Why AI Outcomes Belong Inside Managed Services

AI has changed what businesses need from technology.

Support still matters. Security still matters. Reliable systems and proactive technology planning still matter. But businesses now also expect technology to help them improve productivity, remove manual work, automate workflows, make better use of their data and help their people get more from AI.

That means AI cannot sit off to the side of managed IT as a separate initiative.

Getting real value from AI takes more than giving people access to new tools. It takes the right support, security, data governance, training and business processes working together. Increasingly, those are not separate from the managed technology environment. They are part of it.

That is why First Focus, an MSP, being named the 2026 CRN AI Initiative of the Year for CORE matters to us beyond the award itself. CORE was built around exactly this idea: not AI bolted onto traditional IT support, but AI, automation, security, data governance, training, support and ongoing improvement brought together in one managed services model.

CRN’s coverage of the award quoted First Focus Managing Director Ross Sardi explaining that the traditional managed services model was built to keep technology running, but now needs to help businesses continuously improve how they operate, with AI and automation becoming part of that responsibility.

Read CRN’s coverage of First Focus winning AI Initiative of the Year

That an MSP won the category is an interesting signal in itself. CRN could have recognised an AI startup, software company or specialist consultancy. Instead, its AI Initiative of the Year came from a managed service provider evolving the relationship it already had with customers.

I think there is something important in that. AI does not need to become another service sitting beside managed IT. It needs to sit at the core of what a good MSP delivers.

The foundation remains. The opportunity gets bigger.

For a long time, the job of managed IT has been predominantly defensive.

Keep the lights on. Keep people working. Reduce downtime. Protect the environment. Make sure systems remain reliable. Help the business plan what comes next.

Those things have not become less important because of AI.

If anything, they have become more important.

Safe AI adoption depends on good security. Useful AI depends on good data. Automation depends on reliable applications and integrations. Employees cannot adopt new technology effectively if the underlying environment is poorly managed.

The foundation remains.

What has changed is the opportunity sitting on top of it.

Technology can now play a much more active role in improving how the business works.

• Where are people wasting time?
• Which workflow should be automated next?
• Which process could be redesigned?
• Where could better access to information improve a customer experience?
• Which teams could achieve more with AI?
• Where could the business create capacity without adding headcount at the same rate?

These are technology questions now too.

That is why the role of the technology partner has to expand.

It is no longer enough to understand systems. A modern MSP increasingly needs to understand the business, challenge processes and look at workflows through a productivity lens.

It is no longer only about keeping technology online.

It is about using technology to drive real business outcomes.

AI cannot be separated from the technology around it

The term “AI project” can make AI sound much more self-contained than it really is.

Imagine somebody in finance identifies a process that could be improved with AI.

Perhaps incoming documents could be read automatically. Information could be extracted. Another system could be updated. Exceptions could be flagged and something prepared for human review.

The AI element itself might be relatively straightforward. But making that idea genuinely useful raises a much broader set of questions.

• Where is the information stored?
• Is the data reliable?
• Who should have access?
• Are the permissions correct?
• Is any of the information sensitive?
• Which systems need to connect?
• How will identity and authentication work?
• What happens when an application changes?
• Who monitors the workflow?
• Who supports the people using it?
• How do we make sure it is being used safely?
• How will we know whether it has actually improved anything?

Suddenly the “AI project” depends on security, data, identity, applications, integrations, governance, workflows, training and support.

Those are not secondary considerations.

They determine whether the solution works.

And they are already fundamental parts of the technology environment an MSP is there to manage.

This is the problem with placing AI in a completely separate silo. The AI layer can be separated organisationally, but the outcome cannot be separated technically.

AI touches the environment your MSP is already responsible for, and that is why it belongs within the managed services model.

The wider technology market is moving in the same direction

A recent Sequoia Capital article, Services: The New Software, makes an interesting argument about where AI is taking the services economy more broadly.

Sequoia’s Julien Bek describes the shift simply:

“A copilot sells the tool. An autopilot sells the work.”

The point is that as AI makes software capability and intelligence increasingly accessible, value can move from supplying a tool toward delivering more of the work and ultimately more of the outcome.

What makes the article particularly relevant to MSPs is that Sequoia specifically identifies IT managed services as a $100B+ opportunity, pointing to the large amount of repeatable technology work already outsourced by small and midsize businesses.

Read Sequoia Capital’s “Services: The New Software”

I agree with the direction of travel, but I think there is an additional opportunity for MSPs.

The prize is not simply using AI to perform the existing managed services job more efficiently.

It is using AI to expand what the managed services relationship can achieve for the customer.

Closing tickets faster is useful, but helping a customer eliminate the workflow that keeps generating the tickets could be far more valuable.

Automating support tasks is useful, but helping employees redesign repetitive work across the business is a much bigger opportunity.

Using AI internally within an MSP is inevitable, but bringing AI into the way an MSP continually improves a customer’s business is the more important shift.

The lines between software and services are getting blurred

Integris CEO Rashaad Bajwa picked up on the same Sequoia argument and pushed it one step further.

His point was that if AI continues to make software faster and cheaper to create, then simply being able to build software becomes less distinctive.

The real differentiation moves elsewhere.

As Rashaad put it: “The special sauce is a mix of data, process engineering and vertical market expertise.”

That distinction matters.

The value is not simply in writing the code or choosing the AI model. It is in understanding the business problem well enough to redesign the process, knowing which data matters, understanding the industry context, and then using software, workflows, automation and APIs to deliver a better outcome.

That is why Rashaad later described the market as one where “the lines are getting blurred.”

A traditional software company might once have sold the application.

A consultant might have advised on the process.

An MSP might have managed the environment.

A developer might have built the integration.

Increasingly, those capabilities need to work together.

And from the customer’s perspective, that makes sense.

A business does not ultimately care whether improving a process required an AI agent, an API, an automation, better permissions, SharePoint remediation, custom development or training. It cares that the process became faster, safer or more productive. That is where this becomes particularly relevant to managed services.

An MSP that already understands the customer’s technology environment, data, users, security requirements and business processes is increasingly well placed to bring those capabilities together around the result the customer is trying to achieve.

That is the blurring Rashaad is pointing to.

Not that every provider becomes the same thing.

But that the customer outcome increasingly cuts across the old boundaries between software, consulting, AI and managed services.

Support also needs to go beyond fixing what’s broken

One of the most tangible ways I think managed services will change is through the support experience itself.

Historically, an employee contacts IT because something is not working.

• Their laptop has a problem.
• They cannot access an application.
• Microsoft 365 is behaving unexpectedly.
• They need help with a device.
• That support remains essential.

But there is now another type of technology request.

• Someone is using AI and gets stuck.
• Someone has worked out a smarter way to perform part of their job but does not know how to make it work securely.
• Someone has created an automation that gets most of the way there but needs help connecting it to another system.
• Someone has a good prompt but wants to turn it into a repeatable workflow.
• Someone has built something useful with an AI-assisted development tool but needs help with security, permissions, deployment or integration before the rest of the team can use it.

The question is no longer only:

“Something’s broken. Can you fix it?”

Increasingly, it is also:

“I’ve got a better way to do this. Can you help me bring it to life?”

That should be part of modern technology support.

The people inside a business often know the problems worth solving better than anybody else.

• They know the workflows that frustrate them.
• They know where information gets entered twice.
• They know where customers wait unnecessarily.
• They know which spreadsheet nobody wants to maintain.
• They know which repetitive tasks take time away from better work.

AI increasingly gives those people the ability to start solving those problems themselves. A managed services model built for the AI era should give them ready access to the expertise required to finish the job.

Access to AI is not the difficult part anymore

Most businesses can buy ChatGPT, Claude, Copilot, Gemini or another AI platform tomorrow.

Access is easy.

Generating measurable value is much harder.

Businesses still need to decide who should use which tools and what they should use them for.

• They need to make sure those tools are being used securely.
• They need appropriate data governance.
• They need training.
• They need adoption.
• They need to decide which opportunities deserve investment and which do not.
• They need to measure whether the initiatives they have already implemented are actually producing a return.
• And they need to keep asking what comes next.

Without that ongoing process, AI can easily remain concentrated in the hands of a handful of enthusiastic users while everyone else carries on exactly as before.

Buying AI is easy. Building a business that uses it effectively is harder. That is exactly why it belongs within an ongoing managed services relationship.

The technology conversation needs to expand

A good meeting with your MSP account manager should still cover the fundamentals.

• Technology health matters.
• Security posture matters.
• Support performance matters.
• Lifecycle planning and budgets matter.

But the conversation can no longer end there. It should increasingly include questions like:

• Where is AI adoption growing?
• Where are employees getting stuck?
• Where is poor data preventing better outcomes?
• Which process frustrated people this month?
• Which workflow could we improve next?
• Which initiative is creating value?
• Which team needs more training?
• What is the highest-value technology opportunity we should pursue before we meet again?

This is not about introducing AI for the sake of AI.

In fact, it is the opposite.

The goal is to continually identify where technology can create measurable improvement, prioritise the opportunities that matter and stop investing in the ones that do not.

That is a much more useful definition of modern managed services than simply managing a collection of technology products.

This is why we built CORE as a Managed AI & IT Service

CORE was not built as another AI add-on.

It was built to bring the capabilities businesses now need together in one managed services model designed for the AI era.

• Support.
• Security.
• Data governance.
• AI and automation.
• Training and enablement.
• Account management and technology strategy.
• Ongoing improvement.

The aim is not to replace the managed IT foundation that customers already rely on.

It is to make that foundation more valuable.

The same environment that keeps a business secure and supported can become the foundation for better AI adoption.

The same understanding of a customer’s applications and users can help identify where workflows should improve.

The same ongoing relationship can provide employees with somewhere to go when they have an idea, not just when something fails.

And the same regular technology conversations can start asking not only what needs to remain stable, but what should become better.

That, more than the trophy itself, is why the CRN AI Initiative of the Year recognition means so much to us.

It is a sign that the industry is beginning to recognise that AI does not have to sit outside managed services.

It can be part of what managed services becomes.

AI has changed managed services because AI has changed technology

This is ultimately a simple argument.

AI is now part of how people work.

It increasingly touches the applications they use, the information they access, the security controls protecting that information, the workflows they follow and the support they need.

It therefore makes less and less sense to treat AI as something separate from the technology environment around it.

The foundation remains support, security, reliable systems and good technology management.

But the opportunity is now much bigger.

A modern MSP should also be helping customers adopt AI safely, automate work, improve productivity, govern their data, support their people and continually identify where technology can create more value.

AI has changed what businesses need from technology, and with CORE, First Focus has changed what it means to be an MSP.

learn more about core