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AI Organizational Responsibilities - Governance, Risk Management, Compliance and Cultural Aspects
AI Organizational Responsibilities - Governance, Risk Management, Compliance and Cultural Aspects
Who it's for:
  • CISOs, business leaders, and investors
  • AI researchers, engineers, and developers 
  • Policymakers and regulators 
  • Customers
  • The general public 

AI Organizational Responsibilities - Governance, Risk Management, Compliance and Cultural Aspects

Release Date: 10/21/2024

Continuing CSA's efforts to address the evolving AI landscape, this latest publication covers AI governance, risk management, and culture. Understand various roles and their responsibilities in AI strategy, compliance, technical security, and operations. Find comprehensive best practices that are a must-read for CISOs, AI developers, business leaders, and many others.

This publication steers organizations toward responsible and secure development and deployment of AI. Learn about AI security policies, audit processes, and legislation like the EU AI Act and US AI Executive Order. Delve into strategies for managing risk, developing a strong safety culture, managing inventory, controlling access, and monitoring activities.

For every responsibility listed, understand its evaluation criteria, responsibility matrix, implementation strategies, continuous monitoring and reporting mechanisms, access controls, and applicable regulations. Ensure that your organization can successfully assess, implement, and manage AI initiatives.

This guidance was a collaborative effort by the AI Organizational Responsibilities Working Group and builds on their foundational guidance.

Key Takeaways:
  • The potential job roles within AI governance, technical support, development, and strategic management
  • AI risk management strategies, including threat modeling, risk assessments, attack simulations, incident response planning, and data drift surveillance
  • How to establish and maintain a robust AI governance structure while ensuring adherence to relevant regulations and standards
  • How to build a robust AI safety culture and implement effective training programs
  • Strategies for identifying, managing, and preventing shadow AI
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