Use agentic AI in ServiceNow Otto for Public Sector Digital Services (PSDS)
Summarize
Summary of Use agentic AI in ServiceNow Otto for Public Sector Digital Services (PSDS)
ServiceNow Otto for Public Sector Digital Services (PSDS) offers the AI Agent Studio, enabling administrators to configure, test, and manage standalone AI agents and agentic workflows using natural language and prebuilt workflows. These AI agents automate specific tasks such as fee estimation and handling information requests, improving efficiency in government service operations.
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Key Features
- AI Agent Studio: A tool for administrators to create and manage AI agents that automate tasks relevant to public sector digital services.
- Use Cases: Includes estimating fee breakdowns for information requests, providing subtotal fee estimates, fee waiver recommendations with rationale, and total fee calculations.
- Supported Large Language Models (LLMs): Now LLM Service, Azure OpenAI, Google Gemini, and Anthropic Claude on AWS can be selected as AI model providers. Configuration controls allow defining available options and setting skill-level preferences.
- Security Implementation: AI agents and workflows operate under Access Control Lists (ACLs) with Run As capability, allowing execution as dynamic or AI users. Role masking restricts access to users with specific roles, which must be configured accordingly.
- Autonomous AI Agent Execution: To run AI agents autonomously, agentic workflows need to be duplicated, activated along with their agents, and have unique triggers enabled. Manual invocation is also supported without activating triggers.
- Standalone AI Agents: Some AI agents may exist outside workflows; administrators can view and manage all available AI agents within the instance.
Practical Implications for ServiceNow Customers
By leveraging agentic AI in ServiceNow Otto for PSDS, customers can automate complex tasks like fee estimation, thereby reducing manual effort and improving service delivery accuracy. Administrators gain control over AI agent behavior through the AI Agent Studio and can ensure compliance and security via ACLs and role-based access. The flexibility in choosing AI model providers and managing autonomous workflows allows customers to tailor AI capabilities to their specific public sector needs while maintaining governance and security standards.
Use standalone agents to achieve specific automated outcomes with the Public Sector Digital Services AI Agent Collection application.
AI Agents are configurable through the AI Agent Studio. The AI Agent Studio is available to administrators as part of the ServiceNow Otto for Public Sector Digital Services (PSDS) offering. The AI Agent Studio allows admins to configure, test, and manage AI agents using natural language and prebuilt workflows. These agents can automate tasks like fee estimation and information request handling.
| Use case | Description |
|---|---|
| Estimate fee breakdown for an information request | Helps government service agents determine the fee breakdown for an information request by working to arrive at a subtotal fee estimate, a recommendation for whether a fee waiver request should be approved or rejected, including reasons for any rejection, and a total fee estimate, with the fee waiver, if applicable. |
Find information such as the Large Language Models (LLM) supported in ServiceNow Otto and security controls that are important considerations for using agentic AI.
Supported Large Language Models
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You can use Now LLM Service, Azure OpenAI, Google Gemini or Anthropic Claude on AWS as the AI model provider for all generative AI skills and AI agents. Use the Configuration Controls in AI Control Tower to define which options are available, then set the skill-level preferences in the AI Admin Hub console. For more information, see Large language models on the ServiceNow AI Platform®.
- For the Now LLM Service updates, see Now LLM Service updates.
Security implementation considerations
Enable security implementation to execute AI agents and agentic workflows through Access Control Lists (ACLs) and user identities. ACLs provide the Run As capability to let agents and agentic workflows execute actions either as a dynamic user or as an AI user. For more information, see Implement access control in AI agents
Agentic workflows and their AI agents use role masking to determine which users can access them. Ones installed with your applications have specific roles that come included with the application. If you select Users with specific roles for user access, you must configure the security controls to include these roles. For the instructions to change the security controls, see Define security controls for an agentic workflow.
AI agents use role masking to determine which users can access them. Ones installed with your applications have specific roles that come included with the application. If you select Users with specific roles for user access, you must configure the security controls to include these roles. For the instructions to change the security controls, see Define security controls for an AI agent.
Considerations for running the autonomous AI Agents
To run the AI agents autonomously, you must first duplicate the agentic workflow, and then proceed with the following steps:
- Activate the agentic workflow.
- Activate all agents within the agentic workflow.
- Activate the trigger to invoke the agentic workflow automatically. The triggers for each agentic workflow must be unique. If you prefer to invoke it manually, activating the trigger isn’t necessary.
- Azure OpenAI is recommended for ITSM agentic workflows. For information on Large Language Models (LLMs) for AI agents and agentic workflows, see Large language models on the ServiceNow AI Platform®.
Standalone AI agents
There might be AI agents installed on your instance that are not used in agentic workflows. To learn how to see all agents that are available to you, see Find AI agents.
For information on the standalone Public Sector Digital Services AI agents, see Standalone AI Agents in Public Sector Digital Services.