Humans or AI: How the Source of Recommendations Influences Consumer Choices for Different Product Types

The rise of artificial intelligence (AI) has transformed the way consumers interact with brands and make purchasing decisions. One significant development has been the integration of AI as a recommendation tool, which companies like Amazon, Netflix, and Spotify use to deliver personalized product and service suggestions. However, while AI-driven recommendations provide personalized insights based on shopping behaviors, consumers often demonstrate a preference for human recommendations, especially when subjective judgment is involved (Longoni et al., 2019). The research into “algorithm aversion” highlights that consumers tend to favor human experts over AI in subjective or emotional decision contexts (Dietvorst et al., 2015) due to the algorithms’ inability to address consumers’ unique characteristics, referred to as “uniqueness neglect” (Longoni et al., 2019). In contrast, in more objective decision-making situations, such as those requiring numerical precision or logical reasoning, consumers may prefer AI over human recommendations (Castelo et al., 2019). As a result, for products that require detailed, fact-based evaluations (i.e., search products), rather than products that rely on sensory perceptions or emotional responses (i.e., experience products), AI may be better suited (Gray & Wegner, 2012).