AI and Human Expertise in Defining Job Fit

This research article investigates the role of artificial intelligence (AI) in defining soft skills essential for job performance and compares the effectiveness of large language models (LLMs) with subject matter experts (SMEs). It highlights the challenges hiring managers face in consistently identifying soft skills, which are often defined informally. The study aims to provide data-driven job profiles that accurately specify critical soft skills and evaluates the convergence between AI-generated assessments and SME ratings. Using O*NET as a reference framework, the research analyzes the performance of three AI models—Google Gemini, OpenAI GPT-3.5, and OpenAI GPT-4—in identifying important soft skills across various job families. The findings indicate that while LLMs can reliably identify key soft skills, they struggle with more nuanced requirements that depend on contextual knowledge. The study emphasizes the importance of human expertise in roles requiring interpretation and suggests the development of job templates that combine AI insights with SME judgments to enhance hiring processes.