Redefining Quality for AI-Powered Systems

Evgeny Tkachenko

13:15 - 14:00 CEST, Tuesday 16th June

Are you ready to rethink what quality means in the age of AI?

As artificial intelligence becomes embedded in everything from customer support to healthcare, finance, and product recommendations, the expectations for software quality are rapidly changing. Traditional testing methods fall short when applied to AI systems, which are probabilistic, data-driven, and often opaque.

This session is designed for Quality Engineers and Managers who are ready to take the lead in shaping how we ensure the reliability, fairness, and safety of AI-powered applications.

Drawing on real-world examples and nearly 20 years of hands-on experience, I will walk through the strategies, frameworks, and tools needed to evolve your QE practice for the AI era.

We’ll examine the unique testing challenges posed by machine learning and generative AI models, including data drift, model bias, lack of explainability, and the difficulty of defining pass/fail outcomes.

You will learn how to test critical quality attributes like accuracy, robustness, interpretability, and fairness, and how to embed these checks into your delivery pipelines.

Whether your team is already working with AI or just starting to explore its possibilities, you’ll leave with practical insights and actionable steps to future-proof your testing strategies and processes.

Key topics include:

* How to validate and verify AI models at every stage of development and deployment

* Strategies for detecting and addressing bias, drift, and unpredictable model behavior

* Tools and frameworks to enhance testing for NLP, image recognition, and generative AI

* How to collaborate across roles to build AI systems that are not only performant but also ethical and compliant

You will also receive a curated appendix of practical tools for AI testing that you can start using immediately.

This talk is not just about adapting to change. It’s about seizing the opportunity to lead. Join us and gain the confidence to evolve your role, guide your team, and help your organization deliver AI that works — responsibly and reliably.

What you will learn

Learn practical methods to test AI systems for accuracy, fairness, robustness, and interpretability
Discover tools and frameworks to monitor, validate, and govern AI behavior across the ML lifecycle
Gain a roadmap to evolve your quality engineering role and processes for AI-powered applications

Session Details

Intermediate
45mins
Includes 15min Q&A
Testing the reliability, fairness, and safety of AI models

Buy Conference Ticket

Check out this video from Evgeny Tkachenko to hear more about his talk on Redefining Quality for AI-Powered Systems.

We look forward to welcoming you to EuroSTAR 2026.

Session Speakers

Evgeny Tkachenko

ServiceTrade, USA

Evgeny Tkachenko is a Quality Engineering Program Lead at ServiceTrade, with nearly 20 years of leadership experience across test automation, release management, and quality strategy.

He has held senior roles at EPAM Systems, Wayfair, and Amazon, and is the author of two industry-acclaimed books: Navigating Quality Engineering in the AI Era and Testing AI-Powered Applications.

A regular speaker at global conferences and a contributor to international publications, Evgeny is known for delivering actionable insights that help teams build smarter, safer, and more trustworthy software. His work champions the evolving role of quality professionals in the AI era.

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