Wednesday, May 27, 2026; 10:00 AM EST
As AI moves from experimentation to mission‑critical and autonomous systems, the definition of quality is rapidly evolving. Traditional functional testing is no longer sufficient to ensure trust, fairness, transparency, and compliance in AI‑driven solutions.
This webinar, the second in our TechX series, examines how Quality Assurance must adapt for Responsible AI, shifting from conventional bug detection to addressing challenges such as hallucinations, bias, toxicity, and ethical risk. Industry experts will share how organizations can embed governance, explainability, and human oversight into AI testing strategies – without slowing innovation.
Why attend?
As AI adoption accelerates and regulatory scrutiny increases, organizations must rethink how they assure quality in intelligent systems. This session is designed for leaders seeking practical approaches to validating AI responsibly at scale.
- Understand how AI is redefining quality assurance
- Learn how to test for bias, hallucinations, and ethical risk
- Explore how automation and human‑in‑the‑loop approaches support Responsible AI
- Prepare QA teams for autonomous and agent‑driven AI systems
Key takeaways
In this session, you will learn:
- How modern QA goes beyond functional correctness to include ethics and trust
- Practical ways to measure hallucinations, toxicity, and bias as core quality metrics
- Insight into navigating global Responsible AI governance frameworks
- Strategies to operationalize transparency and explainability at scale
- How QA organizations can future‑proof themselves for autonomous and AI‑driven systems
Meet the panel
This webinar features industry experts from Qualitest and AssureSoft, bringing together deep experience in quality assurance, Responsible AI, and engineering leadership. The panel will share practical perspectives on building scalable, ethical, and compliant AI systems while supporting innovation across modern digital enterprises.
