Move from incident intelligence to trusted automated remediation
For production operations, the joint solution addresses continuity of evidence and action. Incident signals, AI-enriched analysis, and remediation outcomes remain aligned on one governed thread across the incident lifecycle, inside ServiceNow, instead of fragmenting across consoles, chat threads, and unofficial fixes.
Resolve faster with intelligence-led workflow automation
When ticket volumes and architectural complexity accelerate, the operational risk is inconsistent handoffs between what ServiceNow knows and what actually runs in production. Organizations see value on multiple fronts:
- Reduce MTTR from hours to minutes. Eliminate redundant troubleshooting and repeated escalations. Because LEAP has already mined the resolution steps and matched them to a proven Ansible Automation Platform job template, operators can skip much of the time teams often spend hunting logs and context and move straight to a governed remediation instead of another handoff.
- Maximize existing automation investments. ServiceNow LEAP surfaces the automation organizations have already built. When it generates resolution steps for an automation opportunity, its discovery agent finds the Ansible Automation Platform job templates that match, mapping proven, existing automation to the steps that resolve an incident. Service and operations teams stop reinventing fixes that already exist.
- Deliver consistent outcomes. The Ansible Automation Platform playbooks executed are the same pretested, RBAC, and change management aligned work that is already used. The result is the same every time, whether a tier 1 operator, a ServiceNow workflow, or an AI specialist started the process.
- Break down isolated team structures. The integration removes the visibility, skills, and trust barriers between service management and automation. Operators work where they already live. ServiceNow teams see the right Ansible Automation Platform playbooks without having to learn the other platform. The automation organization sees its library actually used in production incidents instead of only in isolated projects.
- Enforce governance at every step. None of the previous points work without control. Every action runs through Ansible Automation Platform RBAC, credentials, and optional approval paths, with full traceability. Results are written back to the ServiceNow record so the organization retains an audit trail there as well.
Use case: AI-powered ticket enrichment
Most enterprises have more existing Ansible Automation Platform playbooks than frontline operators realize. Job templates are spread across business units, undocumented for the service desk, and often invisible at the moment of need so the same class of incident gets solved again manually while a playbook sits unused.
It starts before the next incident. LEAP clusters similar closed incidents into automation opportunities and, with its AI agents, autonomously generates the resolution steps, knowledge base articles, and problem records for each one. Its discovery agent then reaches into an existing Ansible Automation Platform library through the Ansible MCP server and maps the job templates that match those resolution steps. When a new, similar incident arrives in the Service Operations Workspace, LEAP predicts the automation opportunity it belongs to and surfaces the mapped Ansible playbooks alongside the resolution steps, so the operator can choose to run the suggested automation to resolve the incident. Ansible Automation Platform runs that work with RBAC, isolated credentials, and a full audit trail. Steps without a matching automation stay manual, and the operator handles them in the same flow. When the playbook completes, the ServiceNow record is updated so the incident shows what was recommended, what ran, and what changed.
Organizations gain faster MTTR, higher usage of the Ansible automation they have already built, and a LEAP value dashboard that shows which automations are working and where to expand next. Because LEAP is quick to set up and delivers value from the start, teams can capture these gains early while they continue to mature their AIOps practice, with each resolved incident moving them a step closer to zero service outages.
