AI

A Three-Pillar Governance Framework for Safe and Trustworthy AI Agents

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Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 23/10/2026, 04:03:25 UTC.

Briefings

A new three-pillar governance framework addresses AI agent autonomy challenges by integrating transparency, accountability, and trustworthiness. The model outlines an evolutionary path where agent autonomy increases through progressive validation, structured human oversight, and auditable controls. This framework aims to support enterprise deployment of AI agents that remain aligned with human intent while enabling controlled progression toward higher autonomy.

Key points

• The framework defines a three-pillar model consisting of transparency, accountability, and trustworthiness to address AI agent safety and alignment challenges.
• Autonomy increases through a structured evolutionary path involving progressive validation, human oversight, and auditable operational controls.

Context

Existing Human-in-the-Loop (HITL) and responsible AI approaches are fragmented across system design, governance, and operational deployment, creating challenges for safe and trustworthy AI agents.

Limitations

Evidence is limited to an arXiv preprint; findings remain unverified until peer review and publication. Snapshot captures initial framework proposal without empirical validation or real-world deployment data.

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