Fireside chat: Exploring the Transformative Intersection of AI and Quality Engineering
The world of AI and Its Profound Impact on Quality Engineering
Diego Lo Guidice, Vice President and Principal Analyst at Forrester, and Venkatesh Iyengar, Vice President and Global Sales Head at Infosys, came together for an exclusive fireside chat. Moderated by Neelmani Verma, Industry Principal at Infosys, the conversation explored how the worlds of Artificial Intelligence and Quality Engineering (QE) are converging. Together, they unpack the opportunities, challenges, and real-world applications of AI in modern testing environments, offering strategic insights for engineering leaders and practitioners.
Diego Lo Guidice,
Vice President and Principal Analyst, Forrester
Venkatesh Iyengar,
Vice President and Global Sales Head, Infosys
Neelmani Verma,
Industry Principal, Infosys
Rewriting the Rules of QE with AI
The conversation begins by examining how AI is ushering in a new era for quality engineering. The speakers discuss the disruption of traditional testing methods and the integration of AI into everyday QE workflows. Drawing from the Forrester Wave Report, they highlight how leading service providers are achieving test automation rates of 70–80%. Infosys shares practical implementations, including the adoption of Microsoft Copilot for pair programming, Gen AI-powered infrastructure testing, and the use of domain-specific models to enhance accuracy and speed in test case creation.
Fireside Chat with Experts from Infosys and Forrester (Part 1)
Fireside Chat with Experts from Infosys and Forrester (Part 2)
Shaping What’s Next: The New era of QE
The discussion then shifts to the complexities of testing AI applications. Venky and Diego emphasize the importance of validating non-deterministic AI outputs before production and the need to automate manual testing to avoid delays. They explore how the role of quality engineers is evolving, with AI-augmented professionals leading the charge. The session concludes with a focus on AI Assurance (AiA), a holistic approach to ensuring the quality of AI-infused applications. This includes business assurance, benchmarking, red teaming, and responsible AI practices, encapsulated in the principle:
AiA = (BR)2 (Business + Benchmarking + Red teaming + Responsible AI)
