--- sourceDocument: Australia IT Service Management sourceDocumentLink: https://www.servicenow.com/docs/r/it-service-management Release : - australia ft:locale : - en-US ft:publication_title : - Australia IT Service Management ft:clusterId : - itsm bundleId : - itsm workflow : - Technology --- # Explain SLA # IT Service Management AI agent collection explain SLA agentic workflow {#ariaid-title1} * Release version: Australia * * Updated March 12, 2026 * * ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of IT Service Management AI Agent Collection Explain SLA Agentic Workflow The explain SLA agentic workflow in ServiceNow enables users to analyze and gain detailed insights into Service Level Agreements (SLAs) associated with tasks such as incidents, problems, cases, or change requests. It identifies the most critical SLA---usually the one nearest to breach---and provides explanations about SLA assignment, duration, pauses, resumes, and task ownership. This manual workflow helps users understand SLA performance both before and after breaches. Show full answer Show less ## Key Features * **SLA Identification:** Automatically selects the SLA likely to breach first, with flexibility to choose another SLA based on timer configurations. * **Insightful Questions:** Offers a set of suggested questions and allows custom queries to explore SLA details such as breach likelihood, elapsed time, pause/resume events, and assignment history. * **Detailed SLA Breakdown:** Provides explanations on SLA target values, vendor details, ownership, reassignment patterns, and causes leading to breaches. * **AI Agent Integration:** Uses the explain SLA AI agent accessible via the ServiceNow Otto panel and AI Agent Studio, enhancing user interaction and response accuracy. * **Manual Invocation and Customization:** The workflow is triggered manually and can be duplicated and modified to fit specific organizational needs, with a requirement to update all related instructions when changes are made. ## Practical Use Cases * **Pre-Breach Monitoring:** Assigned users can proactively track SLA progress, detect gaps in ownership or repeated pauses, and plan task handling to meet SLA timelines. * **Post-Breach Analysis:** Users or groups can investigate breach causes, explore assignment durations, and identify patterns that can inform SLA monitoring and configuration improvements. * **Enhanced Task Management:** By understanding SLA dynamics, teams can optimize assignment strategies, reduce breaches, and improve overall service delivery. ## How to Access and Use * Requires the **snuxcgenai.snaiaslaexplain** role, included in the itil role. * Access via **AI Agent Studio** under "Explain SLA" or through the **ServiceNow Otto panel**. * Use task identifiers like change request numbers or keywords to query the AI agent. * Follow on-screen instructions triggered by AI-generated messages to complete SLA analysis tasks. Use the explain SLA agentic workflow to analyze a Service Level Agreement (SLA) and gain insight into the SLA assignment, task ownership, and pause and resume events in the SLA duration for a task, such as an incident, problem, case, or change request. ## Explain SLA agentic workflow overview {#now-assist-itsm-aiagents-explain-sla-workflow__section_kqd_z4z_kgc} The explain SLA agentic workflow begins with identifying the most important SLA associated with a task. By default, the matched SLA is the SLA that would be breached first. However, a different SLA can also be identified based on your SLA timer configuration. The workflow then suggests a few standard questions about the identified SLA. Based on the questions asked, the workflow explains the SLA breakdown by assignment, SLA duration, and provides insight into the task ownership, reassignment, and causes for the SLA breach. The explain SLA agentic workflow can be used in the following scenarios: * Before an SLA is breached, assigned users can gain an insight into the time elapsed and potential for the SLA breach. The assigned user can track gaps with previous assignments and SLA ownership if the SLA breakdown shows multiple reassignments across teams and repeated pauses in the SLA. Based on requirements, the user can ask the agent questions to plan the handling of the incident or task in adherence to the SLA timelines. * After an SLA is breached, users or groups can investigate the possible causes of the breach, reassignment patterns, and users who were assigned for the longest duration. The agent can also provide information on the factors contributing to the SLA breach. Based on the information, the SLA can be monitored and configured for better handling of tasks, and improved assignment plans can be created. {#now-assist-itsm-aiagents-explain-sla-workflow__ul_ess_hpz_kgc} Note: The explain SLA agentic workflow doesn't have a trigger and is invoked manually. To modify the explain SLA agentic workflow, [duplicate it](https://www.servicenow.com/docs/access?context=clone-aia-usecase&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US), and adjust the settings according to your requirements. Important: When you modify an agentic workflow, AI agent, or tool, make sure that you update all instructions accordingly. ## Explain SLA {#now-assist-itsm-aiagents-explain-sla-workflow__section_i31_tpz_kgc} Autonomously generate an explanation for the SLA breakdown. Note: The workflow can be accessed by the sn_uxc_gen_ai.sn_aia_sla_explain role that is available as a part of the itil role. To access and configure the agentic workflow: 1. Navigate to AllAI Agent StudioCreate and manage. 2. Select Explain SLA. {#now-assist-itsm-aiagents-explain-sla-workflow__ol_itg_xpz_kgc} ## AI agent used in the explain SLA agentic workflow {#now-assist-itsm-aiagents-explain-sla-workflow__section_vph_dqz_kgc} The explain SLA AI agent provides a list of suggested questions that you can ask the agent to get a detailed explanation about the SLA. You can also add custom questions regarding the SLA. The following SLA details can be traced by conversing with the agent: * Reason for choosing the SLA for the given task * SLA target and vendor values * If the SLA is likely to breach * Time elapsed for the SLA * Number of times the SLA has paused or resumed, and their details * User and group assignments for the SLA * SLA assignment and breach patterns {#now-assist-itsm-aiagents-explain-sla-workflow__ul_ntz_r5g_lgc} ## Generating SLA information using the explain SLA agentic workflow {#now-assist-itsm-aiagents-explain-sla-workflow__section_kf2_wvz_kgc} In the agentic workflow record: 1. Review the information in the Describe and connect screen and in the Define trigger screen, make the necessary updates, and then select Save and Continue. 2. In the Select a UI display screen, turn on the Display option to add the icon for the ServiceNow Otto panel in the menu bar. 3. Select Save and test. {#now-assist-itsm-aiagents-explain-sla-workflow__ol_cqv_xvz_kgc}The AI agent executes the request for the agentic workflow. ## Example of the explain SLA agentic workflow output in the ServiceNow® AI Agent Studio {#now-assist-itsm-aiagents-explain-sla-workflow__section_mgp_jwz_kgc} Access and use the explain SLA agentic workflow from the ServiceNow Otto panel. You can add a query using the change request number to use the AI agent. You can enter the number from the suggested questions, add keywords from the questions, or ask custom questions to the agent. For the query instruction, follow the steps specified in the List of steps field of the Define key requirements screen of the agentic workflow record. In the AI Agent Studio, the human agent gets notified as soon as a text message is generated so that they can follow the on-screen instructions and complete the task. For more information, see [Request the generative AI capabilities in ITSM by using the ServiceNow Otto panel](https://www.servicenow.com/docs/AnJIDfOoTCaVTN3DW2Cxdg "Use the ServiceNow Otto panel to request the contextual generative AI capabilities in IT Service Management (ITSM) such as a chat summary, incident summary, or incident resolution notes in a conversational manner. You can also add comments and work notes. These capabilities provide you with a quick resolution to issues."). *[\>]: and then