Future of Trust in an AI World - Rethinking AI Compliance and Operations

Overview

Syllabus

• Introduction to AI Compliance
Overview of AI Regulations and Standards
Importance of Compliance in AI Systems
Key Stakeholders in AI Compliance
• Building Sustainable AI Compliance Programs
Assessing Current Organizational Compliance Practices
Designing a Compliance Framework for AI
Setting Compliance Goals and Objectives
• Leveraging Existing Tools for Compliance
Review of AI Compliance Tools and Software
Integrating Compliance Tools into AI Workflows
Case Studies on Successful Tool Integration
• Embedding Risk-Aware Practices
Identifying and Assessing AI Risks
Strategies for Risk Mitigation in AI Projects
Developing a Culture of Risk Awareness
• Managing Vendor Relationships
Evaluating Vendor Compliance Capabilities
Building Strong Partnerships with Vendors
Contractual Considerations for AI Solutions
• Adapting to the Evolving AI Landscape
Monitoring Changes in AI Regulation
Future Trends in AI Compliance
Continuous Improvement in Compliance Programs
• Case Studies and Real-World Applications
Analysis of Industry-Specific Compliance Challenges
Lessons Learned from Compliance Failures
Best Practices in AI Compliance
• Conclusion and Path Forward
Summarizing Key Takeaways
Developing a Personal Action Plan for AI Compliance
Resources for Continued Learning in AI Compliance

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Subjects

Business