Use ServiceNow Otto for Retail Service Management (RSM)
Summarize
Summary of Use ServiceNow Otto for Retail Service Management (RSM)
ServiceNow Otto for Retail Service Management (RSM) enhances store inquiry processes using an AI-powered store inquiry agent. This agent automates and streamlines how store-related questions are handled, improving efficiency and accuracy in responses. The workflow activates when a store associate or manager submits a store inquiry case, which is then assigned to a headquarters (HQ) agent who uses the AI assistant to manage the case.
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Key Features
- Automated Inquiry Parsing: The AI agent analyzes incoming store questions to identify key topics such as discount policies, returns, and exceptions, categorizing and tagging inquiries for streamlined processing.
- Intelligent Policy Look-up: It searches across multiple sources like past resolved cases, knowledge base (KB) articles, and attached documents to provide precise, context-relevant guidance.
- Response Drafting with Policy References: Automatically generates suggested replies using clear policy language, linking to the accurate source for traceability.
- Learning from Resolved Cases: Continuously improves its response accuracy by indexing newly resolved inquiries to handle similar future cases better.
- Case Information Updates: HQ agents can accept, edit, or reject AI-suggested resolutions. Accepted or edited responses update case resolution notes and set the case to resolved, while rejected responses allow adding work notes for traceability.
- Now Assist Integration: HQ agents interact with the AI through the Now Assist chat panel, selecting options to accept, edit, or reject the AI’s proposed solutions to efficiently manage store inquiries.
- Security Controls: Access to AI agents and workflows is governed by access control lists (ACLs) and user identities, configurable within AI Agent Studio to ensure appropriate permissions and data security.
Practical Use and Benefits
By leveraging ServiceNow Otto’s AI capabilities for RSM, ServiceNow customers can expect faster and more accurate store inquiry handling, reduced manual effort for HQ agents, and improved consistency in policy application. The AI assistant supports HQ agents by automating routine tasks, providing suggested responses with policy backing, and maintaining detailed case records, which enhances operational efficiency and customer satisfaction in retail service management.
Use store inquiry Al agent to improve and enhance the store inquiry processes in Retail Service Management(RSM).
| AI agent capabilities | Description |
|---|---|
| Automated inquiry parsing | Analyzes incoming questions from stores and identifies key topics like discount policy, returns, and exceptions. It accurately categorizes and tags these inquiries, streamlining the processing and response to store queries |
| Intelligent policy look-up | Searches across multiple sources—such as past resolved cases, knowledge base articles, and their attached documents—to deliver precise and contextually relevant guidance |
| Response drafting with policy references | Automatically generates a suggested reply using clear policy language and provides the accurate source of the suggested reply for traceability by attaching or linking it |
| Learning from resolved cases | Continuously improves by indexing newly resolved inquiries, which expands its ability to respond to similar future cases |
| Update case information | Enables the HQ agent to accept, edit, or reject the suggested resolution, and automatically updates the case resolution notes and status for accepted or edited responses, or add work notes for rejected ones |
This workflow begins when a store associate or manager creates a store inquiry case, a new the case gets created. The case gets assigned to an HQ agent. The HQ agent can then leverage the Now Assist agent by selecting the Now
Assist icon 
to launch the Now Assist chat panel. The Now Assist agent automates parsing of store questions, intelligently search the KB articles and past cases, and the documents attached to the KB articles, and draft responses with policy
references. It prompts the HQ agent to select preferred options like Accept, Edit, or Reject solution.
- Accept: The case state is set to Resolved. The proposed solution gets added to resolution notes automatically.
- Edit: The AI agent prompts the HQ agent to provide custom response. Then, the case state is set to Resolved. The custom response gets added to resolution notes automatically.
- Reject: The proposed solution is not added to the resolution notes. The AI agent asks the agent whether they would like to update the work notes with the resolution provided. If the HQ agent accepts, the proposed solution gets added to the work notes automatically.
- There may be AI agents installed with the Now Assist application that are not used in agentic workflows. To learn how to see all agents that are available on your instance, see Find AI agents.
- To find agents that may not be installed on your instance, visit the AI Agent Marketplace on the ServiceNow Store.
You can enable security implementation on AI agents and agentic workflows through access control lists (ACLs) and user identities. These ACLs determine which users have permissions to discover and invoke an agentic workflow or AI agent.
Configure and manage these ACLs for agentic workflows and AI agents in the AI Agent Studio.
See Implement access control in Now Assist AI agents for more information.