COMMENTARY: Agentic AI is a game-changer for MSPs, shifting AI from a tool you use to a teammate that takes action. Unlike generative models or rule-based automation, agentic AI is built to perform a role. It’s not about executing commands. It’s autonomous, goal-oriented, and capable of making decisions in real time, based on its environment and learned context. Instead of relying on pre-programmed scripts or chatbots, agentic AI acts on its own, evaluates situations, and adjusts course when needed. It removes the need for manual oversight, which is very powerful for MSPs facing mounting operational demands. As these systems take on more responsibility, MSPs need to be ready to identify, evaluate, and implement agentic AI in ways that align with service goals and client expectations. Service desk coordination: Balancing technician workloads and handing off tasks without someone in the middle. Operational workflows: Taking on repeat tasks and getting smarter with each cycle. Back-end analysis: Spotting issues early by watching for patterns and jumping in before something breaks. MSPs can start small by testing agentic AI on narrow, well-defined functions and then scale as confidence and internal alignment grow. Autonomous execution: Can the system act without human prompts? Reasoning transparency: Can it explain why it made a decision? Learning capacity: Does it improve based on past performance? System collaboration: Can it communicate with other applications or agents? If you’re paying for a tool that claims to use agentic AI, don’t settle for marketing – ask how it actually reasons and acts. Any vendor offering agentic AI should be able to show it making real decisions, adjusting to new inputs, and explaining why it chose a particular action. If it can’t do that, it’s probably just rules dressed up as intelligence. That doesn’t make it useless, but it’s not agentic. One of the simplest ways to test that? Challenge it. Ask the AI why it made a decision, then push back and see if it holds up. If it can’t justify the action or adapt when questioned, it’s not thinking, it’s just following a script. Set aside time for testing and quality checks: Build a sandbox where you can watch how it behaves, break things safely, and tweak as needed. Reassess internal processes: Agentic systems can take over entire parts of a process, which means your docs and SOPs will need a refresh. Engage cross-functional stakeholders: Technical staff, client services, and compliance teams need to collaborate to make sure everyone’s aligned. Plan for iteration: As the AI evolves, feedback loops and review cycles must be in place to update logic, permissions, and integrations. Getting started takes time, but if you stick with it, you’ll end up with a system that runs smoother, responds faster, and doesn’t need more people to scale. Escalation thresholds: If confidence is low, hand it off to a human before anything moves forward. Audit trails: Log what the AI does and why, so you can check its work and keep it accountable. Approval checkpoints: For anything high-risk, make sure a human signs off before the AI takes action. Putting limits in place isn’t about holding the AI back – it’s about making sure it works the way you want it to. The best MSPs won’t just let it run wild; they’ll treat it like a teammate that still needs oversight. Start in triage: Use AI to sort tickets and take first steps. This is the fastest way to see impact without high risk. Set confidence thresholds: Define what “sure enough” looks like before the AI makes a move. Run a pilot: Pick one workflow, keep it contained, and track how the AI stacks up against your team. Build for scale: Don’t duct-tape it in – set it up right so it can grow with your service model. Get your team ready: Make sure staff know how to read AI decisions, spot red flags, and step in when needed. Adopting agentic AI is about building a foundation that lets your business grow with the technology, not fall behind it.
ChannelE2E Perspectives columns are written by trusted members of the managed services, value-added reseller, and solution provider channels or ChannelE2E staff. Do you have a unique perspective you want to share? Check out our guidelines here and send a pitch to [email protected].
How Agentic AI Is Already Solving Problems for MSPs
While agentic AI is still gaining traction across industries, its most immediate impact for MSPs is in triage and dispatch. These are natural fits – AI can take in a ticket, figure out what’s going on, and either fix it or hand it off. No human intervention is needed – it just gets to work. This is more than automation. Agentic AI interprets natural language, evaluates tone and context, and makes decisions based on internal confidence scoring. Unlike rule-based systems, it doesn't need constant updates or manual overrides. This reduces resolution times and allows service desk staff to focus on higher-order tasks. And beyond triage and dispatch, MSPs are starting to use it in areas like:How to Tell If It’s Really Agentic AI
Not all AI products marketed to MSPs meet the bar for agentic capabilities. To figure out if a solution is truly agentic, consider these functional benchmarks:This Isn’t Set-and-Forget Tech
Agentic AI is not plug-and-play. Rolling it out requires a commitment to configuration, oversight, and continuous learning – not only for the technology, but for the team using it. MSPs preparing to implement agentic AI should:Putting Guardrails in Place
Just because the AI can act on its own doesn’t mean it should do everything unchecked. MSPs still need to define where the guardrails are. To keep things safe and under control, put a few basics in place:Where to Start
MSPs don’t need to overhaul everything at once. The right approach is to start small, stay hands-on, and build from a solid base. Focus on clear wins, test early, and set yourself up to scale. Here’s what that can look like in practice:Delay Comes at a Cost
It’s fair to be cautious. There’s a lot of noise in the market, and not every tool that claims to be “AI” is actually doing anything smart. Some of it is just old automation in new packaging. But real agentic AI is already reshaping how MSPs work. It’s faster, cheaper, and more capable than it was even a year ago, and it’s only accelerating. More importantly, clients are starting to ask about it. They want to know what it can do and when they can start using it. Choosing to sit this out isn’t a neutral move. It means falling behind MSPs that are already using AI to move faster and do more, missing out on efficiency gains that cut costs without cutting corners, and losing ground with clients who expect their provider to be ahead of the curve. The safest move right now isn’t to wait; it’s to get informed, test what’s out there, and figure out what fits your business. The ones who start early will be the ones who stay ahead.ChannelE2E Perspectives columns are written by trusted members of the managed services, value-added reseller, and solution provider channels or ChannelE2E staff. Do you have a unique perspective you want to share? Check out our guidelines here and send a pitch to [email protected].
