Editor’s note: The following is a guest post by Kyle Schofield, client director in the MSP division at IT services provider ContinueServe.
Twenty years ago, IT support meant a technician waiting for the phone to ring. Something broke, the tech showed up, fixed it and sent an invoice. Today, the best systems catch problems before anyone even notices them. That didn't happen overnight, and it certainly didn't happen by accident.
Every few years, the channel gets handed a "next big thing." Partners that jump on it early pull ahead. The ones who wait spend years playing catch-up. AI and automation are the latest opportunity and, if history is any guide, it’s going to have a sorting effect.
A paradigm shift
Under a break-fix IT support model, when a server went down, the partner got a call and the relationship ended when the invoice was paid. There was no recurring revenue — for most shops, MRR was a pipe dream.
The cloud pulled infrastructure out of the client's server closet and into a model partners could deliver and scale remotely. Proactive monitoring and SLAs gave partners a reason to stay engaged between emergencies. Cybersecurity had a similar effect. As complexity grew, tasks that had been on a generalist’s to-do list folded into a managed services practice.
Now, AI-driven automation is driving change.
Picture a service desk where routine tickets get triaged and resolved before a technician ever touches them. Patching and monitoring that just run with minimal human oversight. That's where AI agents/copilots are taking IT service delivery.
The security operations center is already showing us what that looks like. SOC analysts deal with a flood of alerts every day, and most of it is noise. AI tools can correlate that data and surface the real threats faster than any analyst working alone.
But efficiency is only half the story. The threat actors have access to the same tools, and they're adopting them just as fast as we are. Protecting clients now means building AI-driven defenses. Those services are still being figured out, and the partners who help shape how they're delivered will set the standard for everyone else to follow.
The race to deliver these services has already started. Larger providers are moving downmarket with AI-enabled offerings aimed squarely at midmarket accounts that many channel partners consider home turf. Meanwhile, small and midsize organizations want an AI strategy but don't have a clear plan or the talent to build one internally. A gap is opening for partners who can lead the conversation.
Budget pressure widens that gap. With capital spending staying cautious, more mid-market organizations are looking to outsource and share the cost of scaling AI. That requires partners that are selling more than initial implementation.
The lessons of cloud and cybersecurity
We've seen this movie before. Too many partners treated the move to the cloud like a finish line. They sold lift-and-shift, closed projects, and moved on, leaving recurring revenue from ongoing optimization on the table.
I saw the fallout firsthand. One client was spending millions a year on cloud infrastructure inherited through acquisitions. A lot of it was redundant or unused. A closer look uncovered hundreds of thousands of dollars in savings, and that was just the tip of the iceberg. Without continuous governance, cloud costs spiral. That same gap between adoption and ongoing support is likely to repeat with AI unless partners build ongoing management into their offerings from day one.
AI isn't plug and play. Selling a tool is easy. It takes training, governance and rollout support built into the package, as cloud and cybersecurity eventually required. Skip that work, and clients end up pouring money into legacy refreshes, sitting on expensive shelfware they bought with enthusiasm but never adopted.
Partners can build an AI business around three basic pillars:
- Stand up automation and cloud security as dedicated service towers, just as cybersecurity split off from generalist IT support a decade ago.
- Package AI governance and change management as a salable service, not an afterthought bolted onto a tool sale. Clients can't build this on their own, which is exactly why it belongs on your service list.
- Use your scale to make AI tooling affordable as an operating expense instead of a heavy capital investment for clients. That's a difference smaller or newer providers will struggle to match.
None of this is new. It's the same path the channel has followed since break-fix gave way to managed services: from fixing things to managing things to building self-managing systems. Partners that rebuild their delivery model around that idea can set the pace for the next era of managed services. Those who wait will spend the next five years trying to catch up.
