Abstract:

There is limited research that has critically explored how algorithmic bias may reproduce or intensify gender inequality, particularly for women entrepreneurs performing in digitally mediated markets. The current literature continues to discuss AI efficiency, personalization, and consumer analytics. However, there is limited information on biased data structures, automated targeting, and platform mechanisms that influence gender visibility and market access. The authors aimed to explore the extent to which algorithmic bias impacts gender inequality in AI-driven marketing systems, with particular attention to consumer targeting and entrepreneurial visibility. The authors used a case study approach. Data were collected from three SMEs and 33 interviewees, including SME owners, marketing managers, and digital communication specialists. Moreover, thematic analysis was conducted to identify recurring patterns. This research was grounded in the Social Construction of Technology Theory and Feminist Technology Theory. The results offer insights into how AI-driven marketing systems may unintentionally privilege certain consumer segments, content styles, and entrepreneurial profiles. This was a pilot study, thus limited in generalizability; however, the interview results offer a rich contextual understanding for future research. The novelty lies in connecting algorithmic bias, gender inequality, AI-driven marketing, and entrepreneurial visibility within SME contexts. Hence, this offers value to entrepreneurs, marketing practitioners, platform designers, and policymakers by providing transparent, ethically governed AI marketing systems that support fair digital market participation.