• There is great pressure on organizations to do more with less and still deliver a quality product with hopefully no critical bugs. Every organization is tasked with delivering functionality and at the same time digital transformation, modernization, DevOps, performance, security and compliance requirements are only increasing. Traditional test approaches and test automation are no longer sufficient.

As AI agents and automated pipelines become mainstream and adopted widely, it is clear that AI will play an increasing role in all aspects of software engineering including quality assurance and testing. AI is redefining all aspects of quality engineering, and in this keynote, I will explore how great quality engineers and AI agents will partner together to greatly enhance the quality of the output of a high performing software engineering team. Taking the example of a complex, regulated, highly secure enterprise software platform built using microservices running on containers, handling synchronous and asynchronous events and many API endpoints – we will see how quality engineers and AI agents work together on complex issues of functional and non-functional requirements.

• Great leaders focus on outcomes.
• Automation and AI agents are great force multipliers.
• It is still true that good QA testers matter to the success of any project/team.
• People matter, simple and repeatable processes along with ever increasing fidelity of tools such as AI agents can greatly improve the outcomes.

• Dismantling Test Data Management: Debunking Myths, revealing facts, and Scoring parameters.
• Unlocking the Secrets of Test Data Management: Architecture, Approach, and Best Practices.
• Test Data Management: Understanding Complexities and Challenges.
• From Excellence to Negligence: Real-World Examples of Test Data Management Done Right and Wrong.

• Common misconceptions in Test Data Management, replaced with facts and insights to guide your approach.
• Architecture behind effective, secure and compliant Test Data Management
• Various TDM complexities and challenges.
• What distinguishes excellent TDM practices through real-world examples.

We will do an industry survey of Performance Test Tools and compare the results of using top 6 most popular against publicly available benchmark sites. The Tools will be compared using the following criteria such as

• Type (Commercial/ Cloud Subscription/ Open Source)
• Primary Language
• Ease of Use
• Protocol Support
• CI/CD Integration
• Scalability
• Test Result Visualization
• Scripting Flexibility
• Cloud/Distributed
• Execution
• Community Support

As digital transformation accelerates, testing must evolve faster than ever. This session reveals how AI, analytics, and intelligent automation are redefining quality assurance from dynamic test generation to self-healing frameworks and predictive bug detection.

The terms “GenAI” and “AI” are inescapable! We hear these terms daily while also seeing updates on what is new and how the latest version of a model will revolutionize everything! It’s a lot to take in and overwhelming when you’re looking for a place to start.

The intention of my topic is to cut through the noise and help software testers find practical applications for AI. We will talk about how to use GenAI to our advantage by increasing our efficiency while maintaining quality. The goal is to give attendees practical knowledge they can build on and apply when they get back to their project.

• How to practically apply GenAI to common software testing tasks
• How to maintain quality while increasing efficiency
• Guidelines on where to start and how to upskill

In this talk, Adam Sandman will introduce the latest trends in AI, including GenAI and AgenticAI. He will then discuss how AI is changing the software delivery lifecycle, and how QA needs to change to adapt. Finally, he will discuss ways to ensure safety and quality of the applications being delivered.

Visionary Software Engineering Director with 20+ years’ experience in AI-driven automation, cloud-native transformation, and modernizing financial services technology. Expert in credit platforms, real-time decisioning, and regulatory compliance. Passionate about scalable architecture, operational efficiency, and empowering organizations through innovative, cost-effective tech solutions.

As PwC’s Cloud Engineering Data & AI Leader, I drive cloud and Gen AI transformation—leading innovative solutions like RAG, Agentic frameworks, and Conversational AI. I guide high-performing teams, shape digital strategies, and scale startups through agile cloud solutions, quality engineering, and impactful go-to-market execution.

Senior Engineering Leader with 20+ years in IT, specializing in software development, digital transformation, and product management. Expert in leading high-performance teams, agile delivery, and complex system implementations. Holds multiple certifications, with deep expertise in Guidewire, Salesforce, and SAFe frameworks.

Director of Test Engineering at Glassdoor. Accomplished quality and engineering leader with a strong track record of building high-impact teams, driving innovation, and delivering measurable results that elevate product excellence and organizational performance.

Experience people leader and technology lead in a fast paced high impact environment supporting millions of customers. I believe that with the right people on the team we can do anything. My job is to find those people and clear the road for them to be their best. Skilled in IT Strategy, Data Center, Amazon Web Services (AWS), and Troubleshooting. Strong professional with a Bachelor of Science focused in Information Technology; Information Technology; Computer Science from America Intercontinental University.