Today, as we celebrate Engineers Day, we honor Sir Mokshagundam Visvesvaraya, whose engineering marvels like the Krishna Raja Sagara dam transformed India’s infrastructure. His work exemplifies how engineers not only solve problems but design systems that impact generations. In the same spirit, Quality Engineers (QE) play a critical role in software applications today, ensuring quality by becoming clever toolsmiths, adapting to evolving GenAI-powered Test Methodologies in Agile and DevOps. Like Visvesvaraya, QE professionals must realize they are engineers at heart, and they must skillfully use advanced tools to deliver higher value, AI being no exception.
This Engineers Day, Let’s Set Our Minds for the Next Wave in Quality Engineering
The real transformation for Quality Engineers begins with a mindset shift. AI (the ML/DL and GenAI combo) is no longer just a new magic wand for maintainable test automation– it is an intelligent partner that augments human capabilities at every stage in the Continuous Test Lifecycle on the traditional Test Phases from Planning to Design to Execution to Reporting and Predictive Analytics. Quality Engineers must immediately learn to command and direct the new age AI-powered techniques, using their domain/testing expertise to guide AI in doing its best.
The best way to predict the future is to invent it. - Alan Kay (a true engineer of the GUI and the inspiring Smalltalk programming fame)
Really! The mindset we need is simple!
Learn to command AI, but always ensure that it is your domain expertise and strategic thinking guiding the test process. While AI handles automation, it is our (the Quality Engineer’s) deep understanding of Testing Principles, Test Design Techniques, Predictive Planning, Test Optimization, and the specific system nuances of the AUT that unfolds the course of Quality and value to the customer.
Why Embrace AI as a Quality Engineer?
Let us hallucinate a bit and cut towards mid or late 2025… The Quality Engineer has become the strategist, guiding AI through an intricate web of automation and quality checks across all phases of software delivery. Let me manifest what that future state might look like for a grown-level Test Lead or an AI-powered QE professional.
AI + The Human-in-the-Loop QE Mandate
- Engineers refine AI-suggested test conditions, ensuring domain-specific business cases are addressed.
- Regression cycles are optimized by AI in partnership with the Test Analysts/Leads, suggesting test coverage based on historical data and upcoming release plans.
- QE professionals collaborate with AI to make lateral thinking suggestions, ensuring both Functional and Non-functional aspects are covered.
- Test Data generation becomes AI-enhanced, but domain expertise directs it toward realistic business scenarios, taking Synthetic Test Data to productive heights.
AI + The Human-on-the-Loop QE Leadership
- Quality Engineers supervise AI-driven test aspects of CI/CD pipelines, only stepping in for strategic decisions, while AI handles the execution.
- Product Owners and Lead QE professionals use AI-generated insights to drive high-level decision-making, focusing on long-term risks and optimization.
- Automation frameworks continuously evolve, with AI learning from historical data and creating future-proof test scripts on the fly (with minimal litmus checks from Test Architects and Tool Experts).
- Human QE professionals spend more time in Design Thinking, leaving AI to handle repetitive tasks and large-scale testing.
AI + The Ultimate Autonomous QE Beds
- Engineers guide AI to scan User Stories, extracting conditions and crafting test cases.
- AI-driven test automation scripts are created dynamically based on release-specific workflows.
- Automated beefed-up bug reports with detailed logs, user flows, and root cause suggestions streamline development handoffs.
- AI predicts Non-functional issues early, allowing QE folks to adjust Performance and Security tests before coding even starts.
- Bots that clone the behavior of end users do the User Acceptance Tests.
- And I will leave the rest to your imagination. 🙂
Next?
+ AI suggests lateral strategies for test design, exploring cross-functional applications that Quality Engineers can experiment with.
+ Test optimization and new heuristics become a collaboration between the QE professional’s experience and AI’s vast data insights.
+ By mid to late 2025, the QE role is no longer about manual intervention– it’s about designing smarter, faster, and more adaptive quality solutions in partnership with AI (ML, DL, and GenAI).
Again, as we celebrate Engineers Day, we are reminded that engineers are the architects of tomorrow’s solutions. Sir Visvesvaraya designed systems that transformed a nation, and today, Quality Engineers are transforming the digital landscape. AI and GenAI are simply new tools in the toolbox. Get high on creativity and problem-solving. The future of QE embracing AI has started roughly two years ago! We are feeling it just in the last few months. 🙂
Questions? Comments? Welcome.
Discuss and spread the word, dear Quality Engineer!
