Why Enterprises Must Look Beyond Code Volume to Measure AI Coding Agent ROI

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Enterprises adopting AI coding agents often default to measuring success by the volume of code generated, but experts argue this metric can be misleading. Higher code output can actually increase technical debt, review burden, and security risks if not matched by improvements across the full software delivery pipeline. Meaningful ROI should instead be assessed across delivery speed, software quality, incident rates, and business outcomes. A team may see 30% faster feature development yet still experience longer release cycles if bugs and rework increase downstream. The core question enterprises should ask is not how much code AI produced, but how much waste was eliminated and how much additional business value was delivered.

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