Summary: Microsoft Ignite 2025 accelerated the move toward AI-powered support, but MSPs face several adoption hurdles. Mature processes, readiness for short-term operational lift, cost control, and client pacing all shape the success of MSP AI adoption. Stronger operational readiness and structured rollout planning are now essential.
At Ignite 2025, Microsoft introduced a wave of new AI capabilities designed to reshape how MSPs deliver support. From autonomous ticket triage in Teams, to AI-driven workflows inside Power Apps, to new agentic capabilities for Sales and Support, the message was clear; AI will be foundational across Microsoft’s solutions, and Microsoft is looking to MSPs to support these deployments at scale. In addition, Microsoft further defined what it means to be a Frontier Firm and introduced new partner incentives for those that accelerate their adoption of AI led solutions.
For MSP leaders responsible for customer success and service delivery, this represents both opportunity and pressure. AI-powered services can create differentiation, improve efficiency, and strengthen client value. But clients may not be as ready for AI enabled services requiring most MSPs to most likely take a staged approach that can complicate operations in the short-term.
Top AI Adoption Challenges MSP Leaders Need to Plan For
As MSPs move toward Microsoft’s new AI capabilities, they are doing so against a backdrop of rising support volume, higher labor costs, and growing expectations for consistent outcomes. The real challenge is not turning on the technology but being prepared for what it requires. AI implementations struggle in environments that lack structure, documentation, and time for teams to adjust. From our work at The Functionary supporting MSPs through operational change, four challenges consistently emerge as the biggest barriers to successful adoption.
I. AI Fails Without Preparation, Structure, and Predictable Processes
Why workflow consistency is the foundation of every successful AI rollout.
One of the first things we see when MSPs struggle with AI is a lack of preparation. AI works best when teams build structured, predictable processes the technology can learn from. We recently supported an MSP whose ticket queues looked completely different from one technician to another. Escalation notes were inconsistent, a third of the Knowledge Base Articles (KBAs) proved outdated, and the same issue was being solved five different ways. No AI system can interpret that type of variance.
Our team rebuilt the operational foundation by standardizing ticket categories, cleaning up hundreds of Standard Operating Procedures (SOPs), rewriting escalation paths, and updating KBAs using our AI-assisted QA framework. Within 60 days, the backlog dropped by nearly 40% and first-call resolution increased, even before we turned on automation.
This pattern shows up across MSPs. AI requires a solid foundation. If SOPs are outdated, KBAs are incomplete, or documentation is inconsistent, the environment is not predictable enough for automation to succeed. When workflows are clear and documentation is current, AI can deliver the outcomes MSPs are promising to their clients.
II. AI Rollouts Require Organizational Change Management (OCM), Not Just New Tools
Why MSP teams feel more strain before they see efficiency gains.
As teams start rolling out AI capabilities, one of the biggest challenges is not the technology itself but the impact it has on day-to-day work. AI changes how work gets done, which creates questions and uncertainty that leaders need to plan for.
Most teams need time to understand what is changing and why. Simply announcing that “the new AI workflow is live” does not guarantee adoption or confidence. Ongoing support helps people adjust to new steps, behaviors, and ways of working. And helping teams prepare for that change is just as important as configuring the tool itself, especially when long-standing processes and systems require updates.
As teams move through the transition period, the operational load typically increases. Engineers take on more oversight and hands-on review. Managers devote more time explaining goals, reinforcing expectations, and checking in with customers.
III. AI Adoption Intensifies Margin and Cost Pressures
Why early automation increases oversight, not savings.
When MSPs start building automation into their service delivery, a key goal is to reduce labor costs. But in the early stages, AI typically shifts the work rather than reducing it. During early automation, teams often spend more time validating AI outputs, reviewing exceptions, and updating SOPs to ensure automation performs consistently. SLA commitments stay the same, but the operational mix becomes more complex.
One MSP we supported saw ticket volume drop after introducing automated triage, but margins did not improve. Engineers were still tied up in oversight, cleanup work, and training customers on the new flow. The benefits were delayed because the operating model was not designed to absorb the added load. AI reshapes where effort goes, but until processes and team structures catch up, the early stages often increase cost pressure.
IV. Client Readiness for AI Adoption Varies Widely
Why service delivery leaders must support customers moving at different speeds.
When MSPs begin planning their AI roadmap, one of the first hurdles they run into is client readiness. Within the same portfolio, some customers are eager to adopt AI-driven workflows, while others want to continue using the tools and processes, they already trust. The hesitation is not always about the technology. Sometimes it is about security concerns, process maturity, internal bandwidth, or simply wanting to see more stability before changing how work gets done.
A big part of closing that gap is helping clients understand where AI is a good fit and where it is not. Some functions are strong candidates for automation, and others need more stability before AI can add value. Working through that prioritization gives clients clarity and builds trust.
Why MSPs Partner with The Functionary
The Functionary helps MSPs operationalize Microsoft’s new AI capabilities with a flexible, scalable model that bridges transitional gaps and aligns to each client’s adoption pace. Our approach brings structure, capacity, and predictable execution to the moments that matter most.
We support MSPs by reinforcing operational discipline
- Strengthening operations through process audits, SOP cleanup, and documentation improvements
- Creating automation-ready workflows that reduce variability and support long-term AI adoption
- Applying AI-assisted QA to raise accuracy and consistency across service delivery
We expand capacity so teams can focus on higher-value work
- Providing scalable Tier 1 and L1.5 teams with extended hours and 24/7 coverage options
- Offering rapid ramp capability supported by our global talent pipeline
- Delivering a stable operational layer that absorbs rollout workload and reduces engineer burnout
We deliver predictable outcomes through our People + Process + AI model
- Maintaining consistent SLAs across complex environments
- Bringing process maturity, quality controls, and ongoing refinement into daily operations
- Helping MSPs scale without expanding internal headcount
We adapt to each customer’s readiness level
- Supporting the tools, systems, and workflows clients already use
- Allowing MSPs to advance their AI roadmap without leaving behind customers who need a slower or more stable transition
We support AI adoption after go-live
- Running governance checkpoints that track adoption, accuracy, effectiveness, and cost impact
- Facilitating Voice of the Customer sessions that help teams understand concerns, gather feedback, and reinforce adoption
- Building roadmaps that guide additional AI capabilities and support teams through ongoing changes
Together, these capabilities give MSPs the structure, capacity, and operational readiness to accelerate AI adoption into measurable improvements across service delivery, customer experience, and profitability.
Interested in learning more? Book a consultation with our MSP delivery team today.