With Great Capabilities Come Great Responsibilities: Introducing the Agentic Risk & Capability Framework for Governing Agentic AI Systems

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Authors: Shaun Khoo, Jessica Foo, Roy Ka-Wei Lee
Cited by: 1

Abstract

Agentic AI systems present both significant opportunities and novel risks due to their capacity for autonomous action, encompassing tasks such as code execution, internet interaction, and file modification. This poses considerable challenges for effective organizational governance, particularly in comprehensively identifying, assessing, and mitigating diverse and evolving risks. To tackle this, we introduce the Agentic Risk & Capability (ARC) Framework, a technical governance framework designed to help organizations identify, assess, and mitigate risks arising from agentic AI systems. The framework's core contributions are: (1) it develops a novel capability-centric perspective to analyze a wide range of agentic AI systems; (2) it distills three primary sources of risk intrinsic to agentic AI systems - components, design, and capabilities; (3) it establishes a clear nexus between each risk source, specific materialized risks, and corresponding technical controls; and (4) it provides a structured and practical approach to help organizations implement the framework. This framework provides a robust and adaptable methodology for organizations to navigate the complexities of agentic AI, enabling rapid and effective innovation while ensuring the safe, secure, and responsible deployment of agentic AI systems.

Fields of Study & Subjects

Ethics and Social Impacts of AI Scientific Computing and Data Management Multi-Agent Systems and Negotiation

Publication details

Journal / source
Proceedings of IASEAI Conference
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Volume
2
Issue
1
Pages
318–330
Publication date
15 July 2026