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AIAG: Agentic AI Governance

Agentic AI Governance, led by instructor Sunil Soares, explores the unique operational, regulatory, and ethical challenges of managing AI agents. The course introduces a 13-component governance framework supported by real-world case studies and practical guidance. Participants will gain a clear understanding of AI agent behavior and learn to address key risks, including bias, security, legal exposure, and compliance with global regulations like the EU AI Act. Ideal for those shaping AI strategy or overseeing implementation, this course equips learners to build responsible, resilient governance practices that align agentic AI with business goals and ethical standards.

Autonomous and semi-autonomous AI agents are transforming how businesses operate—taking on tasks, making decisions, and interacting with systems and users with minimal human input. These agentic systems promise major gains in innovation, productivity, and ROI. At the same time, they introduce new layers of complexity in transparency, accountability, ethics, and compliance. As organizations adopt these technologies, the ability to govern them effectively is critical to managing risk and building trust.

This Agentic AI Governance, taught by instructor Sunil Soares, offers a comprehensive look at how to manage the unique challenges posed by AI agents. The course presents a 13-part Agentic AI Governance Framework, grounded in real-world case studies and practical application. Participants will learn to identify the core characteristics of AI agents and navigate issues such as bias mitigation, human-in-the-loop design, security vulnerabilities, intellectual property concerns, data privacy, and compliance with global regulations like the EU AI Act and U.S. sector-specific laws.

By the end of the Agentic AI Governance course, participants will be able to:

Identify the characteristics and functional capabilities of AI agents across different industries.
Recognize governance challenges and implications related to the deployment of agentic AI systems.
Gain a working knowledge of global AI regulations, including the EU AI Act and U.S. sector-specific laws.
Apply risk management strategies tailored to the lifecycle of AI agents.
Assess AI systems for bias, fairness, reliability, security, and transparency.
Understand the ethical and legal considerations related to AI agents, including issues like voice cloning and autonomous decision-making.
Navigate the Agentic AI Governance Framework and its 13 components.
Clarify organizational roles and responsibilities for AI governance, including the function of a Chief AI Officer.
Evaluate and implement human oversight mechanisms and explainability requirements.
Leverage AI governance strategies to drive business value and return on investment.
Analyze real-world governance failures and successes through detailed case studies.
Anticipate emerging trends in agentic AI systems and prepare adaptive governance strategies.

Who Should Take This Course?

This training is ideal for professionals responsible for overseeing, implementing, or supporting AI agent initiatives within their organizations. It’s designed for data governance leaders, compliance officers, risk managers, IT and AI project managers, and legal or policy experts who need to understand the unique regulatory, ethical, and operational challenges of agentic AI. Whether you're developing governance frameworks from the ground up or adapting existing policies to account for autonomous AI systems, this course offers the structured guidance and practical tools needed to govern these technologies responsibly and effectively.

This Course Includes: