AI is transforming software development, but what about quality?
AI has redefined software development from the ground up. Across enterprise software teams, developers are using AI to generate code, complete features, fix issues, and move work forward faster than before.
But that speed comes at a cost. The faster you go, the more software gets deployed, and the harder it becomes to maintain confidence in quality. If everyone is moving at breakneck speed, how can any team be expected to test it all?
The testing bottleneck itself is not new. What has changed is the scale and speed of the challenge. As AI accelerates development across the software lifecycle, teams are producing more code, making more changes, and working within increasingly compressed timelines. That creates more software to validate and, naturally, more potential risk. Testing still depends heavily on manual coordination, fragmented tools, maintenance-heavy scripts, and human judgment embedded deep inside repetitive workflows. As development accelerates, an existing quality...
Copyright of this story solely belongs to diginomica.com. To see the full text click HERE
