing Fields in Filters and Views.

Here's how you can use the Technology Radar report to gain insights and standardize the usage of AI:

• Visualize your AI landscape: The report provides a visual representation of your technologies, including LLMs, categorized by their lifecycle stages (Hold, Assess, Trial, Adopt). This can help you understand the maturity and adoption of different LLMs in your organization.
• Identify AI technologies for standardization: Use the report to identify LLMs that are widely adopted and mature (in the Adopt lifecycle stage). These LLMs are good candidates for standardization.
• Monitor emerging AI technologies: The report can help you monitor emerging LLMs (in the Assess or Trial lifecycle stages) that could become future standards as they mature and their adoption increases.
• Manage AI technology risks: By tracking the lifecycle stages of LLMs, the report can help you manage risks. For example, LLMs in the Hold stage could pose risks if they're widely used in your organization.
• Inform AI governance policies: The insights gained from the report can inform your AI governance policies. For example, you could establish policies that encourage the use of standardized LLMs and discourage the use of LLMs in the Hold stage.

After gaining a comprehensive understanding of how AI technologies are used in your organization, you can plan AI-related transformations. See Step 5: Plan AI-Related Transformations.