Key Components of an AI Governance Program

An effective AI governance program combines clear rules, smart technological limits, and time-tested risk management techniques to enhance oversight and internal control when using artificial intelligence solutions. One effective way to implement a governance program is by using a framework. A well-developed framework will help you understand and apply key components of AI governance in your organization. This will facilitate the protection of data privacy, prevention of bias, and establishment of clear lines of communication, accountability, and ownership in decisions related to AI systems and their impact on your business.

Your blueprint for an effective AI framework

The NIST Artificial Intelligence Risk Management Framework, or NIST AI RMF for short, was developed by the National Institute of Standards and Technology (NIST) to help manage the risks that artificial intelligence poses to individuals, organizations, and society. In this article, we’ll use this framework to explain and document the key components of AI governance. The following sections will take you through each component and explain how they fit into the risk management framework.

NIST AI RMF 1.0 Core

The AI RMF is made up of four key components: Govern, Map, Measure, and Manage. Each component contains sub-categories that provide further context and will help you understand how different elements apply to your organization. Together, these elements can help guide your AI development, ensure compliance, and foster the responsible innovation and application of AI systems.

Govern

• Policies, processes, procedures and practices across the organization related to the mapping, measuring, and managing of AI risks are in place, transparent, and implemented effectively.
• Accountability structures are in place so that the appropriate teams and individuals are empowered, responsible, and trained for mapping, measuring, and managing AI risks.
• Workforce diversity, equity, inclusion, and accessibility processes are prioritized in the mapping, measuring, and managing of AI risks throughout the lifecycle.
• Organizational teams are committed to a culture that considers and communicates AI risk.
• Processes are in place for robust engagement with relevant AI actors.
• Policies and procedures are established to address AI risks and benefits related to third-party software, data, and other supply chain issues.

Map

• Context is established and understood.
• Categorization of the AI system is performed.
• AI capabilities, targeted usage, goals, and expected benefits and costs are understood and compared with appropriate benchmarks.
• Risks and benefits are mapped for all components of the AI system, including third-party software and data.
• Impacts to individuals, groups, communities, organizations, and society are characterized.

Measure

• Appropriate methods and metrics are identified and applied.
• AI systems are evaluated for trustworthy characteristics.
• Mechanisms for tracking identified AI risks over time are in place.
• Feedback about efficacy of measurement is gathered and assessed.

Manage

• AI risks based on assessments and other analytical output from the Map and Measure functions are prioritized, responded to, and managed.
• Strategies to maximize AI benefits and minimize negative impacts are planned, prepared, implemented, documented, and informed by input from relevant AI actors.
• AI risks and benefits from third-party entities are managed.
• Risk treatments, including response, recovery, and communication plans for identified and measured AI risks, are documented and monitored regularly.

Take control of your AI governance

These building blocks of governance can empower your organization to navigate the complexities of AI adoption responsibly. By fostering risk awareness, aligning with your organizational principles, and addressing legal considerations, businesses can maximize the benefits of AI while minimizing the negative impacts. As we venture further into the AI governance landscape, these key components will serve as your guide, ensuring ethical, accountable, and innovative AI practices.

If your organization is looking to develop or enhance its AI governance frameworks, our team offers extensive expertise and strategic guidance tailored to your specific needs. Please fill out the firm on this page to connect with one of our professionals to ensure your AI initiatives are governed effectively, ethically, and in compliance with global standards.