ServiceNow Otto for CSM - Agentic Workflows and AI Agents

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SERVICENOW OTTO for CSM — Agentic AI

Explore the agentic workflows and
AI Agents built into ServiceNow Otto for CSM

Agentic AI extends ServiceNow Otto for CSM beyond human assistance by enabling autonomous execution of multi-step actions directly from the context of a case, conversation, and/or customer intent, independent of where the data resides thanks to AI Agent Fabric and Workflow Data Fabric. These flows reduce friction for human agents and allow the platform to act on their behalf using secure guardrails.

Prebuilt agentic workflows like Triage Cases or AI Agents like Troubleshooting Steps Identification leverage the full ServiceNow AI Platform (Flow Designer, Script, Topics, Catalog Items, RAG, Record operations, web search, Generative AI inputs and more) and any existing automation you've built, to intelligently guide or execute behind-the-scenes processes while mixing and matching solutions for your specific customer facing teams. This allows human agents to focus on more complex work to increase customer satisfaction and resolution.

CSM Agentic Workflows & AI Agents Platform Agentic Capabilities Key Best Practices Formal Learning Measured Success FAQ

CSM Agentic Workflows & AI AgentsPrebuilt agentic solutions purpose-built for customer service

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Triage Cases (Agentic Workflow)

2

Troubleshooting Steps Identification (AI Agent)

3

Customer 360 Insights (AI Agent Collection)

4

AI Voice Agents for CSM: Get Case Status and Manage Cases

5

Accelerate Complaint Case Handling (Agentic Workflow)

Platform Agentic CapabilitiesServiceNow AI Platform agentic workflows that can be tailored for CSM

The following agentic workflows are included as part of the ServiceNow AI Platform and can be tailored for CSM:

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Classify tasks

2

Generate My Work Plan

3

Generate resolution plans

4

Process images for tasks

5

Process emails for tasks

6

Analyze task trends

7

Identify ways to improve service

8

Investigate problems

9

Propose survey responses

10

In Product Experience for Agentic Workflows

11

AI Agent Advisor (Academy session)

Key Best PracticesProven guidance for designing, deploying, and governing agentic AI

Reference Resources

Understanding AI Agents in ServiceNow	General guidelines for creating AI agents and agentic workflows
Control agentic assists usage with these AI Agent properties	Build a dashboard to forecast assists and agentic assists usage
How to estimate and forecast agentic assists usage based on your data	AI Academy: Exploring how workflows, custom skills, and AI agents interconnect
When to Use AI Agents: Rationalizing Uses Cases for Workflows, GenAI Skills & AI Agents	Introducing AI Agents and Quick Start Guide
AI Agent tools - Getting the most out of your agentic workflows	Create your own AI Agent! A walkthrough using AI Agent Studio
AI Agents FAQ and Troubleshooting	AI Agent Practical Implementation: Lessons from the Field
How Governance can accelerate the adoption of AI Agent	Finding the Right Jobs for AI Agents
Optimizing AI Agents at Every Step with ServiceNow Process Mining	From Hype to Hands-On: How to Build and Launch AI Agents That Actually Work

7 Proven Practices for Successful Agentic AI Implementation

1

Design with Structure First: Give each step a single owner (agent) and a single tool. Streamline parallel processes into one clear flow and trigger them in predictable ways to reduce complexity. Reasoning prompting excels at this.

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Prioritize the User Experience: Make interactions seamless by pulling data from existing records, requesting inputs in intuitive ways, and keeping each step focused on one clear tool while allowing AI agents to dynamically choose the right tool at runtime.

3

Create Standards You Can Trust: Use consistent naming, formats, and instructions so AI agent behavior is predictable and traceable. Enforce data privacy rigorously, especially when handling sensitive information.

4

Don't Wait for Perfect Data: Launch with out-of-the-box, productivity-focused agents to deliver quick wins and use generative AI to clean and structure key data (Knowledge, resolution notes, CRM Foundation data models, others). Early successes feed better data back into the system, accelerating future improvements.

5

Check Readiness Before You Deploy: Use instance readiness tools to detect customization conflicts before rollout. Preventing issues is faster and easier than fixing them post-deployment.

6

Know When Agentic AI Isn't the Answer: Not every task needs full Agentic AI. Reserve it for problems that require reasoning and planning. Keep single-step or simpler tasks in Now Assist skills or Flow Designer to avoid unnecessary complexity.

Formal LearningBuild the foundation before you configure

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ServiceNow Otto for CSM Essentials Path

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AI Agents - Get Started

3

AI Agents - Initiate

4

AI Agents - Plan

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AI Agents - Execute

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AI Agents - Deliver

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AI Agents Implementation Guides in Now Create

Measured Success & OutcomesHow do we usually measure success in this set of purpose-driven skills?

Outcome	Explanation (with applicable use case)	Success Metric
Faster time-to-triage	Reduce time spent manually classifying or reassigning cases by auto-executing routing flows. Use case: Triage Cases	Avg. time from case creation to routing (seconds)
Reduced agent intervention	Decrease manual effort by letting agentic flows execute background tasks when conditions are met. Use case: Troubleshooting Steps	% of tasks executed autonomously
Higher accuracy in resolution	Deliver more consistent troubleshooting flows by embedding decision logic at point of need. Use case: Troubleshooting Steps	% of cases resolved without additional escalation
Increased workflow reuse	Use modular agentic flows that can be reused across departments or processes with case types. Use case: Triage Cases	Number of flows reused across workflows or LOBs
Reduced mean time to resolve	Accelerate case resolution by acting on contextual triggers rather than waiting for agent input. Use case: Triage Cases + Troubleshooting Steps	MTTR (minutes)

Frequently Asked QuestionsCommon questions on agentic workflows and AI Agents

Q. Why is my agentic workflow not finding the task record (case or interaction)?

Make sure you are prompting correctly when executing the plan if not using triggers or just using the test playground. The prompt can be defined within the agentic workflow setup. By default it is: table=x, record=y where x is the table you are targeting and y is the record you want to do the workflow on.

Q. What initial steps can I take to troubleshoot my agentic workflow or AI agent?

Please follow this Now Support article: KB2507579

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