THE EVOLUTION OF THE CONSUMER: FROM HUMAN DECISION-MAKERS TO ALGORITHMIC CONSUMERS, DIGITAL TWINS, AND SYNTHETIC CONSUMERS

Abstract

This article follows the evolution of the consumer concept from traditional models based on the observation of human behavior to advanced digital representations based on artificial intelligence. Through a conceptual analysis of the literature on consumer behavior, digital footprints, algorithmic consumers, digital twins and synthetic consumers, the article proposes an evolutionary framework that explains the progressive transformation of the consumer into a digital entity capable of being modeled, simulated and anticipated. The findings highlight that the development of Big Data, Machine Learning and Large Language Models is fundamentally changing the way researchers and organizations understand, measure and predict consumer behavior. The article discusses the theoretical, managerial and ethical implications of this transformation, including issues of decision autonomy, data privacy, and algorithmic transparency.