When software becomes an actor, identity becomes the bottleneck

Core Insights - AI agents are evolving from mere assistants to autonomous actors in production environments, capable of scheduling work, triggering actions, and updating records without direct human supervision [1][2] - The transition from AI as a helper to a delegated actor introduces challenges related to identity and authority within enterprise technology systems [3][4] Group 1: AI Agent Functionality - In early deployments, AI agents assist humans by preparing responses and gathering information, but they soon gain the ability to act on behalf of individuals or systems [2][6] - AI agents operate continuously across systems and time, reacting to conditions rather than following explicit instructions, which complicates traditional user-role permission frameworks [4][6] Group 2: Delegation and Authority - The concept of delegation is critical; AI agents act as delegated actors, which raises questions about whose authority they are exercising when taking actions [6][9] - Traditional enterprise systems are not designed for non-human actors with delegated authority, leading to potential accountability issues when the principal is unclear [3][9] Group 3: Failure Modes - Traditional systems exhibit visible failures such as stopping or throwing errors, while delegated systems may continue to operate and produce outcomes that are technically correct, complicating the understanding of failure [8] - The lack of clarity regarding an agent's authority can lead to confusion rather than identifiable breakdowns, impacting organizational accountability [8][9]