AI insight AI agent
The agent answers questions about a customer engagement or account. It reports health scores, adoption scores, value realization, risks, contract value, and other engagement data, and it forecasts scores and recommends improvements.
Workflow
The agent helps the user explore engagement or account data through a conversation.
- Greet the user and list the topics the agent can cover, such as health score, adoption scores, value realization, risks, objectives, and contract value.
- Wait for the user to ask a question.
- Collect the data that matches the question topic, or search the customer success knowledge graph for record-level details such as risks, objectives, outcomes, and notes.
- Answer from the retrieved data only. The agent pairs each score with its date or period and does not guess missing values.
- Forecast the next score or recommend improvements when the user asks, based on historical values and peer trends.
- Suggest specific follow-up questions or next actions, and repeat the cycle until the user ends the conversation.
|
Field |
Description |
|---|---|
|
Allow third party to access this AI agent |
When enabled, third-party AI agents can use this agent. This value is off (false) by default. This setting is defined in the AI Agent configs [sn_aia_agent_config] table on the External discoverable field. |
|
Allow AI specialists to access this AI agent |
When enabled, AI specialists can use this agent. This value is off (false) by default. When set to true, more configuration options for tools become available so that an AI specialist can map inputs and response templates to tool outputs. This setting is defined in the AI Agent configs [sn_aia_agent_config] table on the Specialist enabled field. |
|
Manage long-term memory |
When enabled, all previous user interactions are used as context for the LLM. This value is off (false) by default. This setting is defined by the sn_aia.ltm.enable_long_term_memory system property. For more information, see ServiceNow Otto AI agents reference. |
|
Tools |
Collect Insight Context Data
Customer Success KG Tag |
|
Allowed user roles The specific user roles that can access this AI agent. |
Not defined. |
|
Data access roles The specific user identity roles that determine which data the AI agent can access and what actions it can take. |
sn_acct_lc.customer_success_agent |
|
Triggers |
Optional. None defined by default. An admin can specify triggers if desired. For more information, see Add a trigger to an AI agent. |
|
Channels |
Configure an assistant for Virtual Agent or ServiceNow Otto panel using Assistant Designer. |
|
Used in agentic workflows |
Not applicable. |
Parent Topic:Customer Success Management AI agents
--- title: AI insight AI agent description: The agent answers questions about a customer engagement or account. It reports health scores, adoption scores, value realization, risks, contract value, and other engagement data, and it forecasts scores and recommends improvements. locale: en-US canonical_url: https://www.servicenow.com/docs/r/australia/intelligent-experiences/tmt-ai-insight-ai-agent.html release: australia topic_type: reference last_updated: "2026-10-27" reading_time_minutes: 2 breadcrumb: [Customer Success Management AI agents, Telecommunications, Media and Technology AI agents, Telecom, Media and Tech AI agents, AI agents library, AI agents and agentic workflows, Enable AI Experiences] --- # AI insight AI agent The agent answers questions about a customer engagement or account. It reports health scores, adoption scores, value realization, risks, contract value, and other engagement data, and it forecasts scores and recommends improvements. ## Workflow The agent helps the user explore engagement or account data through a conversation. 1. Greet the user and list the topics the agent can cover, such as health score, adoption scores, value realization, risks, objectives, and contract value. 2. Wait for the user to ask a question. 3. Collect the data that matches the question topic, or search the customer success knowledge graph for record-level details such as risks, objectives, outcomes, and notes. 4. Answer from the retrieved data only. The agent pairs each score with its date or period and does not guess missing values. 5. Forecast the next score or recommend improvements when the user asks, based on historical values and peer trends. 6. Suggest specific follow-up questions or next actions, and repeat the cycle until the user ends the conversation. <table><thead><tr><th> Field </th><th> Description </th></tr></thead><tbody><tr><td> Allow third party to access this AI agent </td><td> When enabled, third-party AI agents can use this agent. This value is off \(false\) by default. This setting is defined in the AI Agent configs \[sn\_aia\_agent\_config\] table on the External discoverable field. </td></tr><tr><td> Allow AI specialists to access this AI agent </td><td> When enabled, AI specialists can use this agent. This value is off \(false\) by default. When set to true, more configuration options for tools become available so that an AI specialist can map inputs and response templates to tool outputs. This setting is defined in the AI Agent configs \[sn\_aia\_agent\_config\] table on the Specialist enabled field. </td></tr><tr><td> Manage long-term memory </td><td> When enabled, all previous user interactions are used as context for the LLM. This value is off \(false\) by default. This setting is defined by the **sn\_aia.ltm.enable\_long\_term\_memory** system property. For more information, see [ServiceNow Otto AI agents reference](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/na-aia-reference.md). </td></tr><tr><td> Tools </td><td> - **Script** Collect Insight Context Data - **Tool** Customer Success KG Tag </td></tr><tr><td> Allowed user roles The specific user roles that can access this AI agent. </td><td> Not defined. </td></tr><tr><td> Data access roles The specific user identity roles that determine which data the AI agent can access and what actions it can take. </td><td> sn\_acct\_lc.customer\_success\_agent </td></tr><tr><td> Triggers </td><td> Optional. None defined by default. An admin can specify triggers if desired. For more information, see [Add a trigger to an AI agent](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/add-trigger-aia.md). </td></tr><tr><td> Channels </td><td> Configure an assistant for Virtual Agent or ServiceNow Otto panel using [Assistant Designer](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/conversational-interfaces/configure-now-assist-va.md). </td></tr><tr><td> Used in agentic workflows </td><td> Not applicable. </td></tr></tbody> </table>Learn more about Customer Success Management at [Customer Success Management](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/acct-lifecycle-events/account-lifecycle-events-landing.md). **Parent Topic:**[Customer Success Management AI agents](https://raw.githubusercontent.com/ServiceNow/ServiceNowDocs/australia/markdown/australia/intelligent-experiences/customer-success-ai-agents-overview.md)
| title | AI insight AI agent |
| description | The agent answers questions about a customer engagement or account. It reports health scores, adoption scores, value realization, risks, contract value, and other engagement data, and it forecasts scores and recommends improvements. |
| locale | en-US |
| canonical_url | https://www.servicenow.com/docs/r/australia/intelligent-experiences/tmt-ai-insight-ai-agent.html |
| release | australia |
| topic_type | reference |
| last_updated | 2026-10-27 |
| reading_time_minutes | 2 |
| breadcrumb | Customer Success Management AI agentsTelecommunicationsMedia and Technology AI agentsTelecomMedia and Tech AI agentsAI agents libraryAI agents and agentic workflowsEnable AI Experiences |