Analyze potential impact agentic workflow
Summarize
Summary of Analyze potential impact agentic workflow
The Analyze potential impact agentic workflow in ServiceNow Zurich release helps you assess how a change request might affect operational servers and suggested services. By using AI-driven analysis, it provides targeted insights into the potential impact, enabling informed decision-making about change management steps. The workflow saves its findings directly to the change request work notes for traceability.
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Key Features
- AI Agent Integration: Utilizes the Analyze Potential Impact Agent to evaluate change requests by identifying relevant operational servers and matching them with suggested services.
- Workflow Steps: Includes verifying prerequisites, retrieving the change request number, selecting up to 10 affected servers, identifying matches to suggested services, and prioritizing impact analysis results.
- Impact Reporting: Displays up to 10 impacted servers and up to 3 related suggested services with summaries describing potential effects, all within the ServiceNow Otto panel.
- Service Mapping AI Skills: Enhances analysis with generative AI capabilities that classify application services (Service Mapping Candidate skill) and assess change impacts on infrastructure dependencies (Service Mapping Candidates Impact skill).
- Default Activation: The agentic workflow and associated AI skills are enabled by default, simplifying adoption.
Practical Considerations
- The workflow excludes non-operational or retired servers, focusing only on active infrastructure.
- Domain separation is currently unsupported, and conversations should be conducted in English for optimal results.
- The impact analysis is saved automatically in the change request work notes, ensuring documentation continuity.
Benefits for ServiceNow Customers
This workflow empowers customers to:
- Quickly identify risks and benefits associated with change requests by understanding affected servers and services.
- Make more informed decisions regarding change implementation based on AI-generated impact assessments.
- Leverage intelligent service mapping to uncover hidden dependencies and service classifications, improving change management accuracy.
- Maintain comprehensive records of impact analyses within change requests to support audit and compliance needs.
Using the Analyze potential impact agentic workflow streamlines impact evaluation, reduces manual effort, and enhances confidence in change decisions within the ServiceNow platform.
The analyze potential impact agentic workflow analyzes how a change request might impact servers and suggested services. This analysis helps you make informed decisions about the next steps regarding the change request.
Analyze potential impact agentic workflow overview
AI agent used in the analyze potential impact agentic workflow
| AI Agent | AI Agent role |
|---|---|
| Analyze Potential Impact Agent | Analyzes the potential impact of a change on relevant servers and services and generate an impact analysis. |
Generating the impact analysis
- Prerequisite verification - The agent first verifies that all prerequisites have been met.
- Change request identification - If you have a change request open, the agent retrieves the change request number from the current active page. Otherwise, it prompts you to provide the change request number.
- Server selection- The agent selects up to 10 affected servers from the affected configuration items (CIs) in the change request.
- Match identification - The agent identifies matches between servers and suggested services.
- Impact analysis - Eventually, the agent prioritizes and displays up to 10 impacted relevant servers, giving priority to servers that are part of suggested services, and up to 3 impacted suggested services. Additionally, the agent provides you with a summary about each suggested service and how it might be impacted by related servers. This information is displayed in the panel.
- Saving the impact analysis - The analysis generated by the Analyze potential impact agentic workflow is saved to the change request work notes.
To learn more about using the workflow, see Use the Analyze potential impact agentic workflow to assess a change request.
Analyze potential impact agentic workflow sample report
Domain separation
Currently, the analyze potential impact agentic workflow doesn’t support instances with domain separation. For optimal results, conduct all conversations in English.
Service MappingServiceNow Otto Skills
Service Mapping AI skills are intelligent capabilities that enhance the Analyze potential impact agentic workflow. These skills leverage generative AI to identify, classify, and assess the impact of changes to your IT infrastructure.
- Service Mapping Candidate
- Service Mapping Candidates Impact
Service Mapping Candidate skill
This skill automatically identifies and names processes and application service candidates by analyzing process characteristics, commands, and parameters. It provides detailed descriptions and categorization to help you understand which services are running in your environment.
The skill uses a two-stage process:
- In the process classification stage, the agent uses the skill to analyze individual processes within an application service candidate. The agent uses the skill to extract:
- Publisher: The company or organization that released the product. For example: "Project Calico".
- Product: The specific product name. For example: "Calico".
- Description: Detailed explanation of what the process does. For example: "BIRD (BIRD Internet Routing Daemon) process running as part of Calico networking solution for Kubernetes and container orchestration. This process handles BGP routing functionality with remote control socket enabled, running as a daemon with specific Calico configuration for pod-to-pod networking and network policy enforcement."
- Service Hints: Keywords that help identify the service type. For example: "bird,calico,BGP,routing,daemon,networking,kubernetes,container,policy,socket".
- In the service information generation stage, the agent combines process details with load balancer information to generate:
- Service Name: A concise, accurate name for the service candidate. For example: "Calico BGP Routing Service".
- Service Description: A comprehensive description of the service's purpose. For example: "BIRD Internet Routing Daemon process running as part of Project Calico's networking solution for Kubernetes container orchestration. This service handles BGP routing functionality for pod-to-pod networking and network policy enforcement, operating as a daemon with remote control socket capabilities. The component is connected through Calico's container networking infrastructure to provide routing services in Kubernetes environments".
- G2 Category: Industry-standard categorization from G2.com. For example: "Container Networking".
Service Mapping Candidates Impact skill
This skill generates comprehensive impact assessments when changes are made to your infrastructure. It analyzes service connections and dependencies to predict how a change to a single component might affect other services and servers, and provides a summary of the impact analysis.
- Connection Topology: How servers within a service candidate are connected.
- Affected Servers: Which servers are directly impacted by a change.
- Service candidate: "bird [ASC000000015]".
- Impact: "Network routing disruption affecting pod-to-pod communication across Kubernetes cluster nodes due to Calico Bird BGP routing daemon failure on p-kubenode1-2, potentially causing connectivity issues for workloads on connected nodes p-kubenode1-3, p-kubenode1-4, and p-kubenode1-5".