An MSP's guide to agentic AI

The spotlight is shifting. While generative AI has been the buzzword in recent times, agentic AI is emerging as the next pivotal technology that has been drawing attention across industries. For MSPs specifically, the adoption of agentic AI tools represents a significant leap forward, since they are an industry driven by speed, scale, and precision. This isn't merely about MSPs keeping pace, but about strategically leveraging agentic AI to gain a competitive edge and fundamentally transform IT automation and service delivery.

What is agentic AI?

Agentic AI refers to AI systems that act with agency; they can plan, reason, and make autonomous decisions based on a set of goals. While traditional AI typically reacts to inputs, AI agents proactively identify tasks, streamline workflows, and adapt in real time without needing constant human supervision.

The main difference between traditional automation and agentic AI is that traditional automation follows a pre-programmed script. If X happens, then do Y. With agentic AI, it is more like giving an intelligent assistant a high-level goal and the tools to achieve it. The agent then figures out the best course of action, adapts to changing circumstances, and even learns better ways to accomplish the task over time. Unlike traditional automation, which relies on predefined workflows, agentic AI exhibits autonomy and can handle unforeseen situations more effectively. 

Take the example of an MSP that needs to troubleshoot a client's slow internet. A regular AI chatbot could give generic advice like "check the router" or "restart your modem," based on past training. But with an agentic AI platform, it is like having the chatbot connected to tools that can run live diagnostics, check network traffic in real-time, and identify specific bottlenecks such as outdated hardware or bandwidth issues. Instead of just guessing, the technician gets a precise diagnosis and targeted solutions, like "the router's firmware needs an update" or "there's high traffic from a specific device," leading to much faster and more effective problem-solving with less manual investigation. 

What can AI agents do?

AI agents can be thought of as intelligent entities with the following capabilities:

• Perception: They are capable of understanding their environment, whether it's a network configuration, a system log, or a user request.

• Decision-making: They can analyze information, set goals, and formulating strategies to achieve those goals.

• Action: They execute tasks autonomously, from running scripts to troubleshooting issues and communicating with other systems.

• Learning: They can adapt and improve their performance over time based on experience and feedback.

Why MSPs should leverage agentic AI

As IT environments become more complex, MSPs are under pressure to deliver faster response times, reduce manual tasks, and scale operations without increasing overhead. This also allows MSPs to focus on high-value activities such as scaling their business. Here are some of the ways in which agentic AI can elevate MSP operations:

Autonomous remediation

AI agents can detect issues like CPU spikes or failed backups, analyze root causes using real-time and historical data, and apply fixes automatically. They log actions, update tickets, and notify stakeholders, and help cut down MTTR and technician effort.

Smart ticket handling

Agents can classify, prioritize, assign, and even resolve L1 tickets automatically. They can find KB articles, execute scripts, and close common issues, freeing up your team for more complex work.

Automated compliance and patching

Agents can continuously check systems for gaps in compliance, then apply patches or reconfigure settings based on policy. This keeps clients secure and audit-ready without manual checks.

Platform integration

Agentic AI can connect RMMs, PSAs, alerting tools, and documentation, automating workflows across systems. It reduces context-switching and ensures consistent, real-time data flow.

Proactive asset management

Agents can track hardware and software inventory, usage, and lifecycle data. They alert you on EOL assets, license issues, or policy violations, so you can stay ahead of problems.

Predictive maintenance and forecasting

Agentic AI can analyze trends in system performance, hardware health, and support history to predict future issues. Agents can flag risks early, suggest preventive actions, and help MSPs forecast resource needs, turning reactive IT into proactive service delivery.

Gearing up for the agentic AI future

While fully autonomous AI agents might still be on the horizon, the building blocks are here. MSPs should start exploring how they can integrate early forms of agentic AI into their workflows. This might involve:

• Invest in AI-powered automation platforms

• Upskill and educate your technicians on agentic AI fundamentals 

• Identify key areas for initial implementation where it can yield significant benefits

• Stay updated on the latest advancements and potential applications for your team

Agentic AI isn’t just a trend, it’s a sign of where the industry is headed. With AI agents being integrated into modern MSP platforms, early adopters will have a significant edge. Those who adopt agentic AI tools now will have a better edge to improve service levels, reduce churn, and scale with confidence.