Business of Tech: Daily 10-Minute IT Services Insights · 2026-07-01 · 12 min
The dominant structural shift outlined is a transfer of liability and accountability for AI-generated errors from vendors to the entities deploying these systems - primarily MSPs and their clients. While vendors aggressively promote scalable AI tools and urge rapid adoption, the legal and operational burden of verifying and standing behind AI output falls on deployers, not on the tool providers. Recent court rulings and shifting buyer expectations are accelerating this transfer, fundamentally altering the MSP business model around AI services. Primary evidence for this shift comes from both industry behavior and legal precedent. Kaseya urged MSPs to quickly embrace AI services while revealing that only about 13% of providers are seeing significant revenue from AI, despite roughly half of clients requesting these solutions. Compounding the structural gap is a low conversion rate from proof-of-concept to production (only 20% success, per Kaseya), and high failure rates in AI-generated code - Forbes reported security and logic errors appear far more frequently in machine-produced output than in human code.
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