AI Is Writing Your Code. Who's Governing It?
AI-accelerated development has moved from experimental to operational.
But for today's technology leaders, it introduces an entirely new class of Day Zero risk.
From LLM-generated polymorphic malware to poisoned open-source models entering enterprise pipelines, the software supply chain is evolving faster than traditional security can keep up.
When AI agents can test and deploy code autonomously - perimeter security is no longer enough.
A New Operating Model: MLGovOps
The industry is shifting toward MLGovOps - where security, governance, and compliance are embedded directly into the software supply chain.
Not as an afterthought. But by design.
Join a select group of peers for an intimate, off-the-record discussion on how to operationalize this shift.
What You'll Explore
This conversation is designed to unpack how technology leaders are adapting to autonomous development and AI-driven risk.
The Rise of the Autonomous Supply Chain
How do you secure identity when AI agents - no humans - are building software?
What does trust look like with minimal human oversight?
Curation vs Chaos in AI Model Intake
Preventing model poisoning, prompt injection and malicious dependencies
The role of trusted AI catalogs in reducing systemic risk
DevGovOps & Regulatory Readiness
Preparing for emerging frameworks like NIST 800-218 and the EU AI Act
Automating compliance through trust-by-design architectures
Managing "Shadow AI"
Reducing unsanctioned AI usage across teams
Enabling innovation with approved models and secure pathways
Board-Ready Metrics for AI Risk
Quantifying and communicating AI risk reduction
Measuring governance effectiveness in executive terms
