AI in ITOM Visibility

  • Release version: Australia
  • Updated July 6, 2026
  • 5 minutes to read
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    Summary of AI in ITOM Visibility

    AI in ITOM Visibility leverages generative AI and agentic workflows across multiple ServiceNow products to automate complex IT operations management tasks. These features assist administrators in automating service map creation, diagnosing discovery issues, managing certificates, requesting firewall rules, and generating incident resolution content. Access to these AI capabilities depends on your ServiceNow license tier.

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    Agentic Workflows

    Agentic workflows use AI agents to autonomously or semi-autonomously complete ITOM tasks, reducing manual effort and accelerating problem resolution:

    • Discovery Pattern Diagnostic: Automatically identifies missing Configuration Item (CI) attributes, diagnoses root causes from discovery logs, and suggests remediation, helping discovery admins quickly resolve attribute gaps.
    • Firewall Management Task Creation: Accepts natural language firewall rule requests, extracts parameters, performs risk analysis, and creates tasks, streamlining firewall rule requests for administrators.
    • Analyze Potential Impact: Assesses the impact of change requests on servers and services, providing risk analysis in the ServiceNow Otto panel and change request notes, aiding risk assessment without manual CI review.
    • LEAP Ansible Discovery Agent: Identifies relevant Ansible job templates for automation opportunities using AI semantic matching, simplifying template selection for LEAP administrators.
    • LEAP Ansible Execution Agent: Executes mapped Ansible jobs directly from the Service Operations Workspace during incident remediation, enabling seamless automation without switching platforms.

    AI Agents

    Standalone AI agents execute scheduled or triggered operations autonomously, enhancing efficiency in key ITOM processes:

    • Service Mapping AI Agent: Automatically creates service maps from ML-powered Application Service Candidates, filtering noise and populating the CMDB for administrator review.
    • Business App Mapping AI Agent: Establishes "Uses::Used by" relationships between business applications and application services via AI semantic search, reducing manual mapping effort.
    • Certificate Renewal AI Agent: Guides PKI administrators through automated TLS certificate renewal via conversational prompts, streamlining certificate management.
    • LEAP AI Agent: Converts recurring incident patterns into problem records, knowledge base articles, or playbooks based on user requests, automating artifact creation for LEAP administrators.

    Generative AI Skills

    These on-demand AI capabilities generate insights and analyses to support specific ITOM tasks:

    • Service Mapping Candidate Skill: Classifies and generates names/descriptions for application service candidates and their processes, aiding administrators in change impact analysis.
    • Service Mapping Candidates Impact Skill: Summarizes affected components and connection impacts from change requests, providing concise impact overviews for risk assessment.
    • Discovery AI Insights for Discovery Errors: Highlights the highest-impact discovery errors with summaries and recommended remediation, enabling discovery administrators to prioritize fixes effectively.
    • LEAP AI-Generated Resolution Steps: Creates structured incident resolution guidance based on grouped incidents, allowing LEAP administrators to expedite resolution plan development.

    Practical Benefits for ServiceNow Customers

    • Automate complex ITOM tasks, reducing manual workload and accelerating problem resolution.
    • Leverage natural language inputs and AI analysis to streamline firewall rule requests, certificate renewals, and service map creation.
    • Gain actionable insights into change impact, discovery errors, and recurring incidents to improve operational decision-making.
    • Integrate Ansible automation seamlessly within incident workflows for faster remediation.
    • Enhance Service Mapping and LEAP capabilities with AI-driven artifact generation and semantic relationship mapping, improving data accuracy and operational efficiency.

    AI features in ITOM Visibility help administrators automate service map creation, diagnose discovery issues, manage certificates, request firewall rules, and generate incident resolution artifacts using generative AI and agentic workflows.

    AI features in ITOM Visibility span several products. The following tables summarize all available AI features by type and product.

    Note:
    Depending on your license, you will have access to certain application features, generative AI skills, agentic workflows, and AI agents. For more information, see ServiceNow product tiers.

    Agentic workflows

    Agentic workflows in ITOM Visibility use AI agents to complete investigation and management tasks autonomously or with minimal administrator input.

    Table 1. Agentic workflows in ITOM Visibility
    Product AI feature Description Use case Resources
    Discovery Pattern diagnostic agentic workflow Investigates missing CI attributes in pattern-based discovery. The workflow identifies the attribute gap, parses discovery logs, determines the root cause, and suggests a remediation — all from the ServiceNow Otto panel. Uses two agents: the Pattern diagnostic agent and the EF Remediation Agent. A discovery administrator notices that a CI attribute is missing and wants to identify the root cause and a fix without manually navigating discovery logs and tables. Pattern diagnostic agentic workflow
    Firewall Audits and Reporting Firewall Management Task Creation agentic workflow Uses AI to accept natural-language firewall rule requests, extract required parameters, run a risk analysis, and create a rule task. The risk level determines whether the task is created automatically or requires confirmation. A firewall administrator wants to request a new firewall rule by describing it in plain language rather than filling out a form manually.
    Service Mapping Analyze potential impact agentic workflow Analyzes how a change request might affect relevant servers and services. The agent verifies prerequisites, retrieves the change request, selects up to 10 affected servers, identifies matches with suggested services, and displays an impact analysis in the ServiceNow Otto panel. The analysis is also saved to the change request work notes. An operator or change manager wants to assess the risk of a change request before approving it, without manually reviewing all affected CIs.
    LEAP Ansible discovery agent Analyzes automation opportunities and uses AI-powered semantic matching to identify relevant Ansible job templates from Ansible Automation Platform. Presents discovered templates to the LEAP administrator for step-to-job mapping. A LEAP administrator wants to find the most relevant Ansible job templates for an automation opportunity without manually searching the Ansible catalog.
    LEAP Ansible execution agent Automatically launches mapped Ansible job templates during incident remediation in the Service Operations Workspace. Reports execution status back to the incident responder. An incident responder wants to trigger an Ansible automation directly from the Service Operations Workspace during active incident resolution, without switching to the Ansible platform.

    AI agents

    Standalone AI agents in ITOM Visibility run autonomously on a schedule or in response to a trigger, without requiring user input for each operation.

    Table 2. AI agents in ITOM Visibility
    Product AI feature Description Use case Resources
    Service Mapping Service Mapping AI Agent Autonomously creates service maps from ML-powered Application Service Candidates (ASCs). The agent evaluates candidates, filters noise such as monitoring clients and operating system processes, and creates the service topology in the CMDB. Created service maps are set to non-operational by default for administrator review. Runs automatically every 15 minutes after activation. A Service Mapping administrator wants to process a large volume of ML-powered candidates and create service maps automatically, without reviewing each candidate individually.
    Service Mapping Business App Mapping AI Agent Automatically creates CSDM "Uses::Used by" relationships between Business Applications and discovered Application Services using AI semantic search. High-confidence matches are connected automatically. Medium-confidence matches are saved to a staging table for administrator review. A Service Mapping administrator wants to connect discovered application services to their business application context in the CSDM without manually mapping each relationship.
    Certificate Inventory and Management Certificate renewal AI agent Uses AI to automatically renew a single TLS certificate through a conversational prompt. The agent guides the user through the renewal process and provides a link to the task record when complete. A PKI administrator wants to renew a certificate without manually navigating the renewal workflow. Automatically renew certificates using the AI agent
    LEAP LEAP AI agent Uses automation opportunities created by LEAP analysis to generate artifacts — problem records, AI-enhanced knowledge base articles, or playbooks — based on user requests. The agent is turned on by default. A LEAP administrator wants to convert a recurring incident pattern into a problem record, a structured knowledge base article, or a playbook without manually authoring each artifact.

    Generative AI skills

    Generative AI skills in ITOM Visibility are discrete, on-demand capabilities that administrators invoke to generate analyses, summaries, or insights for a specific discovery error set, service map, or incident pattern.

    Table 3. Generative AI skills in ITOM Visibility
    Product AI feature Description Use case Resources
    Service Mapping Service Mapping Candidate skill Classifies application service candidates and generates names and descriptions for the processes within them. Retrieves publisher, product, and description details for each process, then generates a name and description for the candidate. Active by default. Used by the Analyze potential impact agentic workflow. A Service Mapping administrator wants AI to automatically name and describe application service candidates during a change impact analysis, without manually reviewing each process. Activate the Service Mapping Candidate skill
    Service Mapping Service Mapping Candidates Impact skill Analyzes connections and effects on servers following a change request, and generates an impact summary of affected components. Active by default. Used by the Analyze potential impact agentic workflow. A Service Mapping administrator wants AI to automatically summarize which components are affected by a change request, without manually tracing server dependencies. Activate the Service Mapping Candidates Impact skill
    Discovery AI Insights for discovery errors Analyzes current Discovery errors and surfaces the highest-impact and highest-leverage errors in the Discovery Admin Workspace Diagnostics page. Each insight includes a summary of affected schedules and devices, and recommended remediation steps. Powered by ServiceNow Otto for Error Framework. A discovery administrator wants to quickly identify which errors to resolve first to have the greatest effect on discovery health, without reviewing every error individually. Discovery Admin Workspace Diagnostics
    LEAP AI-generated resolution steps Uses generative AI to analyze grouped incidents and generate structured resolution steps for each automation opportunity. Resolution steps can be reviewed and modified before use. A LEAP administrator wants to produce actionable resolution guidance for a recurring incident pattern without manually authoring steps from scratch. Generate and modify resolution steps in LEAP