The rapid advancement of Generative Artificial Intelligence (GenAI) is creating new professional roles that demand specialized skills. This study presents a structured model to assess the "GenAI Readiness" of university degree programs in Italy, determining how well they align with the competencies required for emerging AIrelated professions. The assessment framework evaluates programs based on a five-level ranking system, covering roles such as GenAI Specialist Data Scientist, Prompt Engineer, Ethical AI Specialist, AI Product Manager, and Creative AI Specialist. The methodology involves automated comparative text analysis, using AI tools to match course descriptions against predefined competency standards. Our results highlight gaps and strengths in existing curricula, offering valuable insights for both students selecting academic programs and companies seeking AI talent. By quantifying readiness levels, this study contributes to bridging the gap between higher education and the rapidly evolving demands of the AI industry.
An Approach for Assessing the GenAI Readiness of Degree Programs in Italian Universities / Russo, Dario; Falorsi, Piero; Manzi, Giancarlo; Alleva, Giorgio. - (2026), pp. 402-402. ( CARMA 2025 Roma ).
An Approach for Assessing the GenAI Readiness of Degree Programs in Italian Universities
Piero FalorsiSecondo
;Giancarlo Manzi
Penultimo
;Giorgio AllevaUltimo
2026
Abstract
The rapid advancement of Generative Artificial Intelligence (GenAI) is creating new professional roles that demand specialized skills. This study presents a structured model to assess the "GenAI Readiness" of university degree programs in Italy, determining how well they align with the competencies required for emerging AIrelated professions. The assessment framework evaluates programs based on a five-level ranking system, covering roles such as GenAI Specialist Data Scientist, Prompt Engineer, Ethical AI Specialist, AI Product Manager, and Creative AI Specialist. The methodology involves automated comparative text analysis, using AI tools to match course descriptions against predefined competency standards. Our results highlight gaps and strengths in existing curricula, offering valuable insights for both students selecting academic programs and companies seeking AI talent. By quantifying readiness levels, this study contributes to bridging the gap between higher education and the rapidly evolving demands of the AI industry.| File | Dimensione | Formato | |
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