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

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