Per-User Pricing Under Strain: Rich Freeman Explains the AI Impact for MSP Operators

The central structural shift discussed is the repricing and erosion of the MSP business model as artificial intelligence (AI) and automation impact service delivery, pricing models, and margin structures. Analysis referenced recent polling and reporting, including the Omnia poll of 22,000 MSP partners and Service Leadership’s financial benchmarking. The integration of AI is reducing direct labor requirements and shifting traditional cost structures—posing both short-term increases in service margins for top-tier MSPs and complex, longer-term risks to the per-user pricing paradigm. Vendors, such as ConnectWise and RapidScale, are central to these developments, as their platforms, pricing models, and reporting mechanisms increasingly determine downstream MSP economics.

Supporting evidence from Service Leadership’s recent profitability report shows top quartile MSPs achieved a service multiple of wages (SMW) of 3.01—a level reached previously only during periods of wage collapse. The report also highlights that this margin growth is isolated: while the best-in-class are realizing sharply higher service margins, the median and bottom quartile remain flat. Reporting and analysis attributed this phenomenon to the earliest and most effective adopters of automation, particularly service desk automation aligned with AI, according to theories discussed with Service Leadership and ConnectWise representatives. However, there is a notable lack of definitive causation, as Service Leadership states the link between AI adoption and observed margin increases remains a working theory pending further data.

Additional developments reinforce the risk environment. Nearly 43% of surveyed MSPs are actively considering alternatives to per-user pricing, with another 17% acknowledging a need to change their pricing but lacking a defined direction. Industry analysis notes that consumption-based models—such as token-based or outcome-based pricing—present challenges, including unpredictable vendor cost structures and difficulties in measuring actual results achieved. Meanwhile, the risk of vendor-driven reenactment of break-fix economics and cost volatility increases, with some vendors already raising prices significantly to offset their own AI-related costs, pointing toward future margin compression downstream.

For MSPs and IT service providers, the operational implications are immediate and material. Providers face growing exposure to pricing and margin risk, especially as clients begin to recognize and challenge efficiency gains achieved by automation. Structurally, there is rising accountability for justifying service costs and delivering new forms of value outside commoditized support. Continued reliance on legacy pricing models without adaptation to AI-driven changes increases the risk of eroded margins or adverse contract negotiations. The most resilient operators will need to stabilize internal cost structures, reconsider client contracts, monitor vendor behavior closely, and prepare for increased customer scrutiny on both cost and deliverables.

Supported by:
Guardz https://www.guardz.com/
ScalePad https://scalepad.com/dave/