Advanced AI Governance: Operationalizing AI Controls and Continuous Monitoring

Advanced AI Governance: Operationalizing AI Controls and Continuous Monitoring

27mAdvanced2024-10-21

Authors

Meghan Maneval

Meghan Maneval

Course details

As AI technologies continue to evolve and infiltrate every aspect of our businesses, the need for robust AI governance has never been more critical. In this course, AI governance pioneer Meghan Maneval dissects AI governance to give you an understanding of AI regulations and their role in developing your organization’s AI controls. Explore the critical steps to operationalizing AI governance by integrating controls into your business processes and conducting business impact assessments. Plus, discover practical steps for building an AI continuous monitoring program that scales into the future.

Learning objectives
Design and implement effective controls to ensure the security and reliability of AI systems.
Establish a comprehensive governance framework that is both compliant and adaptable to organizational needs.
Conduct AI Business impact assessments and integrate AI controls into business processes.
Effectively apply these strategies within their organization to ensure that AI systems are secure, functional, and adhere to ethical standards throughout their operational life cycle.

Skills covered

Governance, Risk, and ComplianceArtificial Intelligence FoundationsArtificial Intelligence (AI)CybersecurityOne-Off

Concepts

Introduction

  • Kickstart your AI governance journey
  • Preparing for success

Understanding and Applying AI Governance

  • Navigate AI regulations for responsible AI use
  • Streamline your AI governance with existing controls
  • Design AI controls to manage risk and ensure compliance

Operationalizing AI Controls

  • Evaluate and enhance your controls
  • Integrate AI controls into business processes

Strategies for Success and Scalability

  • Conduct an AI impact assessment to prioritize risk
  • Deploy trustworthy AI systems with confidence
  • Monitor and scale AI systems for long-term success

Conclusion

  • Wrap-up, takeaways, and next steps
40,000 Toman