AI adoption is growing among small businesses, but many are still figuring out how to turn the technology into meaningful operational improvements. That’s where managed service providers (MSPs) have an opportunity to demonstrate their value.
According to the Federal Reserve Bank’s 2026 Report on Employer Firms, 46% of small employer firms reported using AI, and 71% of those using it reported increased productivity. Yet only 7% of AI users said the technology was fully integrated into their business.
MSPs can help small businesses adopt AI through readiness assessments, use case identification, workflow automation, systems integration, employee training, and ongoing security and governance support. By identifying operational challenges and measuring the results of AI deployments, MSPs can help customers move beyond experimentation toward practical applications that improve productivity and deliver measurable business value.
What customers need from their MSPs
It’s important to be able to listen to what the customer does, and how they do it. Then provide suggestions on how AI can improve how they do it. If you can save them enough time, which always saves money, without a dip in quality, you’ve probably got a sale! And you deserve it!
The most successful MSPs focus not only on the initial sale, but also on retention and renewal. The ongoing growth of your business depends on them.
Once a customer becomes a customer, the job is to keep them a customer. So, once again you have to mine their operations to uncover other opportunities that can be accelerated and improved by AI. And then again. And again. It’s a simple case of “use it or lose it.”
Once you stop finding new ways for them to extract more return from their AI investments, the sooner they’ll want to stop using it… or using you.
For customers, it’s not about what the technology is. It’s about what it does for them that increases their success.
Start with the work customers don’t want to do themselves
Many of the tasks employees find least productive or rewarding are also candidates for AI-assisted automation.
These include repetitive activities like sorting, filing, categorizing and organizing data, filling out forms, and retrieving information from business systems.
AI can take some of that work off employees’ plates, leaving more time for activities they find productive and rewarding. The important distinction is that automation should improve a workflow, not simply introduce another tool.
One great example I’ve run into personally is actually getting answers to questions and doing deeper research.
Whenever you write anything, you first need to find information assets that provide important facts you’ll need, including quotations from notable people, announcements, and deeper details.
Imagine sitting at the keyboard and coming up with a question about what you’re writing. You’re probably “in flow” and don’t want to stop writing. But you need that answer. Without AI, you know that’s going to take your attention off the writing for just too long. So, you just keep plowing through, making a note to come back and look up that answer later. Often, you don’t.
Now, when that happens to me, as it does often, I just turn to my AI assistant and ask it the question. They obtain the answer instantly. I write in and move on without interruption. If I want, I can even drill deeper down into the answer to obtain even more valuable information. Again, without interruption.
AI-generated research still needs to be verified against reliable sources. But used properly, these tools can make information gathering more efficient.
The same principle applies to customers across industries: Find the repetitive work that consumes employees’ time, determine whether AI can perform part of it reliably, and measure the improvement.
Which AI use cases can deliver measurable ROI?
Think back to all the solutions you’ve designed and deployed over the years, and you’ll probably find you’ve served every department, every operation, and every category of work people do.
That experience gives MSPs a starting point for identifying practical AI opportunities.
Research and knowledge management
Professional services firms are already exploring how AI can reduce time spent researching, reviewing documents, and retrieving information.
In its 2025 Future of Professionals Report, Thomson Reuters found that surveyed legal professionals expected AI to free up nearly 240 hours annually, based on projected adoption.
Those are estimates rather than guaranteed savings, but they illustrate the potential value of reducing information-intensive work.
For MSP customers, similar opportunities may exist in internal knowledge bases, document retrieval, and employee support. An AI assistant connected to approved company information could help employees locate policies, procedures or technical documentation more quickly.
The MSP’s opportunity includes organizing the underlying data, configuring access permissions, integrating the assistant and evaluating answer quality.
Business operations and back-office automation
Repetitive administrative work presents another opportunity.
Invoice processing, document classification, customer onboarding, and data entry are all activities that can be accelerated through AI-assisted workflows.
Consider a customer whose employees spend hours transferring information from invoices into an accounting system. An MSP could evaluate whether document-processing tools can extract relevant fields, route exceptions for review, and reduce manual entry.
One example comes from AIM Consulting, which reportedly helped a company automate the processing of incoming tickets. Before implementation, employees spent approximately 80 hours each week manually extracting information from those requests. The AI-assisted system was reported to eliminate roughly 3,600 hours of manual work annually.
The return should be measured against the existing process: How much time does each transaction require? How frequently do errors occur? What does the new system cost to operate?
That’s a stronger business case than simply promising automation.
Sales, marketing and customer service
Sales and marketing teams also have opportunities to benefit from AI.
AI tools can help summarize sales calls, identify customer questions, organize CRM information and prepare account research. Customer service teams can use assistants to answer routine inquiries while escalating complex cases to employees.
The Federal Reserve’s 2026 small-business survey found that writing or marketing was the most common use of AI among firms already using the technology, followed by individual productivity and planning or analysis.
For MSPs, the opportunity is to move customers beyond individual experimentation and into repeatable, governed business processes.
That might mean integrating an AI assistant with a CRM, improving the accuracy of customer information or establishing clear rules for when human review is required.
Consider a 60-person B2B software company that worked with Applied Agents to automate inbound lead routing. By integrating HubSpot with Claude and n8n, the company reportedly reduced its median response time to demo requests from three hours and 40 minutes to just 11 minutes.
Importantly, sales representatives retained control of customer communications. AI helped classify leads, recommend assignments and draft responses, while employees reviewed and sent the messages. For MSPs, this illustrates how integrating AI into existing systems can improve a measurable business outcome without removing human oversight.
Compliance and security
Compliance and security workflows deserve particular attention because accuracy, confidentiality and accountability are essential.
AI-assisted tools may help organize evidence, summarize policies, prepare draft responses to security questionnaires and identify documentation gaps.
But those outputs need human validation. Incorrect evidence, fabricated references, or unauthorized exposure of sensitive information can create more problems than the technology solves.
The National Institute of Standards and Technology’s Generative AI Profile provides a useful framework for identifying and managing risks associated with generative AI.
MSPs can provide value by helping customers select appropriate tools, establish data-handling policies, configure access controls, and implement ongoing monitoring.
While your customers may not be UPS or Walmart, the fundamental principle applies to SMBs. Any customer with a van, a service truck, or a delivery schedule has route inefficiency they’ve stopped noticing. AI removes that inefficiency with intelligent routing.
Bottom line: solving your customers’ pain points is a services opportunity
Every successful AI deployment creates potential opportunities for services: setup, training, workflow design, integration, and ongoing tuning.
The most valuable work begins with understanding the customer’s business, not demonstrating the latest technology.
A customer who sees AI pay off in their own work won’t need much convincing to explore the next project.
Start with what they’ve been skipping.
READ MORE: Howard M. Cohen’s previous columns about practical ways for MSPs to embrace AI for themselves and their customers are available here.