Confidently implement NIST AI Risk Management Framework
RiskCognition can help you implement the NIST AI Risk Management Framework, a voluntary guide for managing AI-related risks. Our platform provides a clear, structured way to responsibly develop, deploy, and use AI systems, transforming a complex, non-regulatory framework into an actionable strategy for your organization.
We help you identify, assess, and mitigate risks
The AI RMF is designed to be flexible and adaptable, serving as a guide for organizations of all sizes and in all sectors.
RiskCognition provides a structured approach for your entire AI lifecycle, from initial design to decommissioning. We help you identify, assess, and mitigate risks like algorithmic bias and privacy violations, ensuring you not only address potential negative impacts but also maximize the positive benefits of AI.
Core Functions
The framework is built around four core functions that are meant to be a continuous and iterative process:
Core Functions The framework is built around four core functions that are meant to be a continuous and iterative process: 1. Govern: This function is the foundation of the framework. It emphasizes the need for a strong culture of AI risk management within an organization. This involves establishing clear policies, assigning roles and responsibilities, and ensuring that AI risk management is integrated into the organization's overall governance structure. 2. Map: In this stage, organizations identify and understand the context and potential risks of their AI systems. This includes identifying the AI's purpose, the data it uses, and the potential impacts on people and society. The goal is to gain a comprehensive understanding of the risks, both intended and unintended, within a specific use case. 3. Measure: This function focuses on assessing and analyzing the identified risks. Organizations are encouraged to use both quantitative and qualitative methods to evaluate the performance, reliability, and security of their AI systems. This could involve testing for biases, evaluating data quality, and conducting security assessments. 4. Manage: Once risks are identified and measured, the final function is to prioritize and act on them. This involves developing and implementing strategies to mitigate risks, monitor the AI system post-deployment for new and emerging risks, and communicate with stakeholders about the risk management process.
AI Tech + Domain Expertise
A central concept of the NIST AI RMF is the promotion of "trustworthy AI"
RiskCognition helps you implement the NIST AI Risk Management Framework by using our cutting-edge AI platform and deep domain expertise. We turn the framework's core principles into actionable practices for your organization.
Framework for Responsible and Reliable AI
NIST AI RMF provides a flexible and collaborative guide to help organizations navigate the complex landscape of AI risks and build AI systems that are not only innovative but also safe, ethical, and trustworthy.
NIST AI RFM DESIGN
Case Studies
Case Study – SOC 2
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