Ownership

Ownership refers to the assignment of clear responsibility and accountability for AI systems, models, and their outcomes across an organization. In enterprise governance, establishing ownership ensures that specific individuals or teams are accountable for developing, deploying, monitoring, and maintaining AI systems in compliance with regulations and internal policies. This clarity of ownership is critical for managing liability, ensuring ethical use, maintaining audit trails, and enabling rapid response to issues like model drift, bias, or regulatory violations.

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ResearchGlobal2026-07-23

Healthcare Multi-Agent AI Creates Ownership and Retirement Gaps That Standard Governance Frameworks Do Not Cover, arXiv Research Warns

A preprint published on arXiv proposes a comprehensive governance and lifecycle management framework for agentic AI systems deployed in healthcare settings. The framework focuses on the specific risks that arise when autonomy is distributed across multiple interacting agents, including unclear ownership, uncontrolled permission expansion, and the absence of structured retirement processes. Its core argument is that enterprise-level visibility and enforceability are prerequisites for safe deployment of these systems.

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