Your AI Employee Handles the Tickets. You Handle the Rest.
AutomataskAI puts an AI employee to work inside your MSP, taking over the repetitive, low-value tickets your team answers the same way every single day. It runs inside the tools you already use, from day one.
Your technicians are buried in work that does not need a technician.
Password resets, software installs, onboarding checklists, status update requests: these tickets are predictable, they follow the same steps every time, and they eat hours your team could spend on work that actually moves the business forward. Hiring another technician to handle low-complexity volume is expensive and slow. Telling clients to wait longer is not an option either.
67% of MSP tickets are repetitive, low-value requests that automation can handle, and techs spend about 40% of the day on triage
MSP ticket automation analysis (2026)Figures cited are from third-party sources, linked above. They describe the industry, not Automatask results.
What your AI employee takes off your plate
These are the workflows your team handles on repeat today. Your AI employee resolves them automatically, within the tools and ticketing systems you already run.
Password Resets
Verifies the user's identity and resets credentials automatically, without a technician touching the ticket.
Software Install Requests
Receives the request, checks approval policies, and triggers the deployment through your existing RMM.
New User Onboarding
Walks through the onboarding checklist, creates accounts, assigns licences, and confirms completion back to the requester.
Ticket Triage and Routing
Reads incoming tickets, categorises them by type and urgency, and routes each one to the right queue or technician.
Status Update Responses
Pulls the current ticket status and sends a plain-language update to the client without pulling a technician into the thread.
Offboarding Checklists
Triggers account deactivation, licence removal, and asset tracking steps automatically when an offboarding request comes in.
How MSPs start automating without breaking what works
Automation does not have to mean a risky overhaul. Here is how IT support teams approach it practically, starting small and expanding as confidence builds.
Start with your most repeated ticket type
Pull your ticket data and find the category that appears most often with a resolution that barely changes. That category is your first automation candidate. Solving one high-volume, low-complexity workflow first gives you a fast proof of concept with real impact before touching anything more complex.
Keep humans in the loop for judgment calls
Automation handles the predictable. Anything that requires reading context, managing a frustrated client relationship, or making a non-standard decision should stay with your team. A well-designed AI employee knows when to resolve a ticket and when to escalate it to a person, so the handoff is clean and nothing falls through.
Fit it around your existing stack, not the other way around
Your PSA, RMM, and communication tools are already running. The right approach layers automation on top of those systems rather than replacing them. Your AI employee connects to the tools you use today, so technicians keep working in familiar interfaces and clients see no change in how they submit requests.
How you get one
From first call to a working employee.
Free diagnostic
A short call. We map where your hours actually go and find what an AI employee should take over first.
Built around your process
We build your employee around your tools and the way you already work, not a template, your employee.
It works, we improve
It starts taking over the agreed tasks. You supervise, we make it better every month.
Frequently asked questions
No. It takes over the repetitive, rules-based tickets so your technicians spend their time on work that requires expertise and judgment. Your team stays in control of anything complex, sensitive, or relationship-critical.
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