Why organizations are making trade-offs on software quality in the race to deliver faster
When we wrote about the “AI speed trap” in the software development process for TechRadar Pro a year ago, the central concern was whether faster delivery would come at the expense of quality. A year on, what we’re seeing are actually deeper issues around trust, governance and organizational alignment.
Head of UK & Ireland at Tricentis.
As AI-generated code becomes more routine and ecosystems become more complex, the challenge is no longer simply keeping pace with delivery. It is deciding who owns quality, how much risk is acceptable, and what confidence looks like in an AI-enabled environment.
AI has become firmly embedded across the software development lifecycle, accelerating delivery at an unprecedented rate. But the real story is no longer just speed. Organizations are now being forced to make more explicit decisions about where quality ends and acceptable risk begins, and to reconcile trade-offs around testing, trust and accountability.
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