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Gopinath Kathiresan Enhances Software Quality with Automation, AI

Quality Assurance

Business Honor
25 March, 2025

Gopinath Kathiresan reshapes software quality assurance through automation and AI-driven innovations for efficiency.

In the modern high-speed digital era, quality assurance (QA) is the central aspect of software development. As IT expenses globally continue to increase, with enterprise software totaling more than $1 trillion in 2024 alone, there can be no overstatement of the demand for software quality. For most big companies, QA and testing absorb much of their budget, putting reliability high on their agenda in the software they deliver.

Among the experts who have succeeded in the QA domain is Gopinath Kathiresan, a sixteen-plus years' experienced senior quality engineering manager specializing in software validation automation. His career has been focused on automating testing processes, bringing them to consistency and scalability through smart automation.

Kathiresan has been a key contributor to the evolution of parallel execution in software testing. This feature enables thousands of test cases to execute simultaneously, which reduces validation time considerably and speeds up releases of software. Through parallel execution, businesses are in a position to identify defects early in the development phase, time and cost saved. In addition, it also allows testing across a variety of devices, operating systems, and user scenarios to ensure software works perfectly across different platforms.

Scaling automation in large companies, however, is a complex issue. Kathiresan has led efforts to develop modular and reusable automation frameworks that integrate seamlessly into CI/CD pipelines. His scalable automation process ensures that it is a natural part of the development process, ensuring efficiency while fostering a culture of quality within organizations.

Though AI is continuing to change software testing, AI-based quality engineering is the future horizon, says Kathiresan. AI can detect defects early, auto-heal automation scripts, and risk-based testing with unparalleled precision and lower maintenance overhead. The road to the future of QA is now open: automation and AI will pave the way to more reliable, efficient, and scalable software development.