Now Assist for Telecommunications, Media and Technology (TMT) AI agent collection monitor engagement health agentic workflow

Release version: Australia

Updated March 12, 2026

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Summary of Now Assist for Telecommunications, Media and Technology (TMT) AI Agent Collection Monitor Engagement Health Agentic Workflow

The Monitor engagement health agentic workflow enables customer success managers to track the health scores of up to 10 active engagements over a 6-week period. It analyzes individual metric trends and overall engagement health to detect declines, generating risk signals or occurrences when issues arise. This automated workflow runs weekly on a predefined schedule, with results accessible via the Now Assist panel and risk signals viewable on the Risk signals page.

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Activation of the Monitor engagement health flow is required to run this workflow as a scheduled job. The workflow only monitors engagements with the AI Health Monitor flag enabled, which can be set for up to 10 engagements per customer success manager.

Key Features

Health Score Monitoring: Tracks metric-level and overall engagement health scores, with customizable monitoring based on system property settings.
Risk Signal Generation: Automatically creates risk signals or updates existing ones when declining health trends are detected.
Configurable Color Banding: Allows different health score ranges and categories to be defined per data source context, aiding in visual interpretation of health status.
AI Agent Integration: Utilizes AI agents—Success trend analyst and Success health monitor—for data collection, trend analysis, anomaly detection, and risk signal creation.

Practical Application for ServiceNow Customers

ServiceNow customers using Now Assist can leverage this agentic workflow to proactively monitor engagement health, enabling early detection of risks and informed decision-making. The workflow supports customization to focus on either individual metric trends or overall health scores, and it provides clear, actionable insights via AI-driven analysis.

By enabling this workflow and configuring the AI Health Monitor flags on relevant engagements, customer success managers can efficiently oversee up to 10 engagements, receive timely alerts on health declines, and take corrective actions to improve customer satisfaction and retention.

Use the Monitor engagement health agentic workflow to monitor the health score of engagements and their associated metric data trends, and generate risk signals when a decline is detected.

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, and if a declining pattern is detected, a risk signal or a risk occurrence (for an existing risk signal) 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 Now Assist 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

Note:

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, 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 inactive, 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 Set up 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 trend analyst AI agent	Collects and analyzes metric data, processes large data sets, identifies patterns and anomalies. Provides clear actionable insights enabling AI agents to make informed decisions and take appropriate actions.
Success health monitor AI agent	Retrieves data for all active engagements, identifies trends, and creates a risk signal if a declining pattern is detected.