Yash Mehta
As Digital marketing ecosystems are becoming increasingly complex, intelligent, flexible, and autonomous solutions are required, which are capable of taking decisions in real-time. In order to alter the conventional marketing lifecycle, this study proposes a novel framework of a Multi-Agent Autonomous Marketing System (MAAMS) powered by Agentic Artificial Intelligence (AI). The proposed framework facilitates decentralized yet coordinated execution of marketing activities by integrating specialized agents for planning, execution, experimentation, and optimization tasks. Each of these agents employs machine learning (ML) algorithms, data-driven intelligence, and feedback mechanisms in order to increase consumer engagement and campaign success rates. The dynamic nature of the proposed framework allows strategies to be adapted in real-time in response to environmental changes and performance tracking, which is a characteristic of the closed-loop system architecture. The multi-agent coordination also introduces a novel paradigm for managing complex interdependencies of marketing activities, including budgeting, targeting, content management, and performance tracking.