If AI coding is lowering your code quality, you're not managing quality right

The article argues that AI-assisted coding does not have to degrade code quality if IT organizations adopt a layered quality-management model: clearer requirements, high unit-test coverage, manual validation, extensive end-to-end testing, AI-driven code quality checks, and targeted human review. For CIOs and technology leaders, the strategic implication is that AI can raise software delivery throughput 2-3x while maintaining or even improving reliability, but only if teams redesign engineering processes, quality gates, and review workflows rather than simply letting AI-generated code flow unchecked into production.