The main aim of this project is to assess the impact and viability of AI-powered hiring solutions in transforming traditional recruitment processes. Students will evaluate how AI tools streamline candidate screening, resume parsing, interview scheduling, and predictive assessments for cultural and role fit. The goal is to identify the tangible benefits such as reduced hiring time, cost-efficiency, and improved quality of hire as well as the risks and challenges such as ethical concerns, bias in algorithms, and employee trust. The expected outcome is a business case that helps HR leaders decide when, where, and how to effectively adopt AI tools in their hiring workflows, ensuring alignment with organizational talent strategies and compliance standards.
To complete this project, students will begin by conducting a literature review of AI trends in human resource management, focusing specifically on recruitment. Student will identify and evaluate popular AI hiring platforms such as HireVue, Pymetrics, Eightfold.ai, and LinkedIn Talent Insights in terms of features, usability, and business value.
Students will study real-world case studies from companies that have implemented AI in their HR processes and analyze improvements in time-to-hire, cost-per-hire, and candidate experience. They may conduct interviews or surveys with HR managers and talent acquisition professionals to collect qualitative insights on AI adoption barriers and enablers. Additionally, students will benchmark traditional hiring workflows against AI-augmented ones using key HR metrics and create a SWOT analysis to assess strategic fit.
The final deliverables will include a structured business case report that outlines ROI estimations, change management strategies, risk mitigation measures, and policy recommendations for responsible AI use in hiring. A final presentation will summarize strategic insights and best practices for enterprise-level AI-enabled HR transformation.
