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GenAI in QA: Tiket's Approach to Evolving Quality Engineering | XP Series | LambdaTest
GenAI in QA: Tiket's Approach to Evolving Quality Engineering | XP Series | LambdaTest
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- Leading the Charge in Software Quality with Zero Bug Revolution
- Building a Test Automation Framework for TV Apps & Scaling at FX Digital
- Building High-Quality Teams: People, Process & Proof for QA Leadership
- Why Do We Have Bugs, and Why Do They Happen?
- GenAI in QA: Tiket's Approach to Evolving Quality Engineering
About The Video
Tune in to the latest episode of the LambdaTest Experience (XP) Series, featuring ๐๐ก๐ฎ๐ฉ๐๐ฌ๐ก ๐๐ข๐ญ๐ญ๐๐ฅ, AVP Software Quality Assurance at Tiket.com! In this insightful session, Bhupesh shares invaluable strategies for QA professionals to adapt and thrive in todayโs fast-paced software development environment. He explores how AI and automation can transform QA processes, reduce repetitive tasks, and enable teams to focus on delivering exceptional results.
Video Chapters
00:00 Welcome!
01:33 Guest Introduction
02:37 Overcoming Fear: Embracing AI in QA
06:58 Streamlining QA processes with AI
10:09 Structuring Teams for AI Integration
13:24 Challenges of Implementing AI in QA
21:46 Fostering A Culture of AI Innovation
25:40 Key Recommendations for QA Professionals
30:16 Conclusion
Key Topics Covered
AI in QA Transformation:
How AI tools are enhancing productivity and efficiency in QA processes.
Tackling repetitive tasks and enabling QA teams to focus on higher-value work.
Overcoming AI Fears in QA:
Strategies to shift the mindset of QA professionals from fearing AI to embracing it as a growth tool.
Encouraging upskilling and the adoption of AI as a complement to manual and automation testing.
Real-World Applications:
Use cases at Tiket.com where AI has streamlined test case generation, automation script creation, and code review.
Examples of integrating AI into various phases of QA workflows.
Team Structuring for AI Initiatives:
How QA teams at Tiket.com structured efforts to integrate AI without disrupting ongoing deliverables.
Importance of starting with pilot projects and gradually scaling initiatives.
Measuring ROI:
Methods to evaluate the return on investment (ROI) for AI integration, focusing on productivity improvements and time savings.
Building a Culture of AI Innovation:
Encouraging QA teams to identify and explore use cases for AI autonomously.
Tips for fostering curiosity and enthusiasm within QA teams for AI adoption.
The session also emphasizes the importance of seeing AI as a tool to drive innovation while maintaining a customer-centric approach in QA practices.
Related Blogs & Hubs
A Practical Guide on Improving QA Testing with Gen AI
Changing Role of Quality Engineering in the Age of AI
Leveraging AI for Enhanced Quality Assurance and Test Accuracy in Software
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