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AI Task Health Monitor Built with ServiceNow Build Agent

vaishalisin
Tera Contributor

 

I created a lightweight AI-powered application called AI Task Health Monitor using ServiceNow Build Agent. My goal was to build a clean, simple, and fully Fluent-based ServiceNow app that analyzes task quality, identifies missing information, predicts delays, and recommends next actions — all without using UI Builder, Flow Designer, or catalog items.

 

 What the Application Does

The app is built on a custom table named ai_task_health, which includes fields like:

  • task_number
  • short_description
  • assignment_group
  • state
  • ai_risk_level
  • ai_missing_info
  • ai_next_action
  • ai_delay_prediction
  • ai_summary

These fields store both the original task information and the AI-generated insights.

At the core of the application is a Script Include named AITaskAnalyzer, which reads each task and returns a fully structured JSON analysis including:

  • risk_level
  • missing_info
  • next_action
  • delay_prediction
  • summary

The logic evaluates task completeness, state, clarity, and assignment to determine potential risk and delay.

 

 One-Click AI Analysis

I added a UI Action called Analyze with AI on the form.

When users click the button:

  1. It calls AITaskAnalyzer.analyze(current)
  2. Updates all AI assessment fields
  3. Shows instant feedback on the form

This makes the experience simple and intuitive — no need for extra UI pages or flows.

 

 Application Menu & Navigation

The app includes an Application Menu called AI Task Health Monitor, with two modules:

  • All Tasks → complete list of records
  • High Risk Tasks → filtered where ai_risk_level = High

This helps teams immediately focus on the riskiest work.

 

 Security & Roles

I created two roles for proper access control:

  • ai_task_user → read and create
  • ai_task_admin → full access (includes ai_task_user)

ACLs ensure only authorized users can update AI results.

 

 Impact

In internal testing, the AI Task Health Monitor helped teams spot missing information faster and identify high-risk tasks earlier.
(You may replace this with your own metric)
 Example metric: Reduced manual triage time by 40% in sample tests.

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