Innovative recruitment strategies in the IT sector: A review of successes and failures

  • Funmilayo Aribidesi Ajayi
  • Chioma Ann Udeh
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Abstract

This study systematically reviews and analyzes the impact of innovative recruitment strategies on diversity and inclusion within the Information Technology (IT) sector. Given the rapid technological advancements and the increasing demand for skilled professionals, IT firms are at the forefront of adopting novel recruitment practices. The main objective of this research is to explore how these innovations influence the diversity of the IT workforce and to identify best practices for promoting inclusivity. Employing a systematic literature review and content analysis, the study examines peer-reviewed articles, industry reports, and relevant grey literature published within the last decade. Key insights reveal a significant shift towards the use of artificial intelligence (AI) and data analytics in recruitment processes, aiming to enhance efficiency and reduce biases. However, challenges such as potential algorithmic bias, privacy concerns, and the need for human oversight in automated recruitment are identified. The study concludes with actionable recommendations for IT firms, recruiters, and policymakers to ensure that recruitment innovations contribute positively to workforce diversity and inclusivity. It advocates for a balanced approach that leverages technology while addressing ethical considerations and promoting equal opportunities for underrepresented groups. Future research directions include exploring the long-term effects of these recruitment strategies on organizational performance and further examining the ethical implications of AI in recruitment. This study contributes to a deeper understanding of the evolving landscape of IT recruitment and its implications for diversity and inclusion initiatives.

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Funmilayo Aribidesi Ajayi, & Chioma Ann Udeh. (2024). Innovative recruitment strategies in the IT sector: A review of successes and failures. Magna Scientia Advanced Research and Reviews, 10(2), 150–165. https://doi.org/10.30574/msarr.2024.10.2.0057

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