Safety and Risk Pathways in Cooperative Generative Multi-Agent Systems: A Telecom Perspective

Generative multi-agent systems are rapidly emerging as transformative tools for scalable automation and adaptive decision-making in telecommunications. Despite their promise, these systems introduce novel risks that remain underexplored, particularly when agents operate asynchronously across layered architectures. This paper investigates key safety pathways in telecom-focused Generative Multi-Agent Systems (GMAS), emphasizing risks of mis-coordination and semantic drift shaped by persona diversity. We propose a modular safety evaluation framework that integrates agent-level checks on code quality and compliance with system-level safety metrics. Using controlled simulations across 32 persona sets, five questions, and multiple iterative runs, we demonstrate progressive improvements in analyzer penalties and Allocator-Coder consistency, alongside persistent vulnerabilities such as policy drift and variability under specific persona combinations. Our findings provide the first domain-grounded evidence that persona design, coding style, and planning orientation directly influence the stability and safety of telecom GMAS, highlighting both promising mitigation strategies and open risks for future deployment.