Impact of AI in Recruitment and Talent Acquisition - Sasi, Kiran Parasa (Human Resource and Leadership Journal, 2024)
Purpose: This paper explores the multifaceted impact of AI on the recruitment process, highlighting its role in automating routine tasks, analyzing vast amounts of data for better decision-making, and providing predictive analytics to anticipate hiring needs. AI-driven tools, such as chatbots and applicant tracking systems, streamline candidate sourcing and screening, significantly reducing time-to-hire and improving the quality of hires. Methodology: To assess the impact of AI in recruitment and talent acquisition, this study employs a mixed-methods approach, combining both qualitative and quantitative research methods to provide a comprehensive understanding of the topic. The methodology involves the following Literature Review, Data Collection, Case Studies, Data Analysis, Integration of Findings, Validation and Reliability and Ethical Considerations. By employing this rigorous methodology, the study aims to provide a comprehensive and reliable assessment of the impact of AI in recruitment and talent acquisition, offering valuable insights for HR professionals, policymakers, and researchers in the field. Findings: This paper highlights the key benefits AI brings to recruitment processes, such as efficiency improvements, better decision-making, and enhanced candidate experience, as well as the challenges like data privacy concerns and algorithmic bias. Unique Contribution to Theory, Policy, and Practice: This study advances the theoretical understanding of AI in recruitment by integrating technology adoption and HR management theories. It provides significant policy implications, emphasizing robust data privacy measures, ethical AI use, and inclusive hiring practices. For practitioners, it offers actionable insights on streamlining recruitment processes, enhancing candidate experience, and managing AI adoption challenges. It also shares best practices for bias mitigation in AI algorithms, ensuring fair and equitable recruitment practices.