Three-pillar framework guides safer autonomous AI agents
A Three-Pillar Governance Framework for Safe and Trustworthy AI Agents
Artificial Intelligence
Summary
Autonomous AI agents that make their own decisions can be risky without proper controls. The authors propose a framework with three main parts—transparency, accountability, and trustworthiness—to help safely build and manage these agents. Their model encourages gradually giving agents more independence while keeping humans involved to check and audit decisions. This approach aims to ensure AI systems act in line with human intentions as they become more capable.
What this means in practice
- •For enterprise ai teams: Implement structured oversight and auditing to safely deploy autonomous AI agents within business environments.
- •For it governance teams: Use the framework to monitor AI agent decisions and manage escalation paths for improved accountability.
A position paper. It proposes an approach and reports no results.
Authors
Edward C. Cheng, Jeshua Cheng, Alice Siu
Abstract
AI agents capable of autonomous decision-making introduce significant challenges related to safety, alignment, accountability, and human oversight. Existing Human-in-the-Loop (HITL) and responsible AI approaches provide important foundations, but many remain fragmented across system design, governance, and operational deployment. This paper presents a Three-Pillar (3P) model and framework for developing safe and trustworthy AI agents through transparency, accountability, and trustworthiness. The framework defines an evolutionary path in which increasing agent autonomy is introduced through progressive validation, structured human oversight, and auditable operational controls. We further describe how the model supports agent lifecycle monitoring, decision traceability, escalation management, and human-agent collaboration within enterprise agentic environments. By integrating oversight principles with operational mechanisms, the proposed framework provides a practical foundation for deploying AI agents that remain aligned with human intent while enabling controlled progression toward higher autonomy.