101 AI Governance Key Terms for 2025

In July, the IAPP AI Governance Center updated its Key Terms for AI Governance. This list provides artificial intelligence governance professionals with a reference set of definitions to help navigate the practice of AI governance.

The initial set of key AI governance terms developed in the fall of 2023 by former IAPP Westin Research Fellow Amy Olivero consisted of 61 concepts. Given the constant and rapid evolution of the development and use of AI since then, we continue to update both the terms and definitions. This list now boasts more than 100 relevant concepts AI governance professionals use regularly.

The ongoing updates to the key terms reflect current and best-in-class understanding of key AI governance concepts. Updates are based on AI use and issues raised by the IAPP community and collaborators. These definitions are aligned with, or reference, authoritative definitions and concepts found in AI governance legislation, frameworks and reports from governments, international organizations and other trusted stakeholders. 

Part of the effort, as this list has evolved, has been to ensure that these key terms capture concepts covered in the IAPP AIGP training and certification as well as IAPP-led AI governance research. Consistently using terms has become an important aspect of this work: it’s a crucial way to help support AI governance professionals. As AI technology is advancing at such a rapid pace, a common understanding of terminology is critical for AI governance teams to be able to have clear, effective and consistent conversations. 

Recent updates include the inclusion of the following terms: agentic AI, autonomy, counterfactual, data drift, fail-safe plans, retrieval augmented generation, shadow AI and weights.