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Generative AI
Cloud
Testing
Artificial intelligence
Security
October 30, 2024
This year, our World Quality Report 2024-25 in conjunction with Capgemini and our partner OpenText, dives deep into the rising importance of Quality Engineering (QE) across industries, exploring how businesses are adapting to the demands of an increasingly digital world. You’ll discover some eye-opening trends that every quality professional should be aware of.
For instance, did you know that nearly half of organizations are now integrating quality engineers directly into their agile teams? This shift not only enhances collaboration but drives innovation by creating a culture where quality is a shared responsibility. What’s even more exciting is that nearly a third of companies are already tapping into generative AI for QE tasks like test reporting and data generation. And it’s not just a buzzword—Gen AI is quickly becoming a game-changer, helping teams work faster and more accurately in their daily operations.
WQR 2024 also emphasizes the need to link Quality Engineering metrics with business goals. With nearly two-thirds of organizations recognizing data quality as critical, harnessing data-driven decisions is key to staying competitive in today’s fast-paced market.
Global Leader Quality Engineering & Testing, Sogeti
Sustainability is another hot topic, and while many companies acknowledge its importance, they often struggle to effectively implement and track sustainable IT initiatives. The report highlights how robust quality management frameworks can help overcome these hurdles and ensure sustainable practices.
The 2024 World Quality Report provides an in-depth analysis of current trends and their impact on the future of quality .From exploring the impact of AI to providing actionable insights on sustainability, it’s a must-read for anyone dedicated to achieving excellence in Quality Engineering.
16th edition
The World Quality Report 16th edition highlights exciting new futures powered by technology advancements like Gen AI, automation, and human-in-the-loop systems.
Training AI models like GANs, LLMs, and SLMs needs vast, high-quality data, but privacy concerns, regulations, and limited access make real data scarce. Could synthetic data effectively replace sensitive information in AI training?
Imagine a world where legal professionals are liberated from the mundane tasks of sifting through mountains of documents and can instead focus on crafting strategies that drive justice and innovation.
Generative AI’s impact on future jobs often sparks predictions of technology overtaking human roles in many areas. However, to optimize AI’s deployment, the human role and its interaction with technology remain crucial—especially in software quality engineering.
