Accountable Autonomy: A Governance Framework for Agentic AI in Telecommunication Networks

Abstract

Agentic artificial intelligence (AI) systems are increasingly deployed across distributed cloud–edge–radio infrastructures, where autonomous agents make decisions with direct operational and economic impact. Smart contracts (SCs) enforce business rules and policies, constraining autonomous actions according to predefined operational intent. As agent autonomy expands across heterogeneous networks, ensuring accountability requires transparency, verifiability, and compliance with SC-defined requirements. To address these challenges, this paper proposes the Agent Governance Framework (AGF), which integrates SC-based governance into agentic AI systems, enabling verifiable accountability through traceable autonomous decisions. Built on European Telecommunications Standards Institute (ETSI) and TM Forum principles, AGF comprises six components: (i) a TM Forum-aligned business support system (BSS); (ii) an agentic AI-enhanced operations support system (OSS); (iii) a Network Resource Operations subsystem; (iv) an Identity and Access Role Manager; (v) a Distributed Marketplace; and (vi) a Traceability and Auditability Registry. Together, these components provide an end-to-end (E2E) traceable architecture, linking each action to the responsible agent and SC. A prototype on a local test network with the evaluation of two complementary network test cases demonstrates the framework’s feasibility, confirms its full traceability and immutability, and highlights AGF’s potential as a foundation for reliable, large-scale agent-based systems in telecommunications networks. The results demonstrate 100% traceability across the E2E governance loop and a minimal latency overhead of 2–4% due to the Traceability and Auditability registry.