Customer Service Management AI agent collection provide customer 360 insights

Provide Customer 360 insights agentic workflow is a GenAI-powered assistant that helps agents answer natural language questions about customers, cases, products, catalogs, and past interactions.

This workflow enables agents to retrieve case details, customer information, and perform actions such as case creation, modification, escalation, and closure using natural language queries. It supports real-time context-aware responses and respects role-based access controls.

Provide customer 360 insights agentic workflow overview

The Provide Customer 360 insights agentic workflow is a GenAI-powered assistant that helps agents resolve cases more efficiently and effectively. By answering natural language questions about customers, cases, products, catalogs and past interactions, it provides contextual insights that enable agents to make informed decisions and solve issues faster. It provides a seamless, multi-turn Q&A experience, helping agents to:

• Ask follow-up questions and get context-aware responses in real-time.
• Access critical customer details and history to make informed decisions.

This feature consolidates scattered user and case data, providing agents with timely, accurate insights. This helps agents make informed decisions, reduce Mean Time To Resolve (MTTR), and solve issues faster. If something isn’t found, the GenAI responds clearly. For example, “I couldn’t find any recent catalog interactions for this customer". If the question is outside its scope, it redirects.

Provide Customer 360 insights agentic workflow

Customer 360 insights agentic workflow is set up as a promoted asset in the ServiceNow Otto panel.

This workflow manages all case-related queries and actions, including retrieval of case details, history, timelines, assignments, status, customer information, sentiment analysis, related cases, knowledge articles, and case updates. It supports natural language requests for specific case numbers and aggregates comprehensive case and customer data. It analyzes historical patterns and sentiment. It executes case management operations such as creation, modification, escalation, and closure.

Role masking

Required role: B2B agents (sn_customerservice_agent) and B2C agents (sn_customerservice.consumer_agent)

Important:

To access data in the agentic workflow, the admin role must include the specified roles under Contains roles.

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.

In the data access settings, you must also add the necessary roles to helps agents resolve cases more efficiently and effectively. For example, you can add the csm role to the agentic workflow's list of approved roles so that it can access case records.

Setup Provide customer 360 insights Agentic Workflow

To configure the Provide customer 360 insights agentic workflow, perform the following steps:

1. Navigate to All > AI Agent Studio > Create and manage.
2. Select Provide Customer 360 insights.
3. In Define key requirements the workflow’s purpose is clearly described and its steps with specific actions and criteria for each is outlined.
4. In Define security controls you can set the access at user and data level.
   1. Define user access: Specify which users can access and interact with the agentic workflow. Once you save your selections, the system automatically generates an Access Control List (ACL).
   2. Define data access: Choose the user identity under which the Provide customer 360 insights agentic workflow will run. This determines the roles and associated data access permissions.
      Note:

      Choose the user identity this agentic workflow should run as to determine the roles and the data access permissions derived from them. Remember, when agentic workflows can access data, they can also share that data with the human user who interacts with them. Agent level role mask are: B2B agents (sn_customerservice_agent) and B2C agents (sn_customerservice.consumer_agent).
5. In Add triggers you can set up optional triggers to launch the agentic workflow automatically without a user request. Triggers can be based on conditions or schedules you define and initiate agentic AI experiences.
6. In Select channels and status, you can choose the channels where this agentic workflow will be available to engage with users who initiate interactions. Toggle the display for Engage via the ServiceNow Otto panel to see the agentic flow in the panel.
   Note:

   To turn off the agentic workflow, toggle off Engage via the ServiceNow Otto panel.
7. Select Save and test.

The agent executes the testing in AI Agent Studio for the agentic workflow.

Figure 1. Example of Provide customer 360 insight agentic workflow testing in AI Agent Studio

In the panel, the agent receives a notification as soon as the interaction is generated, which enables them to follow the on-screen instructions and complete the task. For more information, see Request the generative AI capabilities in Customer Service Management by using the ServiceNow Otto panel.

Access Control lists (ACLs)

Access Control Lists (ACLs) are preconfigured to support the Provide customer 360 insights use case. This includes AI agents and their associated flows and actions, such as the Customer insights Agent. By default, ACLs are configured for the sn_esm_agent role. Customers can modify these ACLs to align with their specific business requirements and security policies. For more information, Configure security controls for a skill.

When updating the agent role for the Provide customer 360 insights Agentic Workflow, it is important to also update the corresponding Access Control Lists (ACLs) to ensure proper permissions. To manually update ACLs for custom roles:

1. Go to the sys_security_acl table.
2. Use filters to locate ACLs related to your use case, AI agent, and internal flows or actions.
3. Add your custom role to each relevant ACL record.

AI agents used in Provide customer 360 insights agentic workflow

The following tables list the agents that are used in the Provide customer 360 insights agentic workflow.

Table 1. AI agents and their roles in the Provide customer 360 insights agentic workflow

AI agent	Actions
Case action AI Agent	Perform customer-related actions, including case operations such as creating case tasks and updating work notes.
Customer insight AI Agent	Answer questions related to the record by retrieving comprehensive information. This includes customer details (name, contact info, location, history, cases, orders) and case data (next steps, actions, assigned agent, notes, documents, tasks, resolutions).

Use Provide customer 360 insights Agentic Workflow

The Provide customer 360 insights agentic workflow in ServiceNow Otto for Customer Service Management (CSM) gives agents contextual, GenAI-driven insights about customers directly within a case. By selecting the AI icon in a case record, agents can access the panel that delivers real-time insights based on customer data.

Agents can ask natural language questions, such as "What products is this customer currently using?" The AI agent responds with accurate, contextually relevant answers. The AI agent maintains conversational context across multiple questions.

Table 2. Key features

Feature	Details
Contextual Insights	AI retrieves and summarizes information from multiple sources, including: Case details (status, priority, age, assignees, notes). Customer info (account details, recent activity). Products and services they own. Catalog items they interacted with. Past interactions (calls, chats, emails). Actions taken (resolution steps, escalations, KBs shared).
Handling	If data is unavailable or ambiguous, AI communicates clearly, for example, I couldn’t find any recent catalog interactions for this customer. For out-of-scope questions GenAI declines and redirects.
Security	GenAI respects role-based access controls and does not surface restricted information.
Feedback Loop	Agents can give thumbs up or thumbs down or flag inaccurate responses for retraining.
Enterprise Graph	Enables the agent to connect the case table with one related table at a time in natural language queries- without requiring SQL or schema knowledge.