--- sourceDocument: Australia IT Operations Management sourceDocumentLink: https://www.servicenow.com/docs/r/australia/it-operations-management Release : - australia ft:locale : - en-US ft:publication_title : - Australia IT Operations Management ft:clusterId : - itom bundleId : - itom workflow : - Technology --- # AI Agents for Service Mapping # AI Agents for Service Mapping {#ariaid-title1} Release version: Australia Updated September 18, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 7 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 AI Agents for Service Mapping AI Agents for Service Mapping in ServiceNow automate the creation and maintenance of service maps within the Configuration Management Database (CMDB), significantly reducing manual effort for Service Mapping administrators. These agents run autonomously on a recurring schedule and process relevant records without requiring manual input, enabling large-scale, efficient service map management. Show full answer Show less ## Available AI Agents and Their Roles * **Service Mapping AI Agent:** Creates machine learning (ML)-based service maps from Application Service Candidates (ASCs), filtering out noise (e.g., monitoring or OS processes) and identifying applications from running processes. It builds the service topology in the CMDB, marking new maps as non-operational for administrator review. * **Business App Mapping AI Agent:** Connects discovered application services to their corresponding business applications in the Common Service Data Model (CSDM), working top-down to maintain accurate relationships between business applications and underlying services. This agent is available via the Feature Preview Program and is activated independently. * **Tag-Based Service Map Creation AI Agent:** Automatically creates service maps from cloud infrastructure metadata tags applied to virtual machines, validating that tags represent coherent business services and avoiding incorrect groupings. Service maps are also set to non-operational by default for review. ## Why These AI Agents Matter Without these agents, administrators must manually evaluate large numbers of ML-powered or tag-based service candidates and manually map discovered services to business applications, which is time-consuming and impractical at scale. The AI Agents enable automated, scalable processing that ensures service maps are accurate, coherent, and aligned with business context, improving monitoring and impact analysis. ## How AI Agents Work * Agents utilize a ReAct (Reasoning and Acting) strategy, reasoning through each step before invoking tools. * The orchestrator runs every 15 minutes, processing new candidates automatically without manual input. * Candidates processed within the last 90 days are skipped to avoid duplication. * Errors such as platform limits pause processing until the next run; other failures do not trigger automatic retries. * **Service Mapping AI Agent:** Retrieves and analyzes ASC data, filters noise, identifies services from running processes, then creates non-operational service topologies unless duplicates exist. * **Tag-Based AI Agent:** Validates candidate tags, ensures coherence of virtual machines under the tag, assesses signal strength combining tags and process evidence, derives service names, and creates service maps if appropriate. ## Activation and Monitoring * All AI Agents are inactive by default and require activation by a user with the Service Mapping admin role. * The Service Mapping AI Agent and Tag-Based Service Map Creation AI Agent are activated together via a single workspace button; the Business App Mapping AI Agent is activated separately. * No configuration in AI Agent Studio is needed for Service Mapping administrators; platform administrators manage agent definitions and tokens. * Administrators can monitor AI Agent activity and review results within the Service Mapping application's AI Activity section. * All created service maps are initially non-operational and require manual activation by the administrator. ## Processing Quota and Scaling * By default, each AI Agent can process up to 100 records before pausing. * To increase processing capacity, administrators must adjust specific system properties to raise the quota and then reactivate the agents. * Increasing the quota results in higher AI resource consumption and should be managed accordingly. The Service Mapping AI agents automate the creation and maintenance of service maps in the Configuration Management Database (CMDB), reducing manual effort for Service Mapping administrators. AI Agents for Service Mapping automate key parts of the Service Mapping workflow. After activation, all agents run autonomously in the background on a recurring schedule, processing all relevant records without requiring administrator input for each one. ## Available AI Agents The ITOM AI Agents for Service Mapping application \[sn_sm_gen_ai\] provides the following AI Agents: Service Mapping AI Agent : Automatically creates ML-based service maps from Application Service Candidates (ASCs) and persists the full service topology in the CMDB. The Agent roles: * Evaluates ML-powered candidates and identifies the application from their running processes. * Filters out noise (such as monitoring clients, security clients, and operating system processes), * Creates the service topology. {#service-mapping-ai-agents__ul_u5r_srw_ckc} Created service maps are set to non-operational by default so that the Service Mapping administrator can review them before making them operational. Business App Mapping AI Agent : Tag-Based Service Map Creation AI Agent : Automatically creates service maps from tag-based candidates generated by cloud infrastructure metadata. This Agent analyzes cloud tags (such as Application and Environment) applied to virtual machines and determines whether they represent real, coherent business services. The Agent performs two critical evaluations: * It signals whether the tag represents a meaningful business service using both the tag name and running process evidence. * It verifies that all virtual machines (VMs) grouped under the tag actually belong to the same application service rather than multiple unrelated systems that share a tag. Created service maps are set to non-operational by default. ## Why these AI Agents are needed Without these AI Agents, Service Mapping administrators have to manually review each ML-powered candidate or tag-based candidate and decide whether to create a service map. Similarly, connecting discovered application services to their business application context in the CSDM required manual one-to-one or one-to-many mapping. Using the AI Agents makes these processes significantly less time-consuming and enables processing at a much larger scale. The following examples illustrate the challenges these AI Agents solve. Consider a bank that has a payment application defined as a business application. Under it, Service Mapping discovers many application services: * Online payment processing. * Cash payment handling. * Net banking. * Mobile payment systems. {#service-mapping-ai-agents__ul_bs4_gsw_ckc}Business stakeholders are only concerned with the payment application at the top level. They need it connected to all the relevant discovered services so they can monitor health and impact. Manually maintaining these connections as new application services are created is impractical. The Business App Mapping AI Agent solves this by iterating over all business applications and automatically finding and connecting the matching discovered services. It works top-down, from the smaller set of business applications to the larger set of discovered application services. In a typical scenario, an organization runs hundreds of servers and generates a large number of ML-powered candidates daily. A Service Mapping administrator who previously had to manually evaluate each candidate and create a service map can instead activate the Service Mapping AI Agent. The agent processes the candidates automatically, creates service maps for those that contain a business application, and sets the maps to non-operational for administrator review. Organizations using cloud infrastructure often apply metadata tags to virtual machines for organization and governance. However, manual service creation from these tags is time-consuming and error-prone, especially at scale. The Tag-Based Service Map Creation AI Agent solves this by: * Automatically analyzing tagged infrastructure, detecting when multiple unrelated systems are incorrectly grouped under a single tag. * Creating service maps only when the tag represents a real, coherent business application. {#service-mapping-ai-agents__ul_qmj_rsw_ckc} ## How AI Agents work All agents use a ReAct (Reasoning and Acting) strategy. The agent reasons about each step before deciding which tool to invoke. After activation, the SM Gen AI - Agent Invocation Orchestrator scheduled job runs every 15 minutes. No per-record input from an administrator is required. The agents skip a candidate that they processed in the last 90 days. If the platform returns a temporary error, the job ends the run. An example is reaching the limit of concurrent AI agent plans. The job processes the candidate at the next run. If an invocation fails for any other reason, the job doesn't retry the candidate automatically. Service Mapping AI Agent process: 1. The agent retrieves full ML candidate data from the Application Service Candidate (ASC) record, including the candidate name, process name, and server count. 2. The agent performs a noise check. If the candidate is flagged as noise, such as monitoring clients, security clients, or operating system processes, the agent skips it. 3. The agent retrieves all running processes associated with the candidate. 4. The agent analyzes the running processes and reasons about what the actual service is, using signals such as executable paths and application IDs. 5. The agent creates the service topology in the CMDB and sets the service to non-operational. If a topology for the same candidate already exists, the agent skips creation. Tag-Based Service Map Creation AI Agent process: 1. The agent retrieves a tag-based candidate record from \[svc_by_tags_candidates\], including the cloud tags (such as Application and Environment) and the set of member virtual machines. 2. The Agent validates the candidate through prerequisite checks. It confirms the candidate is not hidden, ensures at least 2 configuration items (CI) exist to form a topology, and verifies no existing service already maps it. 3. The agent performs a coherence evaluation by analyzing the running processes and process groups (AFP groups) across all member VMs. It determines whether all VMs running under this tag belong to the same application service or whether multiple unrelated systems are incorrectly grouped. 4. If the candidate is incoherent (containing multiple distinct business systems), the agent records the outcome and skips service creation, flagging the candidate for administrator review. 5. If the candidate is coherent or uncertain, the agent evaluates the signal strength. The agent does so by combining the cloud tag name (for example, "order-management") with running process evidence to determine whether a real business service exists. 6. If the signal is strong enough, the agent derives a service name using this priority order: 1. Service Fingerprint (SFP) name if the candidate's CIs match an Application Service Fingerprint in the Discovery Content Library. 2. Strong cloud tag value if no service fingerprint exists. 3. AFP process-derived name if the tag signal is weak and no fingerprints exist. {#service-mapping-ai-agents__ol_hfn_1fr_tjc}The agent then creates the service topology and sets the service to non-operational. If a topology for the same candidate already exists, the agent skips creation. ## Activation and monitoring All agents are inactive by default. A user who has the Service Mapping admin role activates them from the Service Mapping home page. For steps to activate the AI Agents, see [Activate AI Agents for Service Mapping](https://www.servicenow.com/docs/1YUQiiA0Gl3MQWi~PRiJuQ "Activate the Service Mapping AI Agent and the Business App Mapping AI Agent from the Service Mapping home page to start automated service map creation."). The Service Mapping AI Agent and Tag-Based Service Map Creation AI Agent are activated together through a single workspace activation button. The Business App Mapping AI Agent is activated independently. The Business App Mapping AI Agent is available through the Feature Preview Program. For more information, see [Feature Preview Program](https://www.servicenow.com/docs/access?context=feature-preview-program&version=australia&pubname=australia-platform-administration&ft:locale=en-US). Note: The Service Mapping AI Agent and Tag-Based Service Map Creation AI Agent operate independently despite sharing the same orchestrator and writing the results to a shared run record table \[sn_sm_gen_ai_svc_create_run\]. They process different input sources and have no data dependencies. No configuration in AI Agent Studio is required for Service Mapping administrators. AI Agent Studio is used by platform administrators or users who have the AI admin role to manage agent definitions and token usage. After activation, administrators can monitor activity and review results in the AI Activity section of the Service Mapping list navigation. For more information, see [Service Mapping AI Agent activity list tables](https://www.servicenow.com/docs/54pw5y43WxTPREJzZ1RCDA "Use this reference to interpret the tables in the Service Mapping AI Agent activity list."). Service maps created by any AI Agent are non-operational by default and can be made operational from the application service record in the Mapped Application Services list. ## AI Agent processing quota Each AI Agent can process up to 100 records by default. When an AI Agent reaches this limit, it stops processing and its status is set to Paused. The agent stays stopped until you raise the quota. To raise the quota and reactivate the agents, first configure the following properties: 1. For the Service Mapping AI Agent: sn_sm_gen_ai.agent_invocation_limit.ServiceMapCreationAISpecialist 2. For the Tag-Based Service Map Creation AI Agent: sn_sm_gen_ai.agent_invocation_limit.TagBasedServiceMapCreationAISpecialist You can change the value based on your available AI resources. After raising the quota, reactivate the Service Mapping AI Agents in the Service Mapping workspace. Note: Raising the quota results in a higher AI resource consumption.