Exploring LEAP

  • Release version: Australia
  • Updated March 12, 2026
  • 4 minutes to read
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    Summary of Exploring LEAP

    LEAP (Learning Enhanced Automation Platform) is an AI-powered tool designed to help ServiceNow customers efficiently manage incidents and operational tasks. It uses machine learning to group similar incidents into Automation Opportunities (AOs) via the Group Action Framework (GAF) and generates AI-driven resolution steps, problem records, knowledge base articles, and playbooks. LEAP automates routine tasks to accelerate incident resolution, reduce manual effort, and improve overall IT operations.

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    Key Features

    • Incident Clustering: LEAP uses GAF, a machine learning clustering engine, to group incidents based on similar problem patterns using the incident short description field. This grouping enables targeted automation rather than treating each incident individually.
    • Automation Opportunities (AOs): Recurring incident types are surfaced as discrete AOs, which LEAP analyzes and uses to generate AI-based artifacts that support faster resolution.
    • Scheduled Analysis: GAF runs on a configurable schedule (default monthly) and processes up to six months of historical incident data to identify relevant incident clusters.
    • Customizable Settings: Administrators can configure which fields, tables, and columns GAF analyzes and adjust the clustering schedule to suit organizational needs.
    • Role-Based Access: LEAP defines user roles—Admin, Viewer, and Agent—with distinct capabilities to manage, view, or execute automation workflows, ensuring secure and streamlined operations.
    • AI Agent: The LEAP AI agent automatically creates problem records, knowledge base articles, or playbooks from identified automation opportunities, and is enabled by default.

    Personas and User Responsibilities

    • Automation Architect: Senior technical expert responsible for designing, developing, and scaling automation solutions, extracting patterns from incident data, and aligning automation with enterprise goals.
    • IT Operator: Incident handlers (L1/L2) who leverage AI-generated playbooks and knowledge base articles to resolve incidents more efficiently.
    • Buyer/Business Goal Owner: Strategic users who use LEAP to optimize IT operations, resource allocation, and automate recurring issue resolution.

    Benefits

    • Promotes Automation Culture: Encourages data-driven automation of incident resolution.
    • Speeds Incident Resolution: Uses AI to generate actionable resolutions and playbooks, improving mean time to resolution (MTTR).
    • Optimizes Resource Allocation: Identifies and prioritizes high-impact automation opportunities.
    • Cost Predictability: Offers a fixed pricing model for incident analysis operations.

    Practical Application for ServiceNow Customers

    LEAP enables ServiceNow customers to proactively identify recurring incidents and automate their resolution, reducing manual workload and improving service quality. By assigning appropriate roles, customers can ensure that automation architects develop scalable solutions, IT operators efficiently handle incidents using AI-driven guidance, and business leaders optimize IT resources. Configuration flexibility allows tailoring LEAP to specific organizational needs, while the AI agent streamlines artifact creation to support continuous improvement.

    LEAP categorizes similar incidents into groups and uses AI to generate resolution steps, problem records, AI-enhanced knowledge base articles, and playbooks.

    LEAP overview

    LEAP helps you manage incidents and operational tasks efficiently. It uses AI to gather information from existing incidents and generates resolutions that can be automated. The LEAP automation provides tools to manage incidents early, speed up resolution, use prebuilt automation, and follow clear steps to handle issues. These tools help support smooth operations.
    Note:
    The plugin name has been updated from AIOps Learning Enhanced Automation Playbook to Learning Enhanced Automation Platform (LEAP) to reflect its expanded capabilities and strategic direction.

    LEAP landing page

    The landing page displays the number of records analyzed on the right-hand side of Automation opportunities section. The tool tip provides details about the duration considered for record analysis.

    Grouping of automation opportunities in LEAP

    GAF (Group Action Framework) is the clustering engine that LEAP uses to group incidents into Automation Opportunities (AOs). GAF analyzes incident records using the short description field and applies ML-powered clustering to group incidents that share similar problem patterns. LEAP surfaces recurring issue types as discrete automation opportunities (AOs) rather than treating every incident in isolation.

    GAF runs on a scheduled job, by default monthly. The schedule is configured during LEAP skill activation through the installer. On the first run, GAF processes up to six months of historical incident data using the filter set in the installer.

    Before clustering begins, GAF selects the top N incidents from the eligible incident pool, where N is configurable and can be set to a maximum of 50. This selection confirms that clustering focuses on the most relevant and recent incidents within the defined scope. You can configure the fields GAF considers during analysis such as tables and columns in the LEAP settings. You can also modify the schedule run frequency in the LEAP settings.

    LEAP users

    Table 1. User roles
    Role Description
    LEAP admin
    You have full control over LEAP capabilities, including the following:
    • Turn features on and off
    • Execute scheduled jobs
    • Manage LEAP tables and the LEAP Workspace
    • Generate and update resolution steps
    • Generate AI-enhanced knowledge base articles, problem records, and playbooks from automation opportunities (AO)

    LEAP viewer

    		 You can access and view data related to LEAP, including tables, the workspace, and problems originating from AOs.

    LEAP agent

    		 You can access the LEAP menu from the Service Operations Workspace (SOW) and trigger LEAP executions directly from within SOW.

    These roles work together to create a streamlined and secure approach for managing automation, resolving incidents, and sharing knowledge across teams.

    Personas in LEAP

    LEAP supports different personas who can have different roles assigned to enhance IT Operations Management.

    Table 2. LEAP personas
    Persona Description Responsibility
    Automation architect An automation architect is a senior technical expert who designs and develops automation solutions, scaling them when required. They're a bridge between IT operations, business needs, and automation strategy. The automation architect streamlines manual, repetitive, and error-prone tasks.
    • Identifies high-impact areas for automation
    • Develops automation scripts, integrate AI-driven insights, and maintain scalable automation frameworks
    • Extracts patterns from historical ticket data to optimize future resolutions
    • Refines automation solutions based on feedback and evolving business needs.
    • Collaborates with different business units to align automation with enterprise objectives.
    IT operator An IT operator includes all L1 and L2 incident handlers who support day-to-day IT operations.
    • Uses AI-generated playbooks to resolve incidents
    • Accesses the Knowledge Base
    Buyer, Business goal owner A buyer or a business goal owner gains strategic and operational advantages using LEAP.
    • Uses LEAP to improve IT operations
    • Optimizes resource allocation
    • Automates recurring issue resolution

    An automation architect can use LEAP to gather feedback and refine solutions. In a similar manner, IT operators will use LEAP to detect recurring issues and LEAP displays suggestions for preventive automation. This enables faster resolution and operators can resolve more incidents independently leading to improved efficiency and service quality.

    LEAP benefits

    Table 3. LEAP benefits
    Benefit Feature
    Promotes automation culture Interpret data and automate records
    Drives incident resolution Measure and enhance performance
    Targets Outcomes for L1 Operators Interpret data and automate records
    Improves MTTR Measure and enhance performance
    Optimize Resource Allocation Identify and prioritize high impact areas
    Provides cost predictability Fixed pricing model for incident analysis operations

    LEAP AI agent

    The LEAP AI agent uses automation opportunities created by LEAP analysis to generate artifacts — problem records, knowledge base articles, or playbooks — based on user requests.

    Table 4. LEAP AI agent
    AI agent AI agent role
    LEAP AI agent Uses the automation opportunities created by LEAP analysis, and creates artifacts — problem records, AI-enhanced knowledge base articles, or playbooks — based on user requests.
    Important:
    This agent is turned on by default. For more information, see Now Assist skills, agents, and agentic workflows on by default.

    What to explore next

    To learn more about configuring and using LEAP, see: