ABSTRACT
This bibliographic study explores the transformative power of Artificial Intelligence (AI) in Human Resources (HR) to improve Diversity, Equity, and Inclusion (DEI) practices in the present context. As organizations across the globe adapt to the dynamic changes in workforce expectations and technological capabilities, AI surfaces as a powerful catalyst in the reimagining of equitable workplaces. Based on more than 42 research articles indexed in the Scopus database from 2020 until 2024 and feeding this data to VOSveiwer tool to generate the required visual representations. This paper explores how AI applications including but not limited to machine learning algorithms, natural language processing tools and predictive analytics are being used to enhance fairness in recruitment, reduce human bias, increase employee engagement and ensure inclusive performance evaluations. Indian enterprises have actively adopted AI tools for almost all functions of the HR ecosystem to underscore a commitment to DEI imperatives in recent years. To combat discriminatory tendencies, which may arise from subconscious human bias are now integrated as standard HR practices such as automated resume screening, sentiment analysis of employee feedback, and data-driven DEI dashboards. The literature shows that when deployed ethically and responsibly, AI can greatly help achieve DEI goals. Anonymized, AI-powered recruitment processes have increased representation from marginalized groups, and employee sentiment analysis tools have provided insight into team dynamics and inclusivity gaps. AI-powered DEI dashboards have also empowered real-time tracking of diversity metrics and supported such informed decision-making at leadership levels. But many scholars warn that algorithmic decision-making is not neutral by nature. If AI tools would not be adapted to the local socio-economic, cultural, and linguistic diversity, there is a risk of reproducing or amplifying existing biases. With a shared vision around the need for localized training data, robust ethical oversight of required tech design, and continuous human-AI collaboration in HR practices.
