Note: The capabilities shown in this video are conceptual demonstrations and not part of the current Ansible Automation Platform product. This video was created to showcase potential future innovations and was originally presented at AnsibleFest 2025.
In this demo, we explore how Ansible Automation Platform could incorporate AI workflows using a new emerging standard called MCP (Model Context Protocol) — an open standard that allows large language models to communicate directly with end systems.
While this is not a product roadmap or a guaranteed feature, the goal is to spark ideas about how AI could assist with:
Creating and executing job templates
Troubleshooting issues in real time
Automatically responding to infrastructure problems
Safely enforcing policy with Ansible Policy Enforcement and OPA
We also want to make something else very clear: This is not RPA (robotic process automation). The UI elements shown in the video are conceptual and are changing dynamically as part of the MCP-powered interaction to help the user understand what the AI assistant is doing behind the scenes.
This video is all about envisioning what’s possible when combining intelligent assistance, automation, and policy controls—creating a safer, faster, and more powerful way to manage IT infrastructure.
In practice, the Ansible Automation Platform remains a classic orchestration system: playbooks, job templates, inventories, roles, etc. Everything related to AI and MCP (Model Context Protocol) is still a research area, aimed at how LLMs can interact with external systems through a standardized interface.
Key points here:
— MCP is indeed interesting as the idea of ​​a unified “bridge” between models and infrastructure, but it is not yet an industry standard in production.
— AI integration into Ansible is currently mostly limited to helper scenarios (YAML generation, log analysis, troubleshooting assistance), rather than direct infrastructure management.
— Any “dynamic UI” and autonomous task execution are still demos, not guaranteed platform functionality.
It’s important to note that such demos often indicate development directions rather than the actual capabilities of upcoming releases. This is especially true in enterprise infrastructure, where requirements for predictability, auditability, and security severely limit the level of AI “autonomy.”
The idea of ​​combining LLM + automation + policy enforcement is indeed promising, but in real-world products, this will almost always be an evolutionary implementation rather than a radical shift to an “AI infrastructure operator.”
Note: The capabilities shown in this video are conceptual demonstrations and not part of the current Ansible Automation Platform product. This video was created to showcase potential future innovations and was originally presented at AnsibleFest 2025.
This is not RPA (robotic process automation).