What 100 MSP Leaders Taught Me About AI in One Room
I recently had the privilege of joining and speaking with roughly 100 leaders of Managed Services Providers — direct competitors, all gathered in the same room to discuss the current state, desired future state, and unknowns of leveraging Artificial Intelligence in their businesses. It's inspiring to see competitors supporting each other in this journey.
The AI conversation in the MSP space is no longer "if." It's how, where, and how fast it pays back. The FOMO is real, but so are the results.
Success Patterns I Heard
These weren't hypotheticals. These were MSPs in the room sharing what's already working, focused on outcomes rather than technology for its own sake.
Ticket data becomes an asset. Every ticket is a data point. LLM-enriched metadata, better root-cause tags, and context packs are cutting research time and lifting first-contact resolution on those painful 1+ hour tickets. Tools like Pia, MSPBots, and Neo Agent are leading the charge on AI-driven ticket triage — auto-categorizing, prioritizing, and routing to the right technician automatically.
Context-aware triage and routing. Enriched tickets plus client stack details, SLAs, entitlements, and skills matrices are driving automated assignment to the best team or individual. The result: fewer handoffs, lower MTTR, healthier backlog.
SOW generation that sells and delivers. Templated scopes from historical delivery data, standardized risks and assumptions, and pricing checks are reducing turnaround time and improving standardization. Clients and delivery teams both get a more consistent experience.
Stop selling AI — sell outcomes. The leading MSPs in the room aren't pitching AI to their clients. They're packaging it as reduced MTTR, predictable margins, SLA adherence, and auditable services. Buyers don't want a model. They want certainty and evidence.
Themes That Kept Coming Up
Across every breakout and hallway conversation, the same patterns surfaced:
Start with your data, not a new platform. The MSPs seeing the fastest ROI are the ones who began by enriching what they already have — ticketing systems, documentation, client records — rather than buying a new AI platform and trying to find a use case for it.
Make governance and observability first-class. With 96% of MSPs believing AI will drive growth in 2026, the temptation is to move fast. But the MSPs who'll still be standing in two years are the ones building governance into the foundation, not bolting it on after an incident.
Price for outcomes, not effort. This one sparked real debate. The shift from cost-plus labor to value-based pricing is uncomfortable for organizations built on billable hours, but it's where the market is heading.
Put change management on the critical path. The technology is the easy part. Getting technicians, account managers, and clients to trust and adopt AI-assisted workflows is where most implementations stall.
Open Questions We Debated
Not everything had an answer. These are the questions that generated the most discussion — and the most honest "I don't know yet" responses:
- Data quality and labeling at scale across tools and clients
- How to meter and price AI within managed services
- Vendor neutrality and lock-in risk as providers race to "platform-ize"
- Human-in-the-loop controls that balance speed, trust, and liability
- Compliance and evidence collection that stands up to audits
What I'm Still Processing
It's been almost a week and I'm still taking notes from the presentations and conversations. The global MSP market grew roughly 13% in 2025, and the growth is projected to accelerate through 2026. Meanwhile, 67% of phishing attacks now leverage some form of AI. The gap between opportunity and risk is widening, and MSPs are sitting right in the middle of it.
The next post in this series digs into what I think MSPs should be executing on today and thinking about for the future — especially around governance and the compliance landscape that's about to hit.
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