AI-Driven Skill Gap Detection in Recruitment

This paper examines how artificial intelligence (AI) can be used to detect skill gaps in recruitment. By combining natural language processing (NLP), machine learning (ML), and robotic process automation (RPA), modern hiring platforms can match candidates to job requirements more accurately and efficiently. Case studies from companies like Unilever and IBM show improvements in screening speed, candidate experience, and hiring quality. At the same time, the growing use of AI raises challenges related to bias, transparency, and data privacy. We analyze these trade-offs and assess whether the advantages of AI-based skill gap detection outweigh the potential risks in real-world HR contexts.