Does higher education properly prepare graduates for the growing artificial intelligence market? Gaps’ identification using text mining

TLDR

Artificial Intelligence’s rapid rise is reshaping technology professions and creating a demand for new, specialized skills. The study aims to identify skill gaps between AI training in French engineering and business schools and the labor market’s requirements. Researchers extracted AI curriculum content from school websites and job postings, then applied Python‑based natural language processing to mine and analyze the data. They classified AI occupations and defined three skill categories—technical, soft, and interdisciplinary—revealing gaps in certifications, tool mastery, research ability, and ethical awareness, thereby informing curriculum redesign.

Abstract

BACKGROUND: The renewed advent of Artificial Intelligence (AI) is inducing profound changes in the classic categories of technology professions and is creating the need for new specific skills. OBJECTIVE: Identify the gaps in terms of skills between academic training on AI in French engineering and Business Schools, and the requirements of the labour market. METHOD: Extraction of AI training contents from the schools’ websites and scraping of a job advertisements’ website. Then, analysis based on a text mining approach with a Python code for Natural Language Processing. RESULTS: Categorization of occupations related to AI. Characterization of three classes of skills for the AI market: Technical, Soft and Interdisciplinary. Skills’ gaps concern some professional certifications and the mastery of specific tools, research abilities, and awareness of ethical and regulatory dimensions of AI. CONCLUSIONS: A deep analysis using algorithms for Natural Language Processing. Results that provide a better understanding of the AI capability components at the individual and the organizational levels. A study that can help shape educational programs to respond to the AI market requirements.