Panel Discussion: Building Confidence in AI-Driven Testing Decisions | TestMu 2025
In this TestMu 2025 panel discussion, industry leaders ๐๐ฌ๐๐ ๐๐๐๐ซ, Vice President of Product Management, Tricentis, ๐๐จ๐ญ๐ฒ ๐๐จ๐ฌ๐๐ง๐๐ฅ๐๐ญ๐ก, Chief Technology Officer, Katalon, ๐๐ฎ๐ฅ๐ฃ๐๐๐ญ ๐๐๐ ๐ฉ๐๐ฎ๐ฅ, Chief Product & Strategy, ACCELQ, and ๐๐๐๐ง ๐๐๐ณ๐ข๐ญ, Head of GitHub Next, GitHub, unpack one of the most critical questions in modern QA: Can we truly trust AI-driven testing decisions?
As AI reshapes the testing landscape, teams are increasingly depending on machine-generated insights, predictions, and automation for critical decisions. But with innovation comes the challenge of trust. How do we ensure AI systems are accurate, transparent, and fair? What guardrails, frameworks, and human-in-the-loop approaches can make AI a trusted partner instead of a black box?
Panelists share their perspectives on validating AI outputs, improving explainability, managing risks, and building trust across teams and stakeholders. From test prioritization and flakiness detection to autonomous test creation and maintenance, discover how organizations are closing the gap between innovation and reliability in intelligent testing.
๐๐๐ฌ๐ฌ๐ข๐จ๐ง ๐๐๐ฒ ๐๐๐ค๐๐๐ฐ๐๐ฒ๐ฌ:
Why is trust the cornerstone of AI adoption in testing?.
Practical strategies for validating and explaining AI-driven decisions.
Guardrails and human-in-the-loop approaches to reduce risks.
Real-world applications: test prioritization, flakiness detection, and autonomous test creation.
How leaders across Tricentis, Katalon, ACCELQ, and GitHub view the future of intelligent testing
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