Flamingo

Kristina Shkriabina

Kristina Shkriabina

Kristina Shkriabina

Marketing Manager @ Flamingo

Kristina runs content, SEO, and community at Flamingo and OpenMSP. She spent years as a correspondent for Ukraine's Public Broadcasting Company before making the jump to tech. Now she covers MSP stack decisions and strategy. You can connect with her in the OpenMSP community or on LinkedIn.

Content by Kristina Shkriabina

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Frequently Asked Questions

MSPs use AI to triage and route tickets, cut alert noise, schedule patches, assist L1 security work, and draft client reports. Kaseya's 2025 benchmark found 30% already use it to eliminate tedious tasks, with ticket triage the most common starting point.
Most MSPs start with AI features inside their existing PSA, RMM, and ticketing systems rather than standalone products. Common categories include AI ticket triage, alert correlation, scripting assistants, and AI-native all-in-one platforms like OpenFrame that run intelligence across the whole stack.
Start with a readiness assessment, not a tool purchase. Confirm your ticket history is clean and your RMM, PSA, and monitoring systems connect. Then pick one high-volume, low-risk workflow, usually ticket triage, and pilot it on internal tickets before any client sees it.
Automate high-volume, low-risk tasks first. Ticket triage and alert noise reduction top the list because they run constantly and a human still resolves the underlying issue. Save security approvals, billing changes, and client-facing actions for later, always with a human in the loop.
It can be, with governance. Keep a human in the loop on high-risk actions, log every automated step for audit, and choose platforms that keep your data yours with no vendor lock-in. Pilot on internal data first so you catch issues before client systems are involved.
Set a baseline before rollout, then track tickets closed per technician, mean time to resolution, percentage of tickets resolved with no human touch, technician hours reclaimed, and cost per ticket. AI-driven automation commonly cuts operational cost per ticket by 25 to 40%.
An AI agent for an MSP is software that reads a ticket, decides the action, performs it across your tools, and records the result without a technician driving each step. It differs from a chatbot or copilot by taking action, not just suggesting one.
No. AI automates routine tickets, patching, and monitoring, but trust, accountability, and complex business judgment still need people. The future of managed services moves technicians from closing tickets to advising clients, which makes the human role more valuable, not obsolete.
AI-powered infrastructure managed services apply machine learning to infrastructure telemetry so providers can predict failures, automatically remediate known issues, and forecast capacity needs. They replace static-threshold monitoring and manual firefighting with predictive, largely automated operations overseen by technicians.
Yes, for low-risk categories. MSPs report 10% to 25% of tickets closed without a tech opening them, covering password resets, MFA enrollment, and known installs. Anything needing judgment or touching production data still escalates to a human.