Toward Enterprise Autonomy: A Multi-Agent Generative AI Architecture for Business Intelligence”

The increasing complexity and velocity of business data demand intelligent systems capable of autonomous and real-time decision-making, which traditional business intelligence (BI) systems fail to provide due to their reliance on static and descriptive analytics. To address this limitation, this paper proposes a multi-agent generative artificial intelligence (AI) architecture that integrates autonomous agents for real-time data processing and strategic decision-making. The framework employs specialized agents for data ingestion, analysis, and decision generation, leveraging generative AI models to produce context-aware insights and recommendations dynamically. Experimental evaluation through a prototype implementation demonstrates improved decision accuracy, reduced response time, and enhanced scalability compared to conventional BI approaches. The system also shows strong adaptability to changing business scenarios by enabling continuous and collaborative agent interactions. This architecture can be applied in domains such as financial analytics, supply chain optimization, and enterprise resource planning, where timely and intelligent decision-making is critical, thereby enhancing organizational agility and strategic outcomes.