Impact of AI-Based Recruitment on Hiring Efficiency

The rapid growth of Artificial Intelligence (AI) has changed traditional recruitment practices by improving hiring efficiency and decision-making. AI-based recruitment systems use technologies like machine learning, natural language processing, and data analytics to automate key hiring tasks such as job posting, resume screening, candidate shortlisting, and interview scheduling. This study looks at how AI-based recruitment affects hiring efficiency in organisations, focusing on time savings, cost savings, and quality of hire. The research relies on primary data gathered from HR professionals and employees in different sectors, along with secondary data from journals and reports. The analysis uses statistical tools like percentage analysis, weighted average scores, and chi-square tests. The findings show that AI-driven recruitment cuts down hiring time by automating repetitive tasks and effectively managing large numbers of applications. AI tools also boost accuracy in candidate matching by reducing human bias and supporting objective decision-making. However, the study also finds challenges, including the absence of human judgment, data privacy issues, and resistance to adopting new technology among recruiters. Despite these hurdles, the overall results suggest that AI-based recruitment positively impacts hiring efficiency when combined with human oversight. The study concludes that AI-based recruitment systems are useful for improving recruitment efficiency. It recommends that organisations take a balanced approach, combining AI technology with human skills to achieve the best hiring results.