KPMG's AI Risk and Controls Guide: Building Trustworthy AI
KPMG has released an AI Risk and Controls Guide to help organizations manage the risks associated with Artificial Intelligence. This guide, aligned with KPMG's Trusted AI framework, provides a structured approach to understanding AI risks and offers actionable control considerations. It aims to enable the responsible and ethical deployment of AI initiatives, fostering trust and maximizing AI's potential.
Navigating AI Risks with a Structured Approach
The rapid adoption of Artificial Intelligence presents both immense opportunities and significant risks for organizations. To fully harness AI's potential, it is crucial to embed trust through robust risk management practices. KPMG's AI Risk and Controls Guide offers a foundational resource for internal audit and assurance professionals to navigate this complex landscape. The guide provides a structured methodology for identifying and understanding AI-specific risks, which is essential for developing a comprehensive AI governance program.
Actionable Controls for AI Governance
A key takeaway for assurance professionals is the guide's focus on actionable control considerations. It moves beyond theoretical discussions of AI risks by offering practical insights into designing an AI control catalog tailored to an organization's specific AI deployments. This includes:
- Identifying relevant AI risks for governance programs.
- Leveraging control considerations to build a customized control framework.
- Integrating these risks and controls into existing AI governance programs, processes, and policies.
This practical guidance empowers internal auditors to assess the effectiveness of AI controls and provide assurance on the responsible use of AI within their organizations.
Alignment with the KPMG Trusted AI Framework
The guide is deeply rooted in KPMG's Trusted AI framework, which emphasizes a values-driven, human-centric, and trustworthy approach to AI development and deployment. This framework is critical for addressing ethical concerns and ensuring compliance with evolving regulatory standards. For internal audit, understanding this framework and its 10 pillars is vital for evaluating an organization's adherence to responsible AI principles. The guide's inventory of AI risks, coupled with control considerations organized under these pillars, provides a clear roadmap for assessing and enhancing AI trust and compliance.
Source: KPMG.com
