AI in GxP: Moving Beyond Governance Theater to Operational Evidence
AI is rapidly moving into life-sciences operations, but GxP organizations need more than policies and governance frameworks. This session explored how risk-based assurance, operational evidence, and practical controls can make AI usable, governable, and defensible.
From Governance to Operational Evidence
AI adoption in regulated environments requires evidence that can withstand quality review and regulatory scrutiny. The discussion explored how organizations can establish traceability, human oversight, change control, performance monitoring, and inspection readiness for AI-enabled operations.
Evolving GxP Assurance for AI
The session connected lessons from 21 CFR Part 11, GxP, CSV, and CSA with today's AI and agentic systems. It explored Context of Use, risk-based thinking, and how Quality, IT, Business, and AI teams can build a practical operating model for responsible AI adoption.
Event at a Glance
115
Registrations
85
Unique Viewers
1668
Minutes Viewed
Featured Voices
Visionaries who led the conversation.
Nagesh Nama
Chief Executive Officer, xLM
Evjatar Cohen
Life Sciences Executive
50 Minutes ofPractical Insight
September 30, 2026
Full access session recording available on demand.
50 Minutes of Content
A practical discussion on AI in GxP, risk-based assurance, Context of Use, CSV/CSA evolution, operational evidence, human oversight, and inspection readiness.
This LinkedIn Live session explored how life-sciences organizations can move beyond governance frameworks and build practical, evidence-based assurance for AI in GxP environments. The discussion connected lessons from 21 CFR Part 11, GxP, CSV, and CSA with the realities of AI-enabled and agentic systems, highlighting the importance of risk-based thinking, operational evidence, traceability, human oversight, and regulatory confidence.
Detailed Event Overview
This LinkedIn Live session explored how life-sciences organizations can move beyond policies and governance frameworks to establish practical, risk-based assurance for AI in GxP environments. The discussion connected regulatory lessons with AI-enabled and agentic systems, focusing on operational evidence, human oversight, traceability, and inspection readiness.
AI Assurance in GxP
Explore how risk-based thinking and Context of Use can guide responsible AI adoption while maintaining regulatory confidence.
Evolving CSV & CSA for AI
Understand how traditional validation approaches can evolve to address AI-enabled and agentic systems, changing performance, and emerging risks.
Operational Evidence & Traceability
Discover what organizations need to demonstrate effective oversight through traceability, change control, performance monitoring, and documented evidence.
Practical AI Operating Models
Learn how Quality, IT, Business, and AI teams can collaborate to establish a practical operating model for AI that is usable, governable, and defensible.