AI Quality Assurance

Auto Added by WPeMatico

Testing Beyond Pass or Fail: A QA Engineer’s Lessons from IMDA’s LLM Testing Starter Kit at Spritle

Adversarial Testing, ai, AI (Artificial Intelligence), AI Application Testing, AI Governance, AI Product Quality, AI Quality Assurance, AI security, AI Security Testing, AI Testing, Artificial Intelligence, Bias Testing, Generative AI, Generative AI Testing, Hallucination Testing, IMDA LLM Testing Starter Kit, LLM Testing, Prompt injection testing, QA Best Practices, QA Engineering, Quality Assurance, Red Teaming, Responsible AI, Semantic Similarity Testing, Software Testing, Spritle Blog, SpritleSoftware

I’ve been in QA for a few years now. I know how testing works. You write a test case. You define the expected result. You run it. It either passes or fails. Simple. So when our team started working on an AI-powered feature, I thought, okay, same process. Different kind of input, but same idea. […]

Testing Beyond Pass or Fail: A QA Engineer’s Lessons from IMDA’s LLM Testing Starter Kit at Spritle Read More »

AI Risk & Compliance in 2026: Why QA Teams Must Lead the Shift

ai, AI (Artificial Intelligence), AI Auditability, AI Compliance 2026, AI Data Privacy, AI Governance, AI Governance & Compliance, AI Quality Assurance, AI Regulations, AI Risk Assessment, AI Risk Management, AI security, AI Testing, Artificial Intelligence, Continuous Compliance, Enterprise Technology, Ethical AI, EU AI Act, QA in AI, Quality Assurance, Responsible AI, Software Testing, Spritle Blog, SpritleSoftware

Artificial Intelligence is no longer a futuristic concept or an experimental capability. In 2026, AI has firmly embedded itself into core business operations—powering decisions in hiring, finance, healthcare, customer experience, and beyond. This shift brings a fundamental change: AI risk is now business risk. For Quality Engineering teams, especially QA leaders, this marks a turning

AI Risk & Compliance in 2026: Why QA Teams Must Lead the Shift Read More »