AI Productivity or AI Debt? What Leaders Are Missing
AI adoption in engineering is nearly universal. According to the MIT Nandanda Center, 97 percent of technology leaders have integrated AI into backend systems. Yet two thirds of those organizations report no meaningful headcount savings. Instead, they are accumulating a technical debt burden estimated at 61 billion workdays to resolve. This is not a tooling problem. It is a governance problem. The Hidden Cost of AI-Generated Code Research from Stanford’s Digital Economy Lab shows that AI-generated code is typically simpler, more repetitive, and less structurally diverse than human-written code. Over time, this produces large volumes of code that technically functions but lacks architectural clarity, intent, and long-term maintainability. Traditional technical debt can be prioritized and refactored. AI-generated debt is harder to unwind because there is often no clear rationale behind design decisions. The result is software that works today but becomes increasingly fragile and expe...