SYSTEMATIC REVIEWS: EXPLORING CONSUMER ACCEPTANCE OF AI

Abstract

This paper explores the factors influencing consumer acceptance and resistance to artificial intelligence (AI) technologies. It examines AI’s role in decision-making across industries such as personalized recommendations, healthcare, and finance, while highlighting the mixed consumer responses influenced by optimism, pessimism, and misconceptions. Notably, “algorithm aversion” emerges as a significant barrier, where consumers prefer human judgment despite AI’s superior accuracy due to concerns about personal nuances and error-learning limitations. This review outlines strategies to enhance AI acceptance, including consumer education, personalized outputs, and anthropomorphism, while acknowledging associated risks. The paper concludes by emphasizing the importance of aligning AI design with consumer relationship norms and ethical considerations to foster trust and adoption.