Impact of Generative AI and LLM-Based Multi-Agent Simulations on Marketing Strategy Design: Revolutionizing Decision-Making and Consumer Insight Generation

Abstract

The advent of generative artificial intelligence (AI) and large language model (LLM)-based multi-agent simulations has created a paradigm shift in the design and execution of marketing strategies. Traditional marketing approaches, often reliant on historical data and static models, face limitations in predicting consumer behavior in complex and dynamic markets. Generative AI-driven simulations offer a dynamic framework for modeling interactions among consumers, competitors, and market forces in real time, enabling more precise and adaptive strategy formulation. This paper explores the theoretical foundations, practical applications, challenges, and future scope of incorporating generative AI and multi-agent simulations in marketing strategy design. It highlights how these technologies enable marketers to anticipate market responses, optimize campaigns, and enhance decision-making under uncertainty.

KEYWORDS: Generative AI, Large Language Models (LLMs), Multi-Agent Simulations, Marketing Strategy, Consumer Behavior, Digital Marketing, Predictive Analytics, Decision-Making