As generative AI systems grow in scale and adoption, traditional software testing methods fall short due to LLMs’ non-deterministic behavior, hallucinations, and bias risks. Happiest Minds outlines a new QA framework emphasizing intent-based testing, bias and fairness checks, hallucination detection, adversarial testing, and human-in-the-loop validation. Key metrics include relevance, coherence, completeness, fluency, BLEU, ROUGE, METEOR, and BERTScore, supplemented with ethical safeguards. Regression testing, automation pipelines, and semantic validations are critical to ensure consistency across updates. Future trends highlight adaptive real-time testing, explainability, multi-modal validation, and regulatory compliance. An automation-first, strategic QA approach is essential to build trustworthy, high-quality GenAI solutions.

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