Limitations of Robotic Process Automation (RPA) bot generation skill

  • Release version: Zurich
  • Updated July 31, 2025
  • 3 minutes to read
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    Summary of Limitations of Robotic Process Automation (RPA) Bot Generation Skill

    The RPA bot generation skill has several limitations that affect its functionality, particularly regarding AI Search, component support, and version compatibility. Understanding these limitations is essential for effectively using the skill within your automation projects.

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    Key Features

    • AI Search and LLM Timeout: The skill relies on AI Search and large language models, which have timeout limits and rate-limiting behaviors impacting the bot generation.
    • Component Scope: The initial version supports a limited number of components. Instructions involving unsupported components may not generate the expected automation workflow.
    • Plugin Version Compatibility: The skill utilizes Yokohama version plugins. If methods from these plugins are incompatible with the LLM, they will appear as unknown components in the workflow.
    • Dynamic Configuration: Dynamic configuration for supported components is not available in the Yokohama release, requiring manual configuration.
    • UI Action Suggestions: For Windows, Java, or browser applications, generic UI actions must be configured manually, as specific methods may not be automatically populated.
    • Expression-based Components: Components requiring expressions will not have automated population in the Zurich release.
    • Hallucinated Components: If the LLM returns non-existent methods, they will be marked as unknown in the workflow.

    Key Outcomes

    Be aware of these limitations to avoid confusion and ensure successful RPA automation projects. Properly configuring components and understanding plugin compatibility will enhance your ability to generate effective automation workflows using the RPA bot generation skill.

    The limitations of the RPA bot generation skill are as follows.

    AI Search and LLM timeout
    The RPA bot generation skill relies on AI Search and large language models (LLM) to understand the user instructions and flow creation. The timeout limits and rate-limiting behavior of these APIs collectively apply to the RPA bot generation skill. For more information about AI search system properties, see AI Search system properties. For more information about API rate limits, see Inbound REST API rate limiting. For more information about configuring rate limiting for providers, see Configure rate limiting for providers.
    Component scope in Yokohama release
    The initial version supports few components. Components outside this scope don't appear in the generated automation workflow. For example, if you provide an instruction, such as Capture a screen shot and save it in the location at 'C:\Users\Screens', the generated automation workflow might not contain the Capture component because it isn’t included in the initial version components list. For more information about the list of supported components, see Supported components and connectors for Now Assist for RPA Hub in Yokohama release.
    Plugin version compatibility
    The feature uses Yokohama version plugins. If the large language model (LLM) returns a method that doesn’t exist in the loaded plugin version, then such methods are displayed as unknown components in the generated automation workflow. For example, if you’re using Washington DC version plugins within an existing automation project and provide an instruction to set or get values from an application, then the SetValue, GetValue, or Click methods of the Universal App connector are displayed as unknown components in the generated automation workflow.
    In the following example, to get the weather information, data reader components are required. Since they are not available in the current scope, they appear as UNKNOWN components in the automation preview.
    Figure 1. Unknown components in the Automation preview
    Automation preview section displays UNKNOWN components.
    If you select Next in the previous screen, the automation appears as follows on the Design surface.
    Figure 2. Unknown components on the Design surface
    Design surface displays UNKNOWN components.
    Usage of existing connectors in new activity using Now Assist or build automation context menu options
    During the automation workflow creation, if a method, such as the AddNewWorksheet method of Microsoft Excel connector is created, RPA Desktop Design Studio checks for an existing global object of the same connector type and uses the most recent one. In the following example, the Badging Data Microsoft Excel connector is used.
    Figure 3. Microsoft Excel connectors in Global Objects
    Project Explorer section displays Microsoft Excel connectors in the Global Objects. Badging Data Microsoft Excel connector is selected.
    Dynamic configuration
    Dynamic configuration for supported components isn’t available in the Yokohama release. You can configure components manually. For example, you must give inputs in the configuration window for the Microsoft Excel connector's SetCellValues method. Select the settings icon (Settings icon.) to view the configuration window.
    Data in the parameter values might not be populated in the large language model (LLM) generated components.
    Figure 4. Configuration window for SetCellValues method
    Configuration window for the SetCellValues method is displayed.
    Automation for Windows, Java, or browser applications
    For automating Windows, Java, or browser-based applications, RPA Desktop Design Studio suggests generic UI actions such as SetValue, GetValue, or Click. These actions are a part of the Universal app connector. You must configure these actions manually, including capturing screens and adding elements via the field window. For more information about these methods, see Universal app connector.
    Expression-based components
    For components that require expressions, such as Decision or Expression, and so on, expressions in these components aren’t automatically populated in the Zurich release.
    Hallucinated components
    If the large language model (LLM) returns a method that doesn’t exist in the RPA Desktop Design Studio, then such methods are displayed as unknown components in the generated automation workflow.