Artificial intelligence (AI) tools are moving away from analytical tools toward semi-autonomous and autonomous agents that enable cross-functional collaboration and skills sharing. This session spotlights this important shift, how it challenges traditional governance models, and explores the implications for accountability, oversight, and professional judgment. This webcast will cover:
Modern, enterprise-wise AI governance operation models
Risk oversight
Regulatory and assurance readiness in environments where AI is embedded across products, platforms, and ecosystems
Learning Objectives
Identify AI governance risks across industries, including agentic and autonomous systems.
Recognize how AI agents affect accountability, transparency, and decision authority.
Distinguish effective governance practices for traditional AI versus agent-based AI.
Recognize AI governance principles across the AI lifecycle and organizational boundaries.
Estimate readiness for regulatory, assurance, and stakeholder expectations.
Major Topics
Enterprise AI governance across industries
Agentic AI and autonomous decision-making
AI-to-AI (agent-to-agent) interaction risks
Accountability, explainability, and oversight
Regulatory and assurance implications of AI
CPE Credits Available
1 CPE Credit
1
Information Technology
Things to Know About This Course
Course Level
Basic
Professional Area of Focus
Technology
Prerequisites
none
Advanced Preparation
None
Intended Audience
This program is designed for professionals responsible for governance, risk, and oversight across all industries, including:
CPAs in public practice and industry
Audit, tax, and advisory partners and managers
Board members and executive leadership
Risk management, compliance, and ethics leaders
Technology, data, and innovation leaders
Professionals working within or serving TMT organizations
