How to Validate AI-Enabled, Non-Product Software, Fast
Quality and regulatory teams are under increasing pressure to use AI to scale their impact and support faster, AI-assisted development. As non-product software is used in regulated environments, the tools must be appropriately controlled and validated.
The problem is that most validation approaches were designed for deterministic software. Teams are left unsure what actually needs to be validated, how to evaluate non-deterministic outputs, and what evidence will hold up in an audit. The result is manual reviews, screenshots, and gaps in evidence. This session gives QA/RA professionals a structured, risk-based framework for validating AI tools used within their organization, so you can maintain control and inspection readiness without slowing your team down.
What you'll learn
- How to scope validation for internally used AI, including defining intended use, risk classification, and acceptance criteria for non-product software
- How to use AI to generate audit-ready evidence, with traceability, human oversight, and repeatable testing approaches that replace screenshots and manual documentation
- How to use AI to accelerate validation workflows more broadly, enabling faster reviews and decision-making while maintaining compliance and control
Who should attend
Clips from this Webinar
Speakers
