Sponsored Webcast: How to Validate AI-Enabled, Non-Product Software (On Demand) (1 CE point)
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.
Learning Objectives
- 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?
- Quality and regulatory professionals responsible for validation strategy, evidence, and inspection readiness
- Teams adopting AI in GxP environments who need a clear, defensible validation approach
- Executives looking to accelerate product innovation with AI
Audience Learning Level
Intermediate: Content is designed based upon the assumption that individuals have basic knowledge of the topic(s) and/or demonstrated competence related to the topic(s). Higher-level concepts are introduced during lectures; exercises requiring synthesis and/or application of concepts are incorporated into the activity.
Speakers
James Plaschke
