Automation’s Cost Curve: Why AI Usage Is Squeezing Profits Across IT Services

Margin pressure driven by AI adoption and automation is fundamentally altering the economic model for IT service delivery and software. Trend Micro’s disclosure that operating margins fell from 19% to 15% while cloud and AI token costs nearly doubled, despite strong AI security product sales, highlights how AI-related expenses grow in step with usage. This shift breaks from the historical software margin structure, where scaling incurred negligible incremental costs, and signals a new landscape in which AI service operation continuously consumes resources.

A significant development underscoring this trend is the $2 billion capital raise by Thrive Holdings at a $12 billion valuation, backed by SoftBank and OpenAI. Thrive’s business model centers on acquiring professional service firms—across IT and accounting—then reorganizing their operations around AI to reduce labor costs while maintaining service levels. According to Dave Sobel, this is not speculative, but reflects direct, substantial financial bets on the ability to remove a portion of service labor without customer disruption, with over 70 acquired service companies already undergoing this transition.

Additional evidence comes from channel segment data and shifts in partner economics. The Techaisle Global Channel Partner Survey found service providers under $10 million in revenue project 8.4% growth, while those above $500 million expect 16.8%. AI-related cloud spending continues to climb, with Gartner projecting $42 billion primarily moving from training to ongoing inference operations. The resulting cost structure affects everyone, from increased hardware component prices—such as memory for GPUs—and service desk automation tool adoption, to the fact that most organizations now monitor AI spend as a named line item but struggle to forecast it reliably. Only 11% of organizations can predict their AI bills, down from 15% the prior year.

For MSPs and IT leaders, these developments indicate rising operational complexity and increasing pricing competition. Automation drives down service delivery costs, but savings will quickly pass to clients as competitors implement similar solutions. Providers must quantify and communicate their impact on client outcomes, translating delivered value into client financial terms rather than relying solely on traditional metrics like licenses or labor hours. Failing to do so exposes providers to rapid commoditization and margin erosion, as clients grow more able to audit, benchmark, and bid out both cost savings and revenue enablement.

00:00 Two Billion Against Your Labor
04:10 Software Got a Cost of Goods
06:56 Get On Their Income Statement
10:29 Why Do We Care?

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