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News, Trends, and Insights for IT & Managed Services Providers
News, Trends, and Insights for IT & Managed Services Providers

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AI for MSPs: Vendors profit from activity, not resolved tickets

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Dave sobel, host of the business of tech podcast
Dave Sobel
Dave Sobel is a leading expert in the delivery of technology services with broad experience in both technology and business. He owned and operated a technology solution provider for over a decade, and worked for vendors leading community, marketing, product strategies, and M&A activities.

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Episode Description

A structural margin pressure is emerging as AI manufacturers bill MSPs for agent activity, while MSPs are paid by clients for resolved outcomes. Companies like ConnectWise and Super IT charge based on volumes of AI-driven attempts (agent activity, token usage), creating a financial disconnect—since MSP contracts tie revenue to tickets actually solved and kept closed, not the process steps taken.

ConnectWise introduced an RMM agent that automates diagnostics and ticket triage within its platform. Company-supplied data claims substantial efficiency gains: for one partner, 99% of over 7,000 tickets were evaluated in 30 days, but these metrics center on activity and hours “handed back,” not the net number of tickets resolved. Shield Technology Partners’ analysis of its Forge platform found that higher pass rates from advanced models like GPT-6 increased the per-ticket cost, and that calculations often did not include the human review and correction required by agents’ errors.

Further developments reinforce this trend. Super IT’s North America plans charge for AI agent activity levels, and Cloudera’s industry survey found only 27% of enterprises can accurately measure AI spend, with just 23% reporting net-positive value. Vendor-reported metrics prioritize activity and recurring revenue, not actual outcome delivery—leaving MSPs to bear the impact of unresolved tickets on their margins.

The operational consequence is that MSPs must track the actual cost per resolved ticket—including failed agent attempts and human verification—to accurately set pricing models and protect profitability. Not accounting for this hidden cost can erode margins and obscure the real impact of automation initiatives. Accurate governance relies on updating pricing models and operational processes to reflect the full scope of AI-related costs and investments.

00:00 The Agent Is in the Ticket
03:45 Billed for the Try, Not the Fix
06:40 What a Resolved Ticket Costs
11:14 Why Do We Care?

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