Tag: QA

A recent email from ASTQB warned testers that to survive in an AI-driven world, they’ll need “broad testing knowledge, not just basic skills.” The advice isn’t wrong—but it misses the bigger picture. The real disruption is already here, and it’s moving faster than most realize. AI systems like AI Script Generation (AISG) and GENI are already generating, executing, and

When artificial intelligence enters the conversation around software testing, a common fear surfaces: Will AI take my job? For QA professionals, who have long been on the frontlines of quality, the rise of AI-driven platforms can feel both exciting and intimidating. The truth is this: AI won’t replace your QA team—it will empower them. Far

SPEED is everything in the fast-paced digital world. Enterprises can’t afford multi-week QA cycles that slow releases, frustrate customers, and hold back innovation. Yet, for many organizations, that’s still the reality. Traditional testing—laden with brittle scripts, manual updates, and siloed teams—creates bottlenecks that delay software delivery. Enter AI testing. With Appvance IQ (AIQ), quality assurance

In today’s fast-paced software world, speed isn’t optional—it’s a competitive necessity. But for many organizations, quality assurance (QA) remains the bottleneck. Traditional testing cycles can take weeks, bogged down by manual script writing, test maintenance, and slow execution times. Enter AI-first testing—and specifically, Appvance IQ (AIQ)—a platform designed to compress QA cycles from weeks to

Agile methodologies have revolutionized how teams approach project management and product delivery. Agile emphasizes flexibility, collaboration, and customer satisfaction, necessitating a shift in the traditional roles within development teams. One such role that has evolved significantly is QA. The role of QA in Agile environments is crucial for enhancing product quality through early and continuous

In a shocking display of incompetence, millions of computers around the world simultaneously became unusable, all thanks to a bug that led to the dreaded “Blue Screen of Death.” CrowdStrike, a US cybersecurity company based in Texas, offers ransomware, malware, and internet security products primarily to businesses and large organizations. But on Friday, July 19,

Software test automation is crucial to quality assurance (QA). Traditionally, the cost of creating and maintaining test automation scripts was a significant investment, with estimates reaching $1,000 per script. However, the winds of change have swept in with the advent of generative AI (GenAI), rendering the concept of test maintenance obsolete. In the bygone era

The emergence of GenAI driven testing has redefined the role and expectations of Directors of Software Quality Assurance. As this technology continues to evolve, it becomes imperative for organizations to rethink the skills and responsibilities required for this critical position. Thus, this post specifies six requirements for Directors of Software QA in the age of

Software QA is undergoing a sea change due to generative AI-driven testing. That begs the question of how to practice responsible AI in software testing. Hence, this post provides eleven considerations for responsible testing when using generative AI (GenAI). First, let’s note that responsible AI is an emerging area of AI governance covering ethics, morals

This is the second #BestPractices blog post of a series, by Kevin Parker. Introduction Developers and quality assurance teams must collaborate to succeed in today’s fast-paced software development industry. By working together from the beginning, Dev and QA can incorporate best practices that make test automation easy and efficient, thereby accelerating release cycles and improving