Artificial Intelligence (AI) has transformed recruitment processes across industries by enhancing efficiency, reducing biases, and improving candidate-job fit. This study evaluates the application of AI in employee recruitment decision-making within Nigeria’s telecom industry, focusing on MTN Nigeria, one of the largest telecommunications companies in Africa. In particular, the research evaluates how AI tools, such as machine learning algorithms, predictive analytics, and natural language processing, are employed to streamline and enhance the recruitment experience. By assessing MTN's use of AI-driven platforms for screening, shortlisting, and decision-making, the study examines the potential benefits and challenges of integrating such technologies in the Nigerian telecom industry. The research examines the extent to which AI-driven tools influence hiring efficiency, fairness, and quality. It employs a case study methodology, utilizing both qualitative and quantitative data to assess AI’s impact on recruitment outcomes. This research aims to provide an in-depth analysis of how AI can improve the efficiency, accuracy, and fairness of recruitment practices while reducing bias, costs, and time. Moreover, it investigates the broader implications of AI adoption in terms of its effects on recruitment transparency, employee satisfaction, and overall organizational performance. Findings will provide insights for industry stakeholders, HR professionals, and policymakers in optimizing AI applications in talent acquisition and will also contribute valuable insights for other telecom companies in Nigeria and Africa at large, assisting them in adopting AI for a more strategic, data-driven approach to talent acquisition. Through this evaluation of MTN’s recruitment practices, the study seeks to highlight both the transformative potential and limitations of AI in the fast-evolving telecom sector.