Generative AI (GenAI) is transforming the landscape of software testing, offering innovative solutions to longstanding challenges. This session will delve into:

• The key obstacles testers face when developing GenAI solutions for testing, from data complexity to model accuracy.
• A structured framework for identifying opportunities to seamlessly integrate GenAI into the Software Testing Life Cycle (STLC), enhancing efficiency and scalability.
• Real-world examples demonstrating the groundbreaking potential of GenAI in testing, showcasing its ability to streamline processes and improve quality assurance practices.

Attendees will understand how GenAI can be used to not only address current testing challenges but also shape the future of software development by enabling smarter, more adaptive, and automated testing strategies. These takeaways will equip attendees with both theoretical knowledge and practical insights into the evolving role of GenAI in testing.

Explain the current trends i.e., AI/ML, GenAI and Agentic AI in Testing and Test automation. Usage of these solutions in the associates day to day work, limitations, and mitigation plans. this is very important in the present testers’ life.

• Benefits of AI/ML,
• Generative AI
• Different use cases in
• STLC/SDLC
• Efforts saving across life cycle
• Limitations and challenges
  Many more

Trends in Test Automation: Framework, Cloud, and Scripting” explores the latest advancements shaping the future of software testing. This session will delve into hybrid and AI-driven frameworks, cloud-based testing solutions for scalability and efficiency, and innovative scripting techniques like self-healing scripts and BDD. Attendees will gain insights into emerging technologies such as hyperautomation, shift-left testing, and AI-powered analytics, enabling them to stay ahead in the rapidly evolving test automation landscape.

Emerging Trends in Test Automation Frameworks:

• Adoption of hybrid frameworks combining methodologies like BDD, TDD, and data-driven testing for comprehensive test coverage and reduced maintenance efforts.
• AI-driven frameworks with self-healing capabilities to address dynamic UI changes and improve resiliency in automation testing.

Cloud-Based Testing Advantages:

• Enhanced scalability and flexibility for simulating diverse real-world scenarios without costly infrastructure investments.
• Faster testing cycles through parallel execution and seamless integration with CI/CD pipelines, enabling quicker time-to-market.

Innovative Scripting Techniques:

• Utilization of self-healing scripts powered by AI/ML to reduce script failures and maintenance overhead.
• Implementation of codeless automation tools to empower non-technical users and accelerate test script creation.

Future Directions in Test Automation:

• Integration of hyperautomation and shift-left testing practices to ensure early defect detection and improved efficiency throughout the SDLC.
• Increased collaboration between AI-driven automation tools and human expertise for strategic decision-making and user-centric testing approaches.

Traditionally, QA is considered to be the same as Quality Assurance which is the process of Testing a developed product. This leads to an increase in the number of release cycles because we tend to Test the product using our Test cases (Automated & Manual).

The role of a Quality Advocate in the Agile world is more to do with the overall responsibility of the Product’s quality. A Quality Advocate ensures that the team is building the product right by undertaking the various actions, early on in the development cycle. An eg. of this is making sure that the acceptance criteria are clearly defined, doing Test coverage at Unit/Integration level, etc.

This new definition of QA could help increase collaboration, reduce the traditional Dev vs QA issues, and ensure that the End product is of the highest quality.

New Age Quality processes
Faster Quality releases

Seasoned Technology Leader with extensive global experience in establishing engineering practices and enhancing team capabilities. Specializes in AI, Gen AI, AWS, modern tooling, shift-left transformations, and automation. Demonstrates proven expertise in conducting cost-benefit analyses to improve efficiency and profitability, while driving technical excellence and modernizing technology stacks.

He is the Director and APAC Quality Engineering Head at Northern Trust Corporation, leading digital assurance, automation, and chaos engineering. Previously, as a startup CTO, he built remo.cardia, an AI-driven remote cardiac monitoring platform. He also led IT transformation at Infosys, specializing in AI, IoT, DevOps, and RPA.

Experienced Technology Leader with a demonstrated history of building teams and leading transformations.
Design, development and implementation of customer facing and enterprise applications at scale. Experienced in cultivating Agile Behaviors, Innovation, and Development Practices in Engineering Teams.
Engineering professional with a Master’s degree focused in Computer Science.

He is a global AI innovation leader, shaping the future through emerging tech. With 16+ years across B2B and B2C sectors, he drives global innovation at _VOIS. An MBA from the University of London, he serves on HBR’s Advisory Council and is a LinkedIn Top AI voice.