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“Generative AI literacy across education and business: competencies, obstacles, and benefits—a systematic literature review”

Authors’ abstract

Abstract This systematic literature review analyses AI literacy, focusing on the required competencies for, the obstacles arising from, and the benefits of, Generative AI (GenAI) in the fields of education and business. The analysis uses the PRISMA 2020 methodology with data from the SCOPUS and ERIC databases. A total of 538 articles were identified; of these, 206 were included after the full-text screening phase. Of those 206, only 33% (education) and 29% (business) were based on empirical research, highlighting the predominantly conceptual state of research. Using a combination of inductive coding and GenAI (ChatGPT-4o) validation, we identified AI literacy as a multidimensional concept comprising technical competencies (e.g. algorithmic literacy and prompt engineering), personal and interpersonal competencies (e.g. adaptability and collaboration), and ethical and critical thinking competencies (e.g. awareness of bias and ethical reflection). While educational literature emphasised pedagogical applications such as adaptive feedback and inclusive curriculum design, business research focused on process automation and data-driven decision-making. Top three identified obstacles included hallucinations, ethics and plagiarism, which manifested differently in contexts such as student assessment and personnel selection. Addressing these challenges will require targeted training modules, ethical governance structures, and institutional support in the form of faculty development programmes or workplace reskilling initiatives. Top three identified benefits of GenAI literacy training are described as critical thinking, personalized teaching and learning and personalized feedback across sectors.

Paper

Authors
M. Reicho, K. Otrel-Cass, M. Ebner, B. Brünner, D. Freinhofer, J. Irfan
Publication date
2026

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Creative Commons Attribution 4.0 International
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