From Bugs to Behaviors: The Shift in AI Quality
AI doesn’t just fail with bugs. It fails in silence, in bias, and in behavior. That’s why traditional QA won’t cut it anymore.
May 23, 2025
In his latest article, Sr. Manager of AI Testing Solutions, Hemraj Bedassee, highlights why AI systems require a new approach that goes beyond traditional pre-release testing. He explains how AI can fail in silent, contextual, and unpredictable ways, introducing risks such as hallucinations, ethical drift, and model degradation over time. To address these challenges, he outlines the importance of continuous behavioral monitoring, real-world signal analysis, and crowd-based red teaming to ensure AI systems remain reliable, aligned, and safe throughout their lifecycle.
