- AI’s transformation of QA is not as straightforward as expected.
- Gokul believes that while AI tools have dramatically transformed QA by increasing efficiency, especially in repetitive tasks like regression testing and bug detection, they still have limitations.
- The true challenge lies in finding the right balance between automated testing and human oversight.
- Despite its advantages, Gokul warns that AI is far from being a perfect solution in QA.
OUR TAKE
AI’s role in QA sure is exciting, it’s like having a super-fast robot assistant that can do the mundane stuff, but still needs you to check the finer details. Remember those days when Google Translate first came out? It was impressive, but still struggled with nuances and cultural context. Same goes for AI in QA. We’ve seen how AI algorithms can perpetuate biases in hiring or loan approvals. So, when it comes to software that affects our daily lives, having that human eye to catch those subtle flaws and ensure fairness is crucial. It’s a balance act, and one that ensures we get the best of both worlds: efficiency and empathy.
–Miurio huang, BTW reporter
AI is revolutionising every industry, and Quality Assurance (QA) is no exception. Recently, BTW Media had the opportunity to conduct an exclusive interview with Gokul Choudhary, senior QA engineer from Tech Mahindra.
Gokul, a seasoned QA engineer, brings over a decade of experience in software testing for mobile, desktop, and web applications, with a specialisation in sectors such as e-commerce, healthcare, and banking. In recent years, he has focused on AI-driven applications, gaining expertise at Meta, where he tested smartwatches and smart glasses to ensure precise AI command recognition and response. His diverse background uniquely positions him to navigate the complexities of QA in the evolving AI landscape.
Gokul explains that AI’s transformation of QA is not as straightforward as expected. While AI and machine learning have automated many testing processes, the need for human oversight remains essential.
AI enhances, but doesn’t replace, human intuition in QA
Gokul believes that while AI tools have dramatically transformed QA by increasing efficiency, especially in repetitive tasks like regression testing and bug detection, they still have limitations. “AI can identify issues faster than any human, but it lacks the intuition to understand context and nuance,” he argues, pointing out that AI operates strictly within the confines of its training data. In complex or unforeseen situations, human testers remain indispensable for interpreting ambiguous outcomes, identifying subtle flaws or edge cases, and ensuring that the software performs according to real-world user behaviors and expectations. Human intuition, experience, and adaptability are qualities that AI currently cannot replicate.
“AI can identify issues faster than any human, but it lacks the intuition to understand context and nuance.”
Gokul Choudhary
Balancing automation with human insight in software testing
According to Gokul, the true challenge lies in finding the right balance between automated testing and human oversight. He notes that many organisations rush to adopt full AI automation, only to discover gaps in areas where AI’s capabilities fall short.
For example, AI-driven testing tools may struggle to accurately interpret creative design elements or fail to account for culturally specific user behavior, leading to a misalignment with user needs. “That’s where the human touch becomes invaluable,” he stresses. Gokul suggests that effective QA strategies combine the speed and consistency of AI with the critical thinking and contextual understanding that only human testers can provide. This balance is crucial for maintaining both technical quality and user satisfaction.
“AI-driven testing tools may struggle to accurately interpret creative design elements or fail to account for culturally specific user behavior, leading to a misalignment with user needs. “That’s where the human touch becomes invaluable.”
Gokul Choudhary
Why AI-driven testing still needs the human touch
Despite its advantages, Gokul warns that AI is far from being a perfect solution in QA. “There’s a tendency to view AI as a panacea, but it’s just another tool—albeit a powerful one,” he cautions.
He highlights that AI systems are vulnerable to issues like algorithmic bias, where the AI could make unfair or unethical decisions based on skewed data. Moreover, AI lacks the ability to exercise empathy, ethical judgment, and moral reasoning, which are essential when evaluating how AI-driven systems impact diverse end users. Human testers provide the necessary oversight to catch these biases and ensure that AI applications function fairly and ethically across different contexts.
“There’s a tendency to view AI as a panacea, but it’s just another tool—albeit a powerful one.”
Gokul Choudhary
Navigating the limitations of AI in QA
Gokul also emphasises that AI’s role in QA is still in its early stages of development. “AI’s role in QA will continue to grow, but it will always need humans to guide it, especially as new, unpredictable challenges emerge,” he predicts. He envisions a future where AI is used to handle repetitive, mundane tasks while human testers focus on more complex and nuanced decision-making. This collaborative approach between AI and human testers will likely be the standard, ensuring that software not only meets technical specifications but also aligns with ethical standards and user needs in a rapidly evolving technological landscape.
By combining AI’s efficiency with human oversight, Gokul advocates for a hybrid model that leverages the strengths of both.
“AI’s role in QA will continue to grow, but it will always need humans to guide it, especially as new, unpredictable challenges emerge.”
Gokul Choudhary
Personal opinion
Gokul’s perspective offers a refreshing take on the future of AI in QA. It is not about replacing humans with machines but about enhancing human capabilities through technology. As he puts it, “AI is an incredible ally, but the human mind is irreplaceable.” His insights serve as a reminder that even in a tech-driven world, the human touch remains vital in navigating the complexities of software quality and user satisfaction.
