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June 11, 2025
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June 27, 2025
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August 22, 2025
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Abstract

Artificial intelligence (AI) is changing the landscape of consumer behaviour in how preferences develop, decisions form, and engagement via marketing occurs. This conceptual paper explores 89 reports, articles, and case studies to analyze the algorithmic consumer, examining the multifaceted impact of AI on consumer preferences and decision-making. By a thorough literature review and commentary, I critically analyzed the impact of AI’s personalization algorithm and addressed ethical implications in terms of potential bias, data privacy, and transparency. This paper establishes a conceptual framework to illustrate how AI technologies, including machine learning, natural language processing, and predictive analytics, intersect with facets of consumer psychology, allowing for personalization of experiences, market segmentation, and influencing behaviour in real time. While AI offers marketers tools to enhance targeting and engagement constructively, AI presents significant ethical implications around autonomy, manipulation, and equity. Therefore, recommendations for transparency, accountability, and ethical considerations of AI applications and frameworks for marketers using AI were also presented. This paper contributes to dynamic discourse around how to responsibly approach AI to influence consumer engagement by providing both a theoretical framework for future empirical study as well as a strategic direction for marketers, developers, and policymakers. Ultimately, this paper insists on a sensible balance between maximizing the potential of AI to shape markets and consumer engagement and the need for consumer trust and well-being.

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Artificial intelligence in marketing Consumer decision-making Algorithmic personalization Ethical AI Use Digital consumer behavior

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How to Cite
Sifat, A. I. (2025). The algorithmic consumer: A conceptual investigation of AI’s influence on consumer preferences and decisions. Asian Management and Business Review, 5(2), 471–486. https://doi.org/10.20885/AMBR.vol5.iss2.art14
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