arXiv:2605.23179v1 Announce Type: new Abstract: Agentic AI orchestrators reduce the interface and assembly costs of composing information systems capabilities across organizational boundaries, seemingly accelerating modularization and organizational disaggregation. Yet AI-enabled capabilities whose outputs require evidence, review, signoff, or assignable responsibility may retain integrated accountability boundaries even when their technical interfaces become modular. We develop a capability-level theory of accountability-boundary placement in agentic ecosystems. We introduce accountability as
The rapid deployment and integration of AI agents across enterprises necessitate a framework for understanding and assigning accountability as these systems become more autonomous.
This theory directly addresses the critical challenge of governance and responsibility in a world increasingly reliant on AI agents, impacting legal, ethical, and operational structures.
The conventional understanding of accountability boundaries will shift, moving from strictly technical interfaces to a capability-level analysis that considers evidence, review, and assignable responsibility.
- · AI governance specialists
- · Legal tech firms
- · Organizations adopting structured agentic systems
- · Companies with opaque AI systems
- · Traditional IT service models
- · Individual developers without clear accountability frameworks
Enterprises will begin to implement new internal frameworks for AI agent accountability, influencing software development lifecycles.
New regulatory standards and insurance products will emerge specifically designed for agentic ecosystems and their associated risks.
The definition of legal personhood and corporate liability may evolve to incorporate the actions and outputs of highly autonomous AI agents.
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Read at arXiv cs.AI