Understanding agent governance technology approaches

Agent artificial intelligence (AI) automates AI using the reasoning power of large language models (LLMs) to make decisions without human intervention. A governance framework is needed to create transparency of decision lineage in multi-agent systems to offer fixes throughout the life cycle of agent development and deployment to ensure agency and safety for humans. This paper outlines five approaches to agent governance and compares the different approaches to offer guidance on this important topic across multiple industries. This includes tracking for metrics,1 security risk from agents calling application programming interfaces (APIs),2 data governance,3 human-in-the-loop approaches,4 and rules to test adversarial attacks for edge cases.5 This paper is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.