Artificial Intelligence (AI) in Revolutionizing Sustainable Recruitment: A Framework for Inclusivity and Efficiency

This study explores the potential of Artificial Intelligence (AI) technologies to advance sustainable recruitment, focusing on both environmental and social sustainability. AI-driven systems, including machine learning (ML) and natural language processing (NLP), offer significant improvements by automating tasks such as resume screening, candidate profiling, and interview scheduling. These technologies reduce resource consumption, eliminate the need for physical interviews and paperwork, and lower the carbon footprint of recruitment processes. Adopting a theoretical and conceptual analysis methodology, this research draws on a comprehensive review of AI applications in recruitment and sustainability frameworks. No primary data was collected; instead, the study utilizes secondary data from academic literature, industry reports, and expert insights. A conceptual framework is developed to illustrate how AI can be systematically integrated into recruitment processes to enhance sustainability, highlighting stages such as data collection, decision-making, and feedback loops to improve AI algorithms over time. The findings suggest that AI can contribute significantly to resource efficiency by digitizing recruitment processes and reducing environmental impacts like travel-related emissions. Moreover, AI enhances social sustainability by promoting diversity and inclusion in hiring, as automated systems reduce biases in candidate selection. Key strategies include adopting energy-efficient AI technologies, ensuring ethical use through algorithm audits, and leveraging feedback mechanisms to optimize AI performance. Policymakers are encouraged to develop regulations promoting transparency and accountability in AI use. Future research should explore AI’s broader role in human resource management, ensuring its sustainability potential is fully realized.