This session will delve into how organizations can leverage cutting-edge technologies and methodologies to build scalable, intelligent, and efficient QA ecosystems that align with modern software delivery practices.

In today’s generative world of intelligence, we need to be cognizant of the fact that the tools and techniques related to software testing have undergone a major transformation. In this proposed session, I talk about the power of GEN AI tools in context of testing and how these can be leveraged to enhance the Value of Testing. During the proposed session, I will use the power of RISE model (developed by Emily Wray) and use this to help it reimagine and reconstruct our Testing Value Equation.
RISE is a famous model which has 4 critical elements of RISE (R- Reflect | I-Inquire, S-Suggest, E-Elevate) to it, and in the proposed topic we will leverage them to enhance value of our Testing.

• Participants will get a clear understanding of the neo Testing based approach needed for a successful Digital Transformation initiative
• Participants will realize the importance of Faster Time to Market and its impact on Business using the Power of GEN AI for testing
• Get an understanding of Testing Strategy to be deployed for Digital Transformation initiatives

Despite making significant investments in test automation, many organizations find it difficult to reap the true rewards. Instead of facilitating agility, tests become flaky, slow, and a bottleneck. Addressing these issues requires leadership, not only from a technical standpoint but also by influencing strategy, culture, and mindset.
The main topics of this presentation will be the reasons why test automation initiatives frequently fall short in Agile settings and the actions that leaders (such as test managers, agile coaches, and quality champions) can do to improve the situation.

• For Leaders: Test automation facilitates agility rather than acting as a stand-alone function.
• For testers: Pay attention to test approach rather than scripting alone.
• For Agile teams should transition from an emphasis with automated coverage to a constant quality focus.
• For Everyone: Don’t simply measure automation statistics; measure quality outcomes.

Most teams believe automated testing makes DevOps faster, but in reality, poorly planned automation can slow everything down. In this presentation, we will explore the biggest mistakes QA teams make and how to avoid them. I will tell how to choose the right tests, use AI to speed up testing, and build a reliable test strategy that works with CI/CD. I will share real-world examples and practical steps to make automated testing a true DevOps enabler. The presentation will enable you to rethink test automation and make it a driver of speed and quality in software development.

• Automating everything is a mistake—test automation should be strategic. Prioritize unit and API tests over slow, flaky UI tests and integrate automation smartly into CI/CD pipelines.
• AI-powered testing and smart test selection can reduce execution time. Instead of running all tests, leverage AI to predict which tests need to run, cutting regression cycles by up to significant percentage.
• DevOps testing isn’t just about execution—it’s about stability and confidence. Use techniques like contract testing, chaos testing, and parallel execution to ensure faster, reliable releases without bottlenecks.

As Quality Engineers, we’re all about making sure things are done right—from how a product is made to how it performs when it reaches the customer. We keep a close eye on processes, catch issues early, dig into root causes when things go wrong, and help teams fix problems so they don’t come back. We work closely with developers and product managers right from the design phase, focusing on building quality into the product from the start. By collaborating early, we aim to prevent issues before they happen and concentrate on delivering a bug-free experience. We also team up with other departments to ensure everyone’s on the same page about what quality really means and how to deliver it. Whether it’s refining a process, analyzing data, or preparing for audits, our goal is always to build better, more reliable outcomes—and to make sure customers get exactly what they expect, if not more.

Most of us think testing is only about finding bugs and make sure application works from end user perspective.

Following are the things Quality Engineering consists of

• Shift Left Approach
• Design Reviews
• Design Discussions
• Acceptance Criteria Agreement
• Test scenario writing and getting it review
• Automation
• Work with SRE, DEVOPS counterparts
• Think about AI

• Lets change / update our perspective towards testing

• How testing teams should operate in future

This presentation aims to shed light on the transformative journey of AI-based testing and guide organizations in fostering a culture that embraces this change. It will provide a strategic roadmap for integrating AI into testing processes, leveraging practical experience. The presentation will initially tackle the cultural challenges organizations often encounter when integrating AI into testing processes, like resistance to change, technical expertise gaps, and data privacy issues. It will offer insights into promoting an innovative and adaptable culture to overcome these hurdles. The focus will then transit to practical strategies for capitalizing on AI in testing processes. Expert guidance will be provided on building a robust AI-based testing framework, effectively training teams to use AI tools, managing data for AI testing, and adhering to ethical AI testing guidelines. The Presentation will end with a discourse on the potential benefits of adopting AI-based testing, such as improved testing speed, enhanced precision, and cost reduction. It will underscore how a culture of AI-based testing can spur innovation, boost product quality, and give organizations a competitive advantage in the digital era.

Transformative Journey of AI-Based Testing:
Guidance on incorporating AI into testing processes.
Addressing resistance to change.
Strategies to foster an adaptable and innovative organizational culture.
Building a robust AI-based testing framework.

Neeta Sonawane is a seasoned IT leader with 19+ years of expertise in engineering, project/program management, AWS/GCP cloud, and team leadership. She excels in automation, testing, stakeholder collaboration, Agile/SAFe methodologies, and business transformation. A skilled speaker, she has successfully led technical and managerial initiatives, ensuring seamless project execution.

As a Director at Fidelity Investments, I bring 19+ years of expertise in product management, leadership, and client relations. Passionate about innovation, I excel in software development, testing, and automation. With ISTQB, NCFM, and ScrumMaster® certifications, I drive efficiency and reliability while adapting to evolving industry needs.

Seasoned QEA Technology leader with 20+ years of experience in emerging tech, AI/Gen AI capability building, and lifecycle automation. Led 50+ innovations, large transformations, and $5M+ in benefits. Expertise in blockchain, RPA, cloud assurance. Strong people leader, conference speaker, and transformation champion.

Smita Degolia is SVP of Wealth Management at BNY Mellon, combining financial expertise with tech skills. A Certified ScrumMaster and Enneagram Practitioner, she excels in client service, agile leadership, and data-driven solutions, backed by a Master’s in Computer Management from the University of Pune.