Enterprise Governance & Production Scale

Overview

AI regulation remains fragmented, incomplete, and still evolving, yet enterprises are already deploying AI into core business operations. This executive session addresses the reality leaders face today: how to govern, scale, and operationalize AI responsibly before regulatory certainty arrives.

This session delivers a pragmatic governance framework for C-suite leaders responsible for approving, overseeing, and scaling AI initiatives. Rather than waiting for AI-specific regulations to mature, participants will learn how to anchor AI governance in proven enterprise frameworks, clearly define accountability, and build governance programs that adapt as new regulations emerge. Attendees will leave with practical governance models that support production-scale agentic AI while maintaining risk visibility, executive control, and organizational readiness.

5 Key Coverage Areas

AI Regulation Reality Check – Understand why AI-specific regulation remains immature and fragmented, including delayed enforcement timelines and the absence of a unified federal AI standard, and why waiting for certainty often increases enterprise risk rather than reducing it

Mapping AI Risk to Existing Enterprise Frameworks – Learn how to align AI risks with established governance and compliance structures such as SOC-2, ISO 27001–aligned security controls, GDPR, and HIPAA, while explicitly documenting the gaps these frameworks do not yet cover for agentic AI systems

Governance Without Over-Engineering – Define ownership, decision rights, and accountability models that function effectively in uncertain regulatory environments without introducing brittle controls or unnecessary process overhead

Adaptive Governance for Regulatory Change – Design governance programs built to evolve as AI regulations mature, separating enduring governance principles from temporary controls and avoiding static compliance checklists

From Experimentation to Production Scale – Identify the governance foundations required to move agentic AI from pilots into enterprise production responsibly, ensuring executive oversight, risk traceability, and organizational readiness at scale

Presenter

David Gloyn-Cox is an enterprise architect and governance specialist with extensive experience helping organizations establish accountable, risk-aware technology programs. He specializes in translating complex regulatory and compliance realities into practical governance models that executives can apply in real operating environments. His work spans enterprise architecture, governance design, and risk management across multiple industries, with a strong focus on preparing organizations to deploy AI responsibly at scale. David brings a board-level perspective on ownership, accountability, and decision-making, guiding enterprises as they navigate AI governance in the absence of finalized regulatory rulebooks.