At an exclusive event in Miami, MSP leaders detailed how they’re applying AI to streamline operations, tighten governance, and prepare for the next phase of managed services.
By Larry Walsh
The managed-service industry has weathered multiple waves of disruption over the past two decades. I’ve watched the shift from break/fix to recurring revenue, the migration to cloud, and the rise of cybersecurity as a board-level concern forcing MSPs to rethink not just their tools but their entire operating models.
Artificial intelligence represents the next inflection point.
At the ConnectWise AI Futures Summit in Miami (photo above), I joined managed-service providers from across North America to examine how AI is moving from concept to operational reality. The discussion wasn’t theoretical. It focused on practical application — how AI changes ticket workflows, technician productivity, customer experience, and ultimately profitability.
ConnectWise, long a central figure in the managed-service ecosystem, reinforced its commitment to AI with its acquisition of start-up zofiQ. The objective is clear: Deliver purpose-built AI capabilities embedded directly in MSP service operations.
I led a panel discussion with three MSP executives who are actively integrating AI into their businesses: Mike Camp, COO of Nexigen; Rick Mutzel, manager of technology at Omega Systems; and Aaron Boeker, chief service officer at Starport Managed Services. Through the discussion and interaction with the audience, five primary themes rose to the surface.
1. AI Delivers Operational Efficiency
The panelists were aligned on a central point: AI produces measurable results when applied to defined workflows and processes, particularly those that are inefficient.
Rather than treating AI as a broad innovation initiative, they’ve focused on repeatable, high-volume tasks – ticket triage, categorization, agreement assignment, documentation lookup, and prioritization. In these areas, AI has delivered immediate impact. They reported reduced average resolution times, increases in tickets closed per technician, and improved customer satisfaction scores.
AI is a tool, not a strategy. While it won’t diagnose and resolve undefined problems on its own, it delivers value when applied to specific operational friction points.
FOR MSPs: Operational discipline now directly ties to AI ROI. MSPs with documented processes, standardized ticketing, and clean data will see faster returns, while those with inconsistent workflows will struggle because AI can’t optimize chaos. By reducing handling time and increasing ticket throughput, AI improves labor efficiency and gross margins, giving early adopters a structural cost advantage.
FOR VENDORS: Vendors need to move beyond generic AI positioning and prove measurable workflow-level outcomes. MSPs aren’t investing in abstract AI strategy; they’re investing in fewer tickets, faster resolution, and greater technician leverage, with proof tied to operational KPIs. Embedding AI directly into PSA, RMM, security, and documentation platforms is essential, as MSPs don’t want another dashboard. Vendors that reduce swivel-chair operations and integrate intelligence into daily workflows will drive stronger adoption and retention.
2. AI Reveals Hidden Inefficiencies
What became clear in the discussion is that AI does more than save time. It exposes inefficiencies that many MSP teams have normalized.
Once triage and prioritization were automated, service leaders gained visibility into inconsistencies in categorization, agreement mapping, and documentation practices. Tasks that technicians had been compensating for surfaced as structural gaps in process discipline.
AI doesn’t simply accelerate existing workflows. It highlights weaknesses that demand redesign. MSPs that treat AI as a catalyst to refine their service architecture — not just automate individual tasks — are more likely to extract long-term value.
FOR MSPs: AI becomes a diagnostic tool, exposing process inconsistencies, poor data hygiene, and undocumented tribal knowledge. MSPs that address those gaps will mature quickly, while those that ignore them will see only marginal gains. AI adoption isn’t just a technical deployment; it requires service leadership to treat it as an operational transformation initiative.
FOR VENDORS: Vendors can position AI within a broader operational maturity framework, recognizing that tools alone will not fix structural inefficiencies. Those that offer best-practice guidance, benchmarking, and implementation support will strengthen partner relationships. At the same time, if AI exposes poor data quality or flawed processes within their own platforms, MSPs will expect remediation, making platform robustness and transparency essential.
3. Governance & Security Are Imperatives
Enthusiasm around AI adoption was balanced by legitimate concerns about data exposure and compliance.
The risk of technicians using public AI tools and inadvertently exposing sensitive client data is real. In response, some MSPs have consolidated AI usage into controlled environments, restricted unauthorized tools, and formalized governance policies around prompt usage and data handling.
For MSPs serving regulated clients, data integrity and confidentiality can’t be secondary considerations. AI increases efficiency, but it can amplify risk if not properly governed.
FOR MSPs: AI governance, including acceptable-use policies, data-handling standards, audit controls, and vendor vetting, must be formalized early. While informal experimentation can speed learning, unmanaged use increases liability. As AI becomes embedded in service delivery, MSPs must also communicate clearly with clients, making transparency around data processing and protection central to maintaining trust.
FOR VENDORS: Security architecture will become a primary differentiator as MSPs demand clarity around data isolation, model training boundaries, and compliance certifications. Vendors that can’t clearly articulate those safeguards will face resistance. Those that build centralized AI controls, logging, and governance tooling into their platforms will reduce risk for MSPs and create stronger, stickier ecosystems.
4. Cultural Adoption Matters as Much as Technology
Technology implementation alone doesn’t guarantee results.
Some technicians initially viewed AI-driven workflow automation as a threat rather than a resource. In some cases, AI reclassified ticket priorities more accurately than staff, exposing inconsistencies in human judgment.
Leadership messaging proved critical. AI was positioned as an operational necessity designed to enhance service delivery and scalability, not as a cost-cutting mechanism aimed at eliminating roles.
FOR MSPs: Change management is now a core leadership competency. Without clear communication, AI can generate internal resistance; with proper framing, it becomes a tool that allows technicians to perform higher-value tasks. MSPs must also invest in training, as prompt engineering and AI oversight are emerging skill sets, and teams that actively collaborate with AI systems will outperform those that use them passively.
FOR VENDORS: Vendors shouldn’t underestimate the enablement required for AI adoption. Without structured onboarding, use-case playbooks, and role-based training, implementation will stall. The vendors that succeed will equip MSP leaders with messaging frameworks, ROI models, and technician-level education materials that drive internal alignment and accelerate platform adoption.
5. The Future Is a Unified, AI-Orchestrated Platform
Today’s deployments focus largely on triage and workflow assistance. The longer-term vision is broader.
MSP leaders described a unified operational layer — a single AI-driven interface capable of analyzing ticket queues, referencing documentation, interpreting RMM data, initiating remediation scripts, and potentially executing actions autonomously.
The objective is to reduce fragmentation. Embedding intelligence across the entire tool stack and surfacing it through one coordinated experience changes the technician’s daily workflow.
FOR MSPs: Platform consolidation will accelerate as MSPs gravitate toward ecosystems wherein AI operates horizontally across tools rather than in isolated modules, since vendor sprawl undermines effectiveness. A unified, AI-driven operating model enhances scalability and strengthens financial performance, leading buyers to place a premium on MSPs that demonstrate automation maturity and reduced labor dependency.
FOR VENDORS: Platform strategy becomes decisive as AI orchestration demands deep integration across PSA, RMM, security, and documentation environments, putting pressure on siloed vendors to integrate or consolidate. The competitive landscape will shift toward ecosystem depth over feature breadth, with vendors that deliver a coherent, AI-enabled operational layer defining the next phase of managed-service tooling.
Looking Forward
AI in managed services is moving beyond experimentation. MSPs are already realizing measurable improvements in efficiency, service quality, and technician productivity. At the same time, they’re confronting governance requirements, cultural resistance, and operational redesign.
For MSPs, AI is both an efficiency engine and a structural catalyst. Those who approach adoption deliberately — targeting defined problems, embedding governance, aligning teams, and committing to platform coherence — will gain sustainable margin advantages and stronger enterprise value.
For vendors, AI isn’t a feature release cycle. It’s a strategic repositioning. The winners will be those who embed intelligence natively, support operational maturity, enforce governance, and unify fragmented toolsets in coordinated ecosystems.
AI won’t replace managed services; rather, it will redefine how they’re delivered, priced, scaled, and valued. The inflection point has arrived. The question isn’t whether AI will reshape the industry but which organizations will lead the transition.
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Larry Walsh is the CEO, chief analyst, and founder of Channelnomics. He’s an expert on the development and execution of channel programs, disruptive sales models, and growth strategies for companies worldwide.
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