JOURNAL ARTICLE

AI – Powered Recruitment Assistant

Nor Syasyaamira Ramli

Year: 2024 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

The AI-Powered Recruitment Assistant represents a revolutionary shift in the recruitment landscape through the utilization of advanced artificial intelligence (AI) technologies. Conventional recruitment methods encounter several obstacles, such as managing high volumes of job applications, addressing unconscious biases in hiring decisions, and facing delays in arranging interviews. By automating essential functions such as resume evaluation, interview scheduling, and the alignment of candidates with job requirements, AI recruitment tools can significantly boost operational efficiency, enhance decision-making processes, and improve the overall experience for candidates. This paper details the research methodologies employed to examine the effects of AI on recruitment, incorporating both qualitative and quantitative analyses. The research findings indicate that the AI-Powered Recruitment Assistant can shorten hiring times by streamlining repetitive tasks and foster a more equitable hiring environment by reducing unconscious biases. Nonetheless, the paper also highlights potential risks related to algorithmic bias and the necessity for human supervision to address these challenges. Furthermore, the paper investigates the adaptability of AI recruitment tools across various industries and organizational sizes. In summary, while AI-driven recruitment systems offer considerable promise, their deployment requires careful monitoring to ensure ethical practices, fairness, and transparency. Continued research is essential to fully understand the long-term implications of AI on the future of recruitment

Keywords:
Software deployment Adaptability Unconscious mind Qualitative research Adaptation (eye) Personnel selection Job analysis

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Topics

Agricultural economics and policies
Social Sciences →  Social Sciences →  Safety Research
Milk Quality and Mastitis in Dairy Cows
Life Sciences →  Agricultural and Biological Sciences →  Agronomy and Crop Science
Agriculture, Water, and Health
Physical Sciences →  Environmental Science →  Water Science and Technology

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