Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive Analysis

Artificial Intelligence (AI) tools can revolutionize literature review practices by transforming the research landscape towards more efficient and reliable review processes. While conducting literature can be challenging and time-consuming, there is a plethora of AI powered tools which uncover poten...

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Main Authors: Phumzile Dorcus Mogoale, Agnieta Beatrijs Pretorius, Refilwe Constance Mogase, Mmatshuene Anna Segooa
Format: Article
Language:English
Published: Informatics Department, Faculty of Computer Science Bina Darma University 2025-03-01
Series:Journal of Information Systems and Informatics
Subjects:
Online Access:https://journal-isi.org/index.php/isi/article/view/1035
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author Phumzile Dorcus Mogoale
Agnieta Beatrijs Pretorius
Refilwe Constance Mogase
Mmatshuene Anna Segooa
author_facet Phumzile Dorcus Mogoale
Agnieta Beatrijs Pretorius
Refilwe Constance Mogase
Mmatshuene Anna Segooa
author_sort Phumzile Dorcus Mogoale
collection DOAJ
description Artificial Intelligence (AI) tools can revolutionize literature review practices by transforming the research landscape towards more efficient and reliable review processes. While conducting literature can be challenging and time-consuming, there is a plethora of AI powered tools which uncover potential solutions to the challenge. AI tools may reduce the time spent on repetitive tasks, allowing scholars to focus more on critical analysis and interpretation. Due to the rising abundance of AI tools, it is difficult to decide which AI tools are best for individual research problems or projects. While concerns exist around the ethical and quality consequences of using AI. The study aims to explore the usage of AI tools on the systematics literature review process, specifically focusing on their effectiveness in various stages and ethical concerns. IEEE and MDPI Journal papers from 2020 to 2024 were reviewed using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. RobotReviewer, Covidence and EPPI-Reviewer are AI tools commonly used. These AI tools are designed to support different aspects of the systematic literature review process by offering capabilities such as problem formulation, literature search, inclusion screening and quality assessment. AI tools demonstrate improved effectiveness of literature searches, screening processes and  data extraction. Language and content presentation, incorrect citation and plagiarism, grammar and spelling errors may be ren when utilizing AI. Concerns related to data quality, biases, and the need for human oversight were identified.
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spelling doaj-art-0e49bfcb1dac4082a2d12209f337193d2025-08-20T02:14:19ZengInformatics Department, Faculty of Computer Science Bina Darma UniversityJournal of Information Systems and Informatics2656-59352656-48822025-03-017187088810.51519/journalisi.v7i1.10351035Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive AnalysisPhumzile Dorcus Mogoale0Agnieta Beatrijs Pretorius1Refilwe Constance Mogase2Mmatshuene Anna Segooa3Tshwane University of TechnologyTshwane University of TechnologyTshwane University of TechnologyTshwane University of TechnologyArtificial Intelligence (AI) tools can revolutionize literature review practices by transforming the research landscape towards more efficient and reliable review processes. While conducting literature can be challenging and time-consuming, there is a plethora of AI powered tools which uncover potential solutions to the challenge. AI tools may reduce the time spent on repetitive tasks, allowing scholars to focus more on critical analysis and interpretation. Due to the rising abundance of AI tools, it is difficult to decide which AI tools are best for individual research problems or projects. While concerns exist around the ethical and quality consequences of using AI. The study aims to explore the usage of AI tools on the systematics literature review process, specifically focusing on their effectiveness in various stages and ethical concerns. IEEE and MDPI Journal papers from 2020 to 2024 were reviewed using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. RobotReviewer, Covidence and EPPI-Reviewer are AI tools commonly used. These AI tools are designed to support different aspects of the systematic literature review process by offering capabilities such as problem formulation, literature search, inclusion screening and quality assessment. AI tools demonstrate improved effectiveness of literature searches, screening processes and  data extraction. Language and content presentation, incorrect citation and plagiarism, grammar and spelling errors may be ren when utilizing AI. Concerns related to data quality, biases, and the need for human oversight were identified.https://journal-isi.org/index.php/isi/article/view/1035artificial intelligence, systematic literature review, software tools, prisma
spellingShingle Phumzile Dorcus Mogoale
Agnieta Beatrijs Pretorius
Refilwe Constance Mogase
Mmatshuene Anna Segooa
Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive Analysis
Journal of Information Systems and Informatics
artificial intelligence, systematic literature review, software tools, prisma
title Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive Analysis
title_full Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive Analysis
title_fullStr Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive Analysis
title_full_unstemmed Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive Analysis
title_short Evaluating the Efficacy of AI Tools in Systematic Literature Reviews: A Comprehensive Analysis
title_sort evaluating the efficacy of ai tools in systematic literature reviews a comprehensive analysis
topic artificial intelligence, systematic literature review, software tools, prisma
url https://journal-isi.org/index.php/isi/article/view/1035
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