Highlighting AI Competencies: A Qualitative Analysis Approach Using AI Agents

Abstract

The rapid advancement of Artificial Intelligence (AI) is reshaping the job market, creating a demand for new skills and competencies in AI and machine learning (ML). As academic institutions strive to align educational programs with industry needs, a clear understanding of job market expectations becomes essential. This study employs a qualitative, grounded theory approach, enhanced by large language models (LLMs), to analyze job postings related to AI. Using a custom coding framework and AI agent arbitration, we extract and classify the competencies sought by employers into eight major categories. Key findings emphasize the significance of technical skills, including system analysis, architecture, programming languages, and machine learning, as well as soft skills such as collaboration and leadership. The results offer critical insights for curriculum developers and accreditation bodies, providing a scalable, auditable methodology for aligning academic programs with real-world AI job market demands.

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