3 Hours
Official Google Content led by Google Authorized Instructors
After-Course Instructor Coaching
-
Sep 24 9:00 AM - 12:00 PM EDTVirtual
Agentic AI Governance Essentials
Agentic AI Governance Essentials 5401
- Duration: Less than a day
- Language: English
- Level: Intermediate
This course provides learners with the essential skills to govern the design, deployment, and scaling of autonomous, Agentic AI systems. It focuses on enabling rapid innovation and accelerating speed-to-market while managing the unique risks presented by AI systems that can make decisions without constant human input. The course is structured around the practical application of the four-phase Agentic AI Governance Maturity Roadmap (Establish, Implement, Scale, Accelerate). The course uses a blend of presentations, detailed case-study scenarios (Cymbal Health, Cymbal Insurance, etc.), group discussions, a tabletop exercise, and quizzes to ensure effective learning. The real-world examples ensure participants can immediately connect theoretical principles to their own organizational and regulatory challenges.
Agentic AI Governance Essentials Training Delivery Methods
In-Person
Online
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Agentic AI Governance Essentials Training Information
- Official Google Content led by Google Authorized Instructors
- ACIC
Prerequisites:
Familiarity with AI Tools in an Enterprise setting
Who Should Attend:
- Business leaders
- Technical practitioners
- Governance professionals
Important Course Information:
- Defining Agentic AI and identifying the key risk vectors unique to autonomous systems (e.g., opacity of logic and the accountability void).
- Establishing the foundational structure, including a cross-functional AI governance committee and core ethical principles.
- Implementing technical enforcement mechanisms, such as real-time audit logging (Decision Provenance Logs) and building in technical guardrails like the Human Veto Point (HVP).
- Scaling governance enterprise-wide by standardizing tooling, establishing a centralized orchestration platform, and integrating controls into the CI/CD pipeline.
- Leveraging governance as a competitive advantage by shifting from oversight to enablement and monetizing trust through external transparency.
Agentic AI Governance Essentials Training Outline
Module 1: The agentic AI governance imperative
- Define agentic AI and understand its governance implications.
Module 2: Establish
- Identify key risk vectors unique to autonomous AI systems.
- Establish accountability and oversight mechanisms.
Module 3 Implement
- Implement governance frameworks for agentic AI deployments.
- Design controls that balance innovation with risk management.
Module 4: Scale
- Establish accountability and oversight mechanisms.
Module 5: Accelerate Module 5: Accelerate
- Design controls that balance innovation with risk management.
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Agentic AI Governance Essentials Training FAQs
Agentic AI refers to AI systems that can autonomously make decisions, plan actions, use tools, and execute tasks with limited human intervention. Because these systems can act independently, organizations must establish governance frameworks to ensure accountability, transparency, security, compliance, and alignment with business objectives. Effective governance helps organizations manage risks while enabling responsible innovation.
This course is designed for business leaders, AI program managers, risk and compliance professionals, cybersecurity practitioners, data governance teams, auditors, legal and regulatory specialists, and anyone responsible for overseeing, deploying, or managing AI systems within an organization. No advanced AI development experience is required.
Participants will learn how to identify governance challenges unique to Agentic AI, assess operational and compliance risks, establish governance controls, define accountability frameworks, and align AI initiatives with emerging regulations and industry best practices. By the end of the course, learners will be able to develop a practical governance approach for autonomous AI systems that balances innovation, trust, and organizational risk management.