Agentic AI for Operational Technology Service Management
Summarize
Summary of Agentic AI for Operational Technology Service Management
The Agentic AI for Operational Technology Service Management (OTSM) enables autonomous task completion using AI agents within ServiceNow. This capability focuses on automating key operational tasks, such as generating knowledge base (KB) articles after incident resolution, to improve efficiency and knowledge sharing in OT environments.
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Key Features
- Agentic Workflows: Predefined workflows like "Generate OT KB articles" automate tasks such as creating KB articles post-incident resolution using AI agents (e.g., OT knowledge generator AI agent).
- Customization: Agentic workflows are inactive by default. Customers must duplicate and customize workflows to fit their specific needs, requiring the
snaia.adminrole for duplication and activation. - AI Model Support: Supports multiple large language model providers including Now LLM Service, Azure OpenAI, Google Gemini, and Anthropic Claude on AWS. Customers can configure preferred models via AI Control Tower and AI Admin Hub.
- Security Controls: Implements Access Control Lists (ACLs) and role masking to control user access and execution permissions for AI agents and workflows, ensuring secure operation.
- Autonomous Execution: To run AI agents autonomously, customers must duplicate, activate the agentic workflow and its triggers. Triggers must be unique unless workflows are invoked manually.
- Standalone AI Agents: Some AI agents may exist independently of workflows and can be managed separately.
Key Outcomes
- Improved Incident Resolution Documentation: Automatically generating KB articles after OT incident resolution ensures essential information is captured and easily accessible for future reference.
- Enhanced Operational Efficiency: Automating routine knowledge generation reduces manual effort and accelerates knowledge dissemination.
- Flexible and Secure AI Integration: Customers can tailor AI workflows to their operational needs while maintaining strict security and role-based access controls.
- Support for Multiple AI Providers: Allows leveraging best-fit language models for generative AI capabilities within the ServiceNow platform.
Practical Next Steps for ServiceNow Customers
- Review and duplicate the provided agentic workflows to customize them according to your OT service management processes.
- Assign necessary roles, especially
snaia.admin, to users managing AI workflows. - Activate the duplicated workflows and configure unique triggers to enable autonomous execution.
- Use AI Control Tower and AI Admin Hub to select and manage large language model providers best suited for your environment.
- Implement and verify security settings including ACLs and role masking to maintain compliance and restrict unauthorized access.
- Leverage the "Generate OT KB articles" workflow to automate knowledge capture post-incident, improving documentation and operational knowledge sharing.
Use the Operational Technology Service Management (OTSM) AI agent collection to complete tasks autonomously.
| Agentic workflow name | Description | Available AI agents |
|---|---|---|
| Generate OT KB articles | After OT incident resolution, the AI agent automatically creates a KB article with relevant contextual information. | OT knowledge generator AI agent |
The minimum role needed to duplicate an agentic workflow is the sn_aia.admin role. By default, the OTSM agentic workflow is inactive. To use the base system agentic workflow, activate the base system trigger. To customize the agentic workflow, duplicate it.
Supported Large Language Models
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®.
Security implementation considerations
Enable security implementation to execute AI agents and agentic workflows through Access Control Lists (ACLs) and user identities. For more information, see Implement access control in AI agents
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.
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.
Role masking
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.