AI has become an undeniable force in software development. But speed comes with a price. Recent projections estimate that the annual cost of poor software quality in the US has risen to over $2.41 trillion.1 As enterprises push AI-generated code into production, the potential for vulnerabilities, reliability issues, and compliance gaps only multiplies. Accelerated innovation can also increase liability if guardrails aren’t in place to manage the risks. This is the productivity paradox at work: the idea that chasing faster delivery can actually increase downstream costs and risks if quality isn’t built in.