Design and Enhancing Recruitment Processes: A Comparative Analysis of AI-Driven Automation Versus Traditional Methods

Abstract

The recruiting environment is changing dramatically as more organizations use Artificial Intelligence (AI) to expedite hiring procedures. This study compares AI-driven recruiting automation against traditional recruitment approaches, examining the efficiency, obstacles, and consequences on organizational results. Traditional approaches sometimes rely on manual processes, which are time-consuming and prone to human bias. In contrast, AI-powered technologies such as resume screening algorithms, predictive analytics, and automated interview platforms offer increased speed, scalability, and consistency. However, new technologies have issues, such as ethical considerations, algorithmic biases, and the possible depersonalization of the recruiting process. This study uses a combination of qualitative and quantitative data to assess the effectiveness of AI in resolving inefficiencies inherent in old approaches while remaining fair and inclusive. The findings aim to provide actionable insights for HR professionals seeking to optimize their recruitment strategies in a technology-driven world