From AI-Ready to AI-Governed

AI Is Writing Your Code. Who's Governing It?

AI-accelerated development has moved from experimentation to everyday operations. But as AI agents gain the ability to write, test and deploy code autonomously, security leaders face an entirely new class of software supply chain risk.

From AI-generated malware to poisoned open-source models and malicious dependencies entering enterprise pipelines, the threat landscape is evolving faster than traditional security controls can keep pace.

When AI agents can build and deploy software with minimal human intervention, perimeter security alone is no longer enough. Organizations need a new approach - one that embeds security, governance and trust directly into the software development lifecycle.

Join a select group of peer CISOs and senior security leaders for a virtual roundtable on moving from AI readiness to AI governance.

A New Operating Model: MLGovOps

AI is transforming how software is built. The next challenge is ensuring it is built securely, governed effectively, and trusted at scale.

Enter MLGovOps - an emerging approach to embedding machine learning governance, security, and compliance directly into the software supply chain.

Rather than treating governance as a final checkpoint, MLGovOps brings trust and accountability into the development process from the start.

For security leaders, this means rethinking how identities are managed, AI models are approved, dependencies are trusted, an risk is measured across increasingly autonomous environments.

The goal is clear: enable AI-driven innovation without losing control over the systems, models, and software that power the enterprise.

What You'll Explore

This virtual roundtable will bring together security leaders to discuss the practical challenges of governing AI-driven development - and how organizations can move from reactive controls to proactive, embedded governance.

1. The Rise of the Autonomous Supply Chain - As AI agents take on greater responsibility for building and deploying software, traditional assumptions about identity, accountability and trust begin to change.

• How do you secure identities and permissions when AI agents - rather than humans - are building software?
• What does trust look like when human oversight is limited?
• How can organizations establish accountability across autonomous development workflows?

2. Curation vs Chaos in AI Model Intake - The growing availability of AI models and tools creates new opportunities for innovation - alongside new risk for malicious or compromised components.

• How can organizations reduce the risk of model poisoning, prompt injection, and malicious dependencies?
• What role can trusted AI model catalogs play in reducing systemic risk?
• How should security teams establish clear policies for model approval, provenance and usage?

3. DevGovOps and Regulatory Readiness - As AI governance expectations evolve, organizations must connect software security controls with demonstrable compliance and accountability.

• How can organizations prepare for relevant frameworks, including NIST Secure Software Development Framework guidance and the EU AI Act?
• Where can compliance evidence and governance checks be automated?
• How can trust-by-design architectures help embed governance into everyday development workflows?

4. Managing Shadow AI - Unsanctioned AI adoption can introduce risks that security teams cannot easily see or measure. Yet overly restrictive policies can push usage further out of view.

• How can organizations identify and reduce unsanctioned AI usage across teams?
• How can approved models, tools and secure development pathways enable innovation without sacrificing control?
• What does an effective balance between developer autonomy and organizational governance look like?

5. Board-Ready Metrics for AI Risk - AI governance must move beyond policies and principles to demonstrate measurable outcomes that resonate with executive leadership.

• How can security leaders quantify AI risk reduction and communicate it in business terms?
• Which metrics best demonstrate the effectiveness of AI governance?
• How can CISOs give boards confidence that AI adoption is progressing responsibly and securely?

Join the Conversation

AI is writing your code. It's time to govern what comes next.

Join a select group of CISOs and senior security leaders for a virtual roundtable exploring how to secure autonomous development, operationalise AI governance, and build trust at scale. 

Register below