Algorithmic AI controlling

The controlling role of artificial intelligence in digital consumer behaviour

Abstract

This study examines the controlling effects of artificial intelligence-based algorithms on consumer behaviour from a marketing science perspective. Algorithmic controlling is defined as a set of digital mechanisms that filter, rank, and present content based on users’ prior behaviour, search history, and preference data, thereby shaping decision-making contexts. The research employs a thematic and interpretative synthesis of recent European-focused literature. The analysis identifies six key mechanisms of algorithmic controlling: scarcity messages, recommendation systems, filter bubbles and echo chambers, dark patterns in user interface design, dynamic and personalised pricing, and social proof manipulation. The study contends that these algorithms are not neutral intermediaries but act as active control elements in the digital consumer environment, with significant implications for vulnerability, fairness, and trust. The discussion further situates these mechanisms within the evolving EU regulatory framework, with particular attention to the Digital Services Act and the AI Act. The contribution of this research is to offer an integrative framework that connects technological, behavioural, and regulatory dimensions for a more comprehensive understanding of algorithmic influence in digital markets.