Bottom line: AI coding infrastructure costs could compete with individual developer salaries by 2028 if organizations fail to actively manage consumption and billing.
According to an analysis, costs for AI-assisted software development are expected to reach or exceed the annual salary of an average developer by 2028. Drivers include undisciplined AI usage and opaque billing models from AI providers.
Several factors are making AI-based software development increasingly expensive for corporate budgets. Opaque billing models from AI providers make it difficult to track and forecast actual operating costs. At the same time, many organizations lack governance structures: AI tools are deployed without clear usage guidelines or cost monitoring.
For CTOs, this represents a planning and control challenge. While individual developers use AI assistants like Claude for code generation, there are no organization-wide policies on responsible use. This leads to uncontrolled growth in API calls, unnecessary requests, and consequently cost explosions that can exceed traditional personnel budgets.
The challenge lies in striking a balance: on one hand, teams should benefit from AI productivity gains; on the other hand, transparency and cost caps are needed. This requires better monitoring of model calls and API consumption at the technical level, as well as defined standards for AI tool deployment at the organizational level.
Source: www.golem.de · Published June 25, 2026
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