A data-driven approach to aligning academic offerings with industry needs for business and economy in SloveniaAndonovikj, Viktor (Avtor) Boshkoska, Biljana Mileva (Avtor) Redek, Tjaša (Avtor) Boškoski, Pavle (Avtor) labour marketdecision makingartificial intelligencedecision supportlanguage modelsdata-driven insightsThe success of graduates and their employability hinge on a crucial alignment between the skills and competencies sought by employers and those possessed by job seekers. This study delves into the extent to which the competencies cultivated in the curricula of selected Slovenian universities align with the ever-evolving requirements of the Slovenian labour market. Employing a combination of LLaMA-2-7B-chat, a generative language model, and the multilingual Sentence Transformer, a contextual language model, we identify skill gaps and pinpoint the most in-demand competencies that align with those generated by the faculty. This data-driven approach offers a roadmap for confirming the relevance and enhancing the university curricula, thus fostering a stronger connection between education and employment as well as improving the labour market efficiency.20242025-03-04 15:53:16Članek v reviji167625UDK: 331.5ISSN pri članku: 1246-0125DOI: 10.1080/12460125.2024.2354587COBISS_ID: 195922179sl