Gender Bias in AI-Based Recruitment Platforms: Evidence from Private Business Organization

Artificial Intelligence (AI)–based recruitment platforms are increasingly adopted by private business organizations to enhance efficiency, objectivity, and data-driven hiring decisions. Despite these advantages, concerns regarding algorithmic gender bias have emerged as a critical ethical and managerial challenge. This study investigates gender bias perceptions in AI-based recruitment platforms within private business organizations. A quantitative research design was employed using primary data collected from 24 respondents who experienced AI-enabled hiring processes. Structured questionnaires based on a five-point Likert scale were used to examine perceptions related to fairness, transparency, usability, and gender neutrality of AI systems. The findings reveal that while AI significantly improves recruitment efficiency and standardization, respondents express moderate concerns regarding fairness and transparency, indicating the potential presence of gender bias during screening and evaluation stages. The study further identifies that human involvement remains essential in minimizing algorithmic discrimination and ensuring equitable hiring outcomes. The research recommends the adoption of hybrid recruitment models integrating AI capabilities with ethical oversight, bias auditing mechanisms, and inclusive algorithm design. The study contributes to the growing discourse on responsible AI implementation by highlighting the importance of fairness, accountability, and gender equality in technology-driven recruitment practices. Index Terms— Artificial Intelligence, Gender Bias, AI Recruitment, Algorithmic Fairness, HR Analytics, Ethical AI