An Illustrative AI Risk and Controls Guide
Organizations can only harness AI’s full potential when initiatives are grounded in trust. That’s why pragmatic, scalable risk management practices are so critical to the success of AI programs.
What is the AI Risk and Controls Guide?
We published this first-of-its-kind AI Risk and Controls Guide to help organizations manage the risks of AI in a responsible and ethical manner. This guide:
- Is aligned with the KPMG Trusted AI framework
- Provides a structured approach for understanding AI risks
- Delves into actionable control considerations to manage those risks
Dive into our thinking:
Deploying trustworthy AI: An Illustrative Risk and Controls Guide
Download PDFHow to use the AI Risk and Controls Guide
This guide can serve as a resource for any professional involved in AI risk management and governance. Use it to help you:
- Identify the AI risks that are relevant to your AI governance program and principles
- Leverage the control considerations to design an AI control catalog tailored to your AI deployments
- Integrate the risks and controls into your AI governance program, processes, and policies
About the KPMG Trusted AI framework
The AI Risk and Controls Guide is aligned to our Trusted AI framework, which is rooted in a values-driven, human-centric, and trustworthy approach to AI development and deployment. The Trusted AI framework helps our own firm, and our clients, develop and deploy AI solutions that address ethical concerns and comply with regulatory standards.
Organized under the 10 pillars of the KPMG Trusted AI framework, this guide outlines an initial inventory of AI risks, each with a set of control considerations that organizations can leverage as they build out their control catalogues.
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How KPMG can help
The KPMG AI Trust framework offers a pathway to help harness AI's potential in a trusted manner, and our suite of Trusted AI services and solutions helps companies put the framework into action. Our services include:
- Trusted AI Strategy
- AI Ethics and Governance
- AI Risk Assessment and Regulatory Compliance
- Machine Learning Operations
- AI Security
- AI Assurance
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