Manage alerts autonomously agentic workflow
Summarize
Summary of Manage alerts autonomously agentic workflow
The Manage alerts autonomously agentic workflow in the Zurich release leverages AI to streamline IT alert management, significantly reducing resolution times. This unified workflow automates key alert management tasks, including triage, impact analysis, root cause investigation, and reporting. It enhances operational efficiency by providing AI-driven insights and summaries that help prioritize and resolve alerts effectively.
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Key Features
- AI-Driven Triage and Categorization: Automatically evaluates and categorizes alerts while analyzing alert history to reduce noise and update alert group descriptions.
- Impact Analysis: Assesses the impact of alerts on IT services and users by correlating with recent incidents, cases, and service health metrics using observability skills.
- Root Cause Investigation: Retrieves and summarizes similar past alerts, analyzes recent changes, related knowledge base articles, logs, and metrics to identify trends, anomalies, and potential causes.
- Contextual Insights: Classifies alerts as proactive or reactive and provides failure scenario contexts and consequences if alerts are unaddressed.
- Summary and Reporting: Consolidates findings into clear, actionable summaries stored directly in alert records, including reasoning, evidence, and confidence levels, facilitating informed decision-making and automatic closure of insignificant alerts.
- Integration with Service Observability: Offers health analysis of services associated with alerts to provide deeper insights into service states.
- Express List AI Insights: Enables monitoring and review of AI-generated alert insights via badges, columns, and filters in the Express List interface for practical alert status tracking.
Practical Considerations for ServiceNow Customers
- The workflow is enabled by default, ensuring immediate benefits without additional configuration.
- To customize the workflow, duplication and careful updating of AI agent instructions are required to maintain accuracy and effectiveness.
- Customers can access detailed AI-generated insights and summaries directly within alert records and Express List, supporting proactive and informed alert management.
Expected Outcomes
By implementing the Manage alerts autonomously agentic workflow, ServiceNow customers can expect faster alert resolution through AI-driven automation, reduced alert noise, improved accuracy in impact and root cause analysis, and enhanced visibility into IT service health. This leads to more efficient IT operations and better allocation of resources to critical issues.
Enhance IT operations with AI-driven, autonomous alert management using the manage alerts autonomously agentic workflow.
Manage alerts autonomously agentic workflow overview
- Automates the triage
- Impact analysis
- Root cause investigation of IT alerts
- Generates reports, summarizes key insights and possible next steps
For information on how to review key insights and data derived from the workflow in Express List, see Review AI-generated alert insights in Express List.
For information about configuring this workflow, see Configure the manage alerts autonomously agentic workflow.
Use the information on this page to learn about the actions related to the manage alerts autonomously agentic workflow. To modify the workflow, you must duplicate it and adjust the settings according to your requirements. For more information, see Duplicate an agentic workflow.
Manage alerts autonomously agentic workflow
The manage alerts autonomously agentic workflow uses the manage alerts AI agent to perform alert management and resolution tasks.
| AI agent | AI agent role |
|---|---|
| Manage alerts AI agent | Investigates alerts, summarizes alert-related reports, and stores structured insights with key findings. |
The manage alerts autonomously agentic workflow performs several actions in the course of the workflow. These actions may include the following:
- Triages alerts
- Evaluates and categorizes alert
- Analyzes alert history to identify noise patterns
- Updates alert group description based on analysis
- Performs related incidents analysis to detect focal points and common closure patterns
- Determines alert impact
- Evaluates impact on services
- Determines user impact by finding recent incidents or cases
- Uses observability skills for deeper service state validation
- Investigates relevant information
- Retrieves and summarizes similar closed alerts
- Analyzes recent changes for causal relationships
- Summarizes related KB articles for relevant information
- Identifies trends or anomalies in related metrics
- Uncovers errors, exceptions, or warnings in related logs
- Analyzes non-primary log analytics alerts in an alert group to support investigation, including the following:
- Classifies alerts as proactive or reactive, indicating emerging risk or an active issue
- Assess if triage is required
- Provides contextual insights, including potential failure scenarios and what may occur if the alert isn't addressed
- Summarizes and stores information
- Consolidates findings
- Generates a final summary
- Saves the summaries in the alert record, such as
- reasoning, evidence, and confidence level behind AI-driven investigation of alert significance and automatic closure of insignificant alerts
- summaries of Service Observability dashboards to provide health analysis of each service associated with an alert. For more information see, Analyze service health in Service Observability
- Provides clear, actionable insights