Every organization recognizes the situation. An employee starts their day ready to work, only to be stopped by a locked account, missing access, or a minor configuration issue. These situations are common, and in most cases, resolving them is routine.
Still, the usual process is the same: the employee contacts IT support, a ticket is created, routed, reviewed, and processed. While this happens, work is on hold. Not because the issue is complex, but because resolution depends on availability and manual steps.
For IT teams, this creates a constant stream of similar requests. A significant share of service desk contacts comes from issues that follow predictable patterns. Handling them one by one takes time, increases backlog, and leaves less capacity for work that actually requires human expertise.
AI Agents for self-resolution offer a different approach.
Matrix42 AI Agents for Self-Resolution are built to address these situations early, before a ticket is created.
Instead of filling out a form or waiting for support, users can ask for help directly through the tools they already use every day, such as Microsoft Teams or the Matrix42 Self-Service Portal.
From there, the AI Agent supports self-resolution by carrying out approved actions immediately. If a request can be handled safely and automatically, it is resolved on the spot. If not, it can still guide the user or prepare the next step for IT support.
The goal is simple: reduce unnecessary tickets and resolve routine issues as early as possible.
The AI Agent for Self-resolution is not a separate channel or a generic chatbot. It is fully integrated into existing service management workflows, connectors, and permissions, and operates within the same governance framework IT teams already use.
In practice, this allows end users to resolve common issues. The AI Agent can execute end-to-end actions, including:
All actions follow existing rules, approvals, and integrations. Nothing is bypassed or redefined.
The AI Agents for Self-Resolution also operate with context awareness. It takes into account the user information, for example:
This context reduces unnecessary back-and-forth and helps avoid incorrect actions. When additional information is required, the agent asks for it. When a task cannot be completed within defined permissions, it does not proceed.
Nothing happens outside established workflows. Control remains with IT at all times.
When routine issues are resolved immediately, the impact is felt across the organization.
Employees experience fewer interruptions and spend less time waiting for support. IT teams see a noticeable reduction in ticket volume and can focus on complex issues, service improvements, and strategic initiatives instead of repetitive tasks.
Over time, this leads to faster resolution times, more consistent service quality, and a more efficient IT operation.
AI Agents for self-resolution are not about changing how IT works; they are about improving it. By removing friction from everyday support, organizations create a smoother experience for employees and a more sustainable workload for IT teams.
This is how Matrix42 supports the shift from manual handling toward more proactive and autonomous service management.
If you want to know more about the AI Agents for Self-resolution, watch our on-demand webinar.
Matrix42 – AI Your Way