ServiceNow Otto for Telecommunications, Media, and Technology (TMT) Monitor engagement health agentic workflow

  • Release version: Zurich
  • Updated July 31, 2025
  • 3 minutes to read
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    Summary of ServiceNow Otto for Telecommunications, Media, and Technology (TMT) Monitor engagement health agentic workflow

    The Monitor engagement health agentic workflow enables customer success managers to track and assess the health scores of up to 10 active customer engagements over the past 6 weeks. It analyzes individual metrics contributing to the health score and detects declining trends to generate risk signals automatically. These risk signals and occurrences help proactively identify potential issues in customer engagements. The workflow runs weekly and displays results within the ServiceNow Otto panel.

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    Key Features

    • Health Score Monitoring: Tracks health scores for each metric or overall engagement health, depending on configuration.
    • Risk Signal Generation: Automatically creates AI-generated risk signals when a decline in health score trends is detected.
    • Scheduled Execution: Runs on a predefined weekly schedule to provide up-to-date engagement health insights.
    • Role-Based Access: Uses role masking to restrict access to users with the snacctlc.customersuccessagent role, ensuring security and appropriate visibility.
    • Configurable Monitoring Scope: Enables monitoring of up to 10 engagements per customer success manager with the AI Health Monitor flag enabled.
    • Customizable Metric Monitoring: Ability to monitor individual metric scores or only the overall health score by adjusting the sncustsuccaiagentenablehealthmonitormetrics system property.
    • Color Banding Configuration: Supports defining color-coded health score ranges per data context, allowing customized visualization of health status per customer or metric.
    • AI Agent Integration: Employs a Success Health Monitor AI agent to retrieve engagement data, analyze trends, and generate risk signals.

    Configuration and Usage

    • Before running the workflow, activate the Analyze metric data trend skill to collect necessary metric data.
    • Activate the Monitor engagement health flow to schedule the agentic workflow as a job.
    • Enable the AI Health Monitor flag on engagements you wish to monitor (max 10 per customer success manager).
    • Adjust system properties to tailor monitoring to either individual metrics or overall health scores.
    • Configure color banding tables with contextual data to reflect health score thresholds accurately across different customers or metrics.
    • Access generated risk signals and occurrences on the Risk signals page within ServiceNow Otto.
    • Ensure user roles are correctly assigned and security controls configured to allow access to the agentic workflow and its outputs.

    Benefits for ServiceNow Customers

    This workflow provides a proactive, AI-driven approach to monitoring customer engagement health, enabling customer success managers to:

    • Identify declining trends early to mitigate risks in customer relationships.
    • Focus on a manageable number of engagements with actionable insights.
    • Customize monitoring and visualization to fit specific customer contexts.
    • Leverage AI-generated signals to prioritize engagement efforts efficiently.
    • Maintain secure and role-based access to sensitive health data and risk signals.

    Monitor engagement health scores and metric trends. The workflow generates risk signals when a decline is detected.

    Important:
    Before you run this agentic workflow, you must activate the Analyze metric data trend skill to collect the metric data that is to be evaluated.

    Monitor engagement health agentic workflow overview

    Customer success managers can monitor the health score of up to 10 active engagements and summarize the health trend for the past 6 weeks. Each metric used to calculate the health score is monitored. If a declining pattern is detected, a risk signal or a risk occurrence is generated. A summary indicating the number of risk signals created and the health score range is generated. The Monitor engagement health agentic workflow is triggered weekly based on a predefined schedule and the results are displayed in the ServiceNow Otto panel.

    You can view the risk signals and occurrences that have been created by navigating to the Risk signals page. For risks created using the agentic workflow, the following field values are displayed:
    • Category: Health declined
    • Creation method: AI generated

    Role masking

    Required role: sn_acct_lc.customer_success_agent

    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.

    Configure the monitor engagement health agentic workflow

    • To run the agentic workflow as a scheduled job, you must activate the Monitor engagement health flow. See Activate a flow for details.
    • The agentic workflow monitors only the engagements for which AI Health Monitor flag has been enabled. Each customer success manager can enable a maximum of 10 engagements. For instructions on enabling this flag, see Create an engagement.
    • By default, the health score of each individual metric is monitored. If you want to monitor only the overall health score across all engagements, you need to update the sn_cust_succ_ai_agent_enable_health_monitor_metrics system property by following these steps:
      • Navigate to All and enter sys_properties.LIST in the search field.
      • Select the sn_cust_succ_ai_agent_enable_health_monitor_metrics property.
      • Set the Value field to false. When this property is disabled, the agentic workflow will monitor the overall health score instead of the individual metrics.
    • For any new or existing health definitions, you must specify the Context for the Data source to indicate how the color banding range will be applied. Based on the Context, you can define different color banding ranges that can be used for the health score. For example, you can configure different values for the same Data source as follows:
      • Data source 1
        • Data source: Daily collection of NPS
        • Context: Health Metric Configuration: Daily collection of NPS (Global)
        • Min: 80
        • Max: 100
        • Color: Green
        • Category: Good
      • Data source 2
        • Data source: Daily collection of NPS
        • Context: Daily collection of NPS for (Customer X)
        • Min: 0
        • Max: 60
        • Color: Red
        • Category: Poor
      For more details on configuring the color banding table, see Setup the color banding table.

    AI agents used in the Monitor engagement health agentic workflow

    The Monitor engagement health agentic workflow uses specific AI agents to monitor the engagements, analyze the health trend, and generate a health score.

    Table 1. AI agents and their role in the Monitor engagement health agentic workflow
    AI agent AI agent role
    Success health monitor AI agent Retrieves data for all active engagements, identifies trends, and creates a risk signal if a declining pattern is detected.