How Partners Can Turn AI Interest into Repeatable Revenue
A practical path for MSPs to build measurable AI services and recurring revenue
Turn customer AI interest into measurable value
Customers are experimenting with AI, testing Copilot, and exploring where automation can improve their businesses. For MSPs, the opportunity is to turn that interest into measurable value - and a repeatable AI practice. In Episode 2 of OpenMic: Accelerating MSP Growth, Lynda Mahabir and I speak with OpenMic host Keelin Conant about how partners can lead with customer outcomes and build the right mix of technology, services, and support across the AI journey.
Five ways MSPs can build an AI practice
Expand beyond licensing: Build services around readiness, deployment, adoption, training, agent development, and ongoing management.
Match technology to the outcome: Use Microsoft 365 Copilot, Copilot Studio, or Azure AI Foundry according to the customer’s need.
Prove and scale value: Establish a baseline, measure results, start with focused use cases, and expand from early wins.
Start with focused use cases: Solve a specific business problem, involve users early, and build momentum from measurable wins.
Keep evolving the practice: Continue building expertise as AI capabilities change while staying anchored to customer outcomes, adoption, and results.
Think beyond the initial AI sale
When we think about monetizing AI, partners need to look beyond the initial license. The larger opportunity is helping customers turn an AI investment into business value they can see and measure. That opens the door to readiness assessments, deployment and professional services, adoption and training, agent development, and ongoing managed services. Partners also do not need to build every solution from scratch. Microsoft 365 Copilot can address everyday productivity needs, Copilot Studio can support low-code agents and workflows, and Azure AI Foundry can enable highly customized solutions. The right starting point is always the customer need and the business outcome - not the technology alone.
Make measurement part of the AI strategy
I encourage partners to make measurement part of the plan from day one. Capture a baseline before deployment, then choose metrics tied directly to the business problem the use case is meant to solve. Start with a specific challenge and a few meaningful use cases, involve users early, and prove value in a contained scenario before expanding. That approach not only validates the investment - it also shows where AI can deliver value next.
Build an AI practice that can evolve
AI technology will keep changing, but the customer’s business challenge may remain the same. That is why the strongest partner opportunity to build an AI practice is building a practice that can evolve. By continuing to develop expertise while staying focused on outcomes, adoption, and measurable results, MSPs can guide customers through new capabilities and create services that grow with their needs. For the full conversation on our discussion around how partners should approach monetizing AI, listen to Episode 2 of OpenMic: Accelerating MSP Growth, “How to Monetize AI,” featuring Steven Dantes and Lynda Mahabir.
Steven Dantes
Steven has 20 years of Microsoft experience spanning multiple industry verticals. He brings deep expertise in Microsoft Azure and Security solutions and specializes in helping partners build and scale successful Azure practices. Steven works closely with partners to scope and align projects within the Azure ecosystem, ensuring they are positioned for success. He delivers both in-person and virtual enablement training to support partner readiness and leads webinars and bootcamps that drive ongoing education, capability development, and engagement.
