Building autonomy in layers: How MSPs and IT teams can get agentic AI adoption right

AI isn’t just about automation anymore, it’s about autonomy. What makes this wave of agentic AI powerful is that it goes beyond fixed workflows and rule-based automation; it can now understand context, learn from data, and apply reasoning.

This, however, doesn’t mean that AI can now handle everything on its own. The truth is, AI can’t do everything on its own. Even the most powerful AI models need that human trigger to get started and human oversight to ensure that it is on the right path. Guardrails and human involvement are critical to make agentic AI work. 

AI brings the scale we’re looking for, but humans still provide the domain knowledge that trains and nudges the AI, making sure it delivers real value. What’s really happening is a shift to having AI as a coworker. AI is not replacing technicians; it’s working alongside them. That collaboration is what allows us to make the best use of AI features.

So then, how do organizations balance AI’s autonomy with human oversight?  The key is to unlock autonomy step by step. 

Building autonomy one layer at a time

Everybody is thinking about AI on a large scale, imagining dramatic, immediate change. But AI isn’t something that can change things overnight. It needs to be implemented thoughtfully, in context, one step at a time. 

Embrace AI internally first 

Today, around 41.5% of MSPs use AI in at least a quarter of their operations. But most are still stuck in the slow lane. High-growth MSPs are those that are 75% more likely to use AI for internal processes and client wins. 

So to avoid the risk of falling behind, business leaders need to actively drive adoption. It can be slow and cautious, but every business leader and IT professional has to embrace AI; it is no longer an option. 

“You know the best thing is to eat your own dog food. You learn it, and that’s how you can advise accordingly and implement those business processes for all small businesses or clients and make sure that they are at a competitive edge, whatever field they are in. There’s no better way than to embrace AI today.” - Chee Lam, managing partner at Technique Ltd.

Start small 

You have to start small, and ideally do so with internal processes. If you can’t adopt AI within your own operations, you won’t be in a position to help your clients and act as a thought leader.

The best way to adopt AI is to automate small, repetitive tasks and use AI to make your existing processes smarter and more efficient. Jump in too deep too fast, and you’ll miss the outcomes you expect.

Once you’ve introduced it into one part of your business, you can slowly introduce it into another. Eventually, you reach the point where AI doesn’t run your business, but it runs through all different parts of your business, extending even to your clients.

“Start with an AI policy that outlines what AI can be used for and what it shouldn’t be used for. It starts by giving you small wins in the business, saves time, and the more you press on it, the more it can help you win business and streamline your operations.” - Sam Godfrey, cofounder and director of TaskGroup (CompuTask Ltd)

Have a healthy human-AI collaboration

One of the most important responsibilities of an MSP is talking to clients regularly, nurturing the relationship, and engaging with them beyond simply providing IT services. Human-to-human communication and connection are what differentiate businesses, including MSPs. And AI helps with this. 

For example, some of SuperOps’ customers use the AI features to glean customer insights. Employees who would otherwise have to spend days compiling and analyzing such insight, now simply use AI and do it in minutes. The IT leaders then validate the analysis and insights by having humans vet the AI-generated insight. Essentially, AI is like a super sharp intern, a second pair of hands and eyes on a project. 

“Right now, think of autonomy like self-driving cars: level one to five. We’re probably around level three — AI resolves low-risk issues and can close tickets. Some workflows can already operate at level four, running fuller workflows and resolving tickets to a point. It cuts down mundane tasks and enhances customer experience.” -  Chee Lam, managing partner at Technique Ltd.

For more real-world stories of how MSPs are adopting agentic AI, watch the recording of our recent webinar with Chee Lam, Sam Godfrey, and the SuperOps team - Jayakumar Karumbasalam - CTO & Co-founder, Arjun Marella - Head of Business – ROW, and Sriram Prasad - Product Marketing Manager.

The three levels of autonomy 

An agentic AI-first organization needn’t be fully autonomous on day one. It can’t, in fact. 

Adopting agentic AI is just like hiring and training people, in that there’s a maturity curve and it takes time for the new entrant to learn the process, establish credibility, and earn trust before handling major tasks themselves. 

At SuperOps, we approach autonomy in agentic AI in three levels:

1. Assistive - This is where AI acts as a digital assistant sitting beside your technician. It makes information available quickly, reduces human effort on repetitive tasks, and saves time by handling tasks such as report creation, writing scripts, or drafting customer responses.  This is the initial level of autonomy and the ideal place to start to build familiarity and comfort with the tool.

2. Advisory, with human approval: The next stage is when AI performs a bigger chunk of work such as diagnosing an endpoint issue or suggesting a patch, but stops before final execution to ask the technician or manager for approval. This phase is important to build trust. 

3. Fully autonomous: Once you trust the AI and see that it can carry out repetitive, low-risk jobs accurately, you can gradually let the AI handle more.

The path to becoming AI-first

AI only works if the whole team uses it. If one person champions it and the rest don’t, adoption won’t stick. AI has to be part of everyday workflows, not an optional tool.

The way to make that happen is to put processes in place so adoption happens gradually and measurably. Each stage should earn its place by proving value before you move forward. Simple things like assigning trust scores can help teams decide when it’s safe to hand workflows over to AI agents.

Even as autonomy grows, people remain essential. Anything that involves empathy, nuance, or client communication still needs human oversight. This is where AI supports the work but humans carry the responsibility.

Another factor that requires practice and conscious effort is prompting. Poor data and poor prompts are the two biggest reasons AI adoption fails. Learning how to frame prompts clearly and effectively can shape how AI works for you.

Start small, build trust in layers, and keep humans at the center. The MSPs that embrace this shift today will be the ones leading the industry tomorrow.

You can enter the AI era with SuperOps, a unified platform powered by agentic AI and built for scale. The platform is designed to help MSPs unlock autonomy in stages, so you can move towards being truly AI-first with confidence. Schedule a demo with us to learn how you can get started.