Why organizations are making trade-offs on software quality in the race to deliver faster
AI is shifting software quality from an engineering challenge to a leadership and governance priority.
Organizations are prioritizing speed over quality in software development, a trend accelerated by AI adoption. While AI has significantly boosted productivity, enabling teams to generate code faster and release updates in minutes, it has also outpaced their capacity to validate the resulting software. Consequently, 60% of teams knowingly deploy untested code, opting to accept certain risks rather than slowing down the delivery process.
This shift towards risk-based quality models necessitates new governance structures, real-time visibility into AI-generated code, and continuous validation throughout the development lifecycle. Rather than attempting to test every line of AI-generated code, organizations must focus on identifying and managing the risks that matter most, setting clear boundaries on acceptable risk levels.
By redefining quality in an AI-driven landscape, businesses can maintain a balance between rapid delivery and acceptable risk, ensuring software remains both functional and reliable.
Written by urgent.news from TechRadar's reporting — not their text. Machine-written — it may contain errors, so check the original before relying on it.
