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Artificial Intelligence in Higher Education: A PRISMA 2020 Review

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Title: Artificial Intelligence in Higher Education: A PRISMA 2020 Review
Language: English
Authors: Mohammed Jaboob, Abdullah M. Al-Ansi (ORCID 0000-0002-1682-3154), Hosam Alden Riyadh (ORCID 0000-0002-9426-5282)
Source: International Journal of Educational Management. 2026 40(1-2):113-132.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 20
Publication Date: 2026
Document Type: Journal Articles
Information Analyses
Education Level: Higher Education
Postsecondary Education
Descriptors: Literature Reviews, Higher Education, Artificial Intelligence, Technology Uses in Education, Educational Research, Educational Trends, Trend Analysis, Barriers, Educational Benefits, Technology Integration, Educational Opportunities, Automation
DOI: 10.1108/IJEM-09-2024-0560
ISSN: 0951-354X
1758-6518
Abstract: Purpose: Artificial Intelligence (AI) is making significant inroads in higher education (HE) institutions, revolutionizing how students learn and instructors teach. With the ability to analyze vast amounts of data quickly, AI can personalize learning experiences for students based on their individual needs and learning styles. The review aims to synthesize the literature regarding opportunities, challenges and current trends of AI in HE. Design/methodology/approach: The fragmented body of knowledge in AI and its adoption in HE was aggregated by conducting this PRISMA 2020 review during 2014-2024, using the Scopus database as a source for literature. Findings: The research findings of 33 primary reviews relevant to the research of AI in HE mapped the main opportunities, challenges and recent trends of AI in HE during this period. Personalized learning, automated feedback and grading, enhanced accessibility and better resource allocation are features of AI opportunities, while infrastructure and internet access, HR skills and ethical concerns about data privacy and security and integrity were the most challenges of AI in HE. Results indicate the exponential increase during the last four years in AI research that reflects the huge changes and development in all aspects of education. Research limitations/implications: This review has some limitations regarding the data selection and analysis. Although PRISMA 2020 guidelines were applied, inclusion and exclusion criteria included many prior kinds of research that were not in HE. Social implications: The implications for higher education functions are to advocate for AI responsibility that addresses social and ethical concerns that have the potential to undermine the effective integration of AI and its opportunities and challenges. Future research should conduct empirical studies on AI and HE and its assessment and evaluation in this context. Originality/value: The review advances the literature by providing the current state of AI in HE, its applications and trends, opportunities and challenges and a research agenda for future works.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1503077
Database: ERIC
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  Data: Artificial Intelligence in Higher Education: A PRISMA 2020 Review
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  Label: Language
  Group: Lang
  Data: English
– Name: Author
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  Data: <searchLink fieldCode="AR" term="%22Mohammed+Jaboob%22">Mohammed Jaboob</searchLink><br /><searchLink fieldCode="AR" term="%22Abdullah+M%2E+Al-Ansi%22">Abdullah M. Al-Ansi</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1682-3154">0000-0002-1682-3154</externalLink>)<br /><searchLink fieldCode="AR" term="%22Hosam+Alden+Riyadh%22">Hosam Alden Riyadh</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9426-5282">0000-0002-9426-5282</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Educational+Management%22"><i>International Journal of Educational Management</i></searchLink>. 2026 40(1-2):113-132.
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  Label: Availability
  Group: Avail
  Data: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
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  Label: Peer Reviewed
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  Data: Y
– Name: Pages
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  Group: Src
  Data: 20
– Name: DatePubCY
  Label: Publication Date
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  Data: 2026
– Name: TypeDocument
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  Data: Journal Articles<br />Information Analyses
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  Label: Education Level
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Literature+Reviews%22">Literature Reviews</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Research%22">Educational Research</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Trends%22">Educational Trends</searchLink><br /><searchLink fieldCode="DE" term="%22Trend+Analysis%22">Trend Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Barriers%22">Barriers</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Benefits%22">Educational Benefits</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Integration%22">Technology Integration</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Opportunities%22">Educational Opportunities</searchLink><br /><searchLink fieldCode="DE" term="%22Automation%22">Automation</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1108/IJEM-09-2024-0560
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0951-354X<br />1758-6518
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: Artificial Intelligence (AI) is making significant inroads in higher education (HE) institutions, revolutionizing how students learn and instructors teach. With the ability to analyze vast amounts of data quickly, AI can personalize learning experiences for students based on their individual needs and learning styles. The review aims to synthesize the literature regarding opportunities, challenges and current trends of AI in HE. Design/methodology/approach: The fragmented body of knowledge in AI and its adoption in HE was aggregated by conducting this PRISMA 2020 review during 2014-2024, using the Scopus database as a source for literature. Findings: The research findings of 33 primary reviews relevant to the research of AI in HE mapped the main opportunities, challenges and recent trends of AI in HE during this period. Personalized learning, automated feedback and grading, enhanced accessibility and better resource allocation are features of AI opportunities, while infrastructure and internet access, HR skills and ethical concerns about data privacy and security and integrity were the most challenges of AI in HE. Results indicate the exponential increase during the last four years in AI research that reflects the huge changes and development in all aspects of education. Research limitations/implications: This review has some limitations regarding the data selection and analysis. Although PRISMA 2020 guidelines were applied, inclusion and exclusion criteria included many prior kinds of research that were not in HE. Social implications: The implications for higher education functions are to advocate for AI responsibility that addresses social and ethical concerns that have the potential to undermine the effective integration of AI and its opportunities and challenges. Future research should conduct empirical studies on AI and HE and its assessment and evaluation in this context. Originality/value: The review advances the literature by providing the current state of AI in HE, its applications and trends, opportunities and challenges and a research agenda for future works.
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  Data: 2026
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  Label: Accession Number
  Group: ID
  Data: EJ1503077
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        Value: 10.1108/IJEM-09-2024-0560
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      – Text: English
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    Subjects:
      – SubjectFull: Literature Reviews
        Type: general
      – SubjectFull: Higher Education
        Type: general
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Educational Research
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      – SubjectFull: Educational Trends
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      – SubjectFull: Technology Integration
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      – SubjectFull: Automation
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      – TitleFull: Artificial Intelligence in Higher Education: A PRISMA 2020 Review
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