Digital teaching skills in artificial intelligence applied to university research: Systematic review

Abstract

Within the framework of the Fourth Industrial Revolution, artificial intelligence (AI) has become a key tool in higher education research processes. However, significant challenges remain regarding the development of faculty digital competencies, limiting the effective integration of these technologies into academia. This qualitative study adopted an integrative systematic review design based on PRISMA 2020 guidelines. A total of 30 studies, published between 2020 and 2025 in the Scopus and SciELO databases, were analyzed based on thematic, temporal, and open-access criteria. The analysis addressed three objectives: identifying digital competence levels among university teachers who integrate AI in their research, analyzing training strategies related to AI in university research, and examining the benefits and limitations of its use in research processes. Findings revealed heterogeneous levels of digital competence with a predominance of basic levels, the emergence of adaptive and personalized training strategies, and a positive assessment of AI's potential contrasted with ethical and structural limitations. It is concluded that strengthening digital competencies among faculty through contextualized training strategies is a strategic action to enhance research quality in universities, aligned with SDG 4 on quality education.