Agentic AI Trust, Safety & Alignment in Multi-Agent Systems: A Comprehensive Framework for Secure Autonomous Enterprise Intelligence

ATLAS (Autonomous Trust, Alignment and Safety Architecture) is a proposed governance and security framework for enterprise-scale multi-agent AI systems. The framework introduces eight integrated layers addressing agent identity, capability control, prompt validation, communication integrity, memory verification, risk assessment, alignment monitoring, and human oversight. This work explores emerging security and alignment challenges in agentic AI environments, including prompt injection, tool poisoning, memory poisoning, autonomous escalation, and cascading failure chains. A simulation-based evaluation is presented to illustrate the potential effectiveness of the framework in reducing attack success rates and improving governance outcomes. Keywords: Agentic AI, Multi-Agent Systems, AI Safety, AI Alignment, Enterprise AI, AI Governance, Cybersecurity, Autonomous Systems.