From policy to practice: the regulation and implementation of generative AI in Swedish higher education institutes

Abstract Background The rapid development of generative artificial intelligence (GenAI) is reshaping higher education by offering innovative solutions in course design, assessment, and learning experiences. Despite its potential, GenAI integration poses ethical, pedagogical, and practical challenges, but also a risk of academic misconduct. This study explores how Swedish higher education institutions (HEIs) are addressing GenAI through guidelines, policy documents, and public website information. Methods A qualitative manifest content analysis for objectivity and consistency was conducted on GenAI-related documents and website information from Swedish HEIs. Forty-nine institutions were contacted, with 36 providing relevant data. Data collection involved email correspondence and systematic searches on public websites. Results Few formal GenAI guidelines exist across Swedish HEIs. Independent institutions were more likely to have established guidelines for both staff and students, whereas universities or university colleges often provided more GenAI-related information on their websites. Five categories were identified: Good academic practice; GenAI use and governance in education; Information governance; Ethical and social impact; and GenAI essentials, the latter unique to websites. Good academic practice was the most emphasized, focusing on transparency, responsibility, and the challenges of GenAI-related misconduct. Conclusions Taken together, GenAI integration in higher education remains early and uneven, with some institutions implementing formal guidelines while others are still developing policies. This inconsistency calls for national directives to balance GenAI´s benefits with ethical concerns, promote GenAI literacy, and ensure equitable access. Rapid technological change challenges HEIs to update policies that ensure academic integrity and fairness. Future research should foster collaborative policy development among HEIs, policymakers, and technology providers.

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Publication Details

Journal
International Journal for Educational Integrity
Published
2025-07-20
DOI
https://doi.org/10.1007/s40979-025-00195-6
Citations
3
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
6.85

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article

From policy to practice: the regulation and implementation of generative AI in Swedish higher education institutes

Anastasios Grigoriadis, Maria Christidis, Nikolaos Christidis, Abhishek Kumar et al.
3 citations
International Journal for Educational Integrity
Big Data and Business Intelligence
6.85
article

From policy to practice: the regulation and implementation of generative AI in Swedish higher education institutes

Anastasios Grigoriadis, Maria Christidis, Nikolaos Christidis, Abhishek Kumar, Charlotte Erhardt, Helena Kullenberg
article en
3 citations

Abstract

Abstract Background The rapid development of generative artificial intelligence (GenAI) is reshaping higher education by offering innovative solutions in course design, assessment, and learning experiences. Despite its potential, GenAI integration poses ethical, pedagogical, and practical challenges, but also a risk of academic misconduct. This study explores how Swedish higher education institutions (HEIs) are addressing GenAI through guidelines, policy documents, and public website information. Methods A qualitative manifest content analysis for objectivity and consistency was conducted on GenAI-related documents and website information from Swedish HEIs. Forty-nine institutions were contacted, with 36 providing relevant data. Data collection involved email correspondence and systematic searches on public websites. Results Few formal GenAI guidelines exist across Swedish HEIs. Independent institutions were more likely to have established guidelines for both staff and students, whereas universities or university colleges often provided more GenAI-related information on their websites. Five categories were identified: Good academic practice; GenAI use and governance in education; Information governance; Ethical and social impact; and GenAI essentials, the latter unique to websites. Good academic practice was the most emphasized, focusing on transparency, responsibility, and the challenges of GenAI-related misconduct. Conclusions Taken together, GenAI integration in higher education remains early and uneven, with some institutions implementing formal guidelines while others are still developing policies. This inconsistency calls for national directives to balance GenAI´s benefits with ethical concerns, promote GenAI literacy, and ensure equitable access. Rapid technological change challenges HEIs to update policies that ensure academic integrity and fairness. Future research should foster collaborative policy development among HEIs, policymakers, and technology providers.

International Journal for Educational IntegrityVol. 21(1)
Sophiahemmet University College (SE), Karolinska Institutet (SE)
Karolinska Institutet
Openalex Percentile: Top 3%
Big Data and Business Intelligence
6.85
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