Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx

Introduction<p>Artificial intelligence (AI) is transforming organizational knowledge management (KM) by leveraging techniques such as machine learning, neural networks, and fuzzy logic to enhance knowledge discovery, capture, storage, and sharing. While this shift promises improved efficiency...

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Tác giả chính: Teona Gelashvili-Luik (21659153) (author)
Tác giả khác: Peeter Vihma (21659156) (author), Ingrid Pappel (21659159) (author)
Được phát hành: 2025
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author Teona Gelashvili-Luik (21659153)
author2 Peeter Vihma (21659156)
Ingrid Pappel (21659159)
author2_role author
author
author_facet Teona Gelashvili-Luik (21659153)
Peeter Vihma (21659156)
Ingrid Pappel (21659159)
author_role author
dc.creator.none.fl_str_mv Teona Gelashvili-Luik (21659153)
Peeter Vihma (21659156)
Ingrid Pappel (21659159)
dc.date.none.fl_str_mv 2025-07-04T05:14:40Z
dc.identifier.none.fl_str_mv 10.3389/frai.2025.1595930.s001
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Data_Sheet_1_Navigating_the_AI_revolution_challenges_and_opportunities_for_integrating_emerging_technologies_into_knowledge_management_systems_Systematic_literature_review_docx/29475803
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Knowledge Representation and Machine Learning
artificial intelligence
emerging technologies
knowledge management
organizational performance
digital transformation
dc.title.none.fl_str_mv Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description Introduction<p>Artificial intelligence (AI) is transforming organizational knowledge management (KM) by leveraging techniques such as machine learning, neural networks, and fuzzy logic to enhance knowledge discovery, capture, storage, and sharing. While this shift promises improved efficiency and personalization, it also poses challenges related to data quality, employee resistance, and alignment with existing workflows.</p>Methods<p>This study presents a systematic literature review (SLR) of 40 peer-reviewed publications focused on the integration of AI in KM. The review follows PRISMA guidelines and includes thematic coding to identify patterns, critical success factors, and knowledge gaps.</p>Results<p>Findings indicate that successful AI-enabled KM depends on strong leadership commitment, adaptable governance structures, and context-sensitive technology selection. AI’s role is evolving from supporting routine tasks to enabling dynamic, real-time knowledge flows. The review also highlights a critical need to balance automation with human oversight.</p>Discussion<p>Key gaps were identified in understanding cost–benefit trade-offs, ethical implications, and governance mechanisms. These insights suggest directions for future research focused on practical, accountable, and empirically validated KM strategies. As part of an ongoing research project, the synthesized findings will inform the design of future empirical studies. The evidence suggests that, when strategically implemented, AI can serve as a competitive enabler in knowledge-driven organizations.</p>
eu_rights_str_mv openAccess
id Manara_4f1d06a013baa8c7abd34eb631f19e7e
identifier_str_mv 10.3389/frai.2025.1595930.s001
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/29475803
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docxTeona Gelashvili-Luik (21659153)Peeter Vihma (21659156)Ingrid Pappel (21659159)Knowledge Representation and Machine Learningartificial intelligenceemerging technologiesknowledge managementorganizational performancedigital transformationIntroduction<p>Artificial intelligence (AI) is transforming organizational knowledge management (KM) by leveraging techniques such as machine learning, neural networks, and fuzzy logic to enhance knowledge discovery, capture, storage, and sharing. While this shift promises improved efficiency and personalization, it also poses challenges related to data quality, employee resistance, and alignment with existing workflows.</p>Methods<p>This study presents a systematic literature review (SLR) of 40 peer-reviewed publications focused on the integration of AI in KM. The review follows PRISMA guidelines and includes thematic coding to identify patterns, critical success factors, and knowledge gaps.</p>Results<p>Findings indicate that successful AI-enabled KM depends on strong leadership commitment, adaptable governance structures, and context-sensitive technology selection. AI’s role is evolving from supporting routine tasks to enabling dynamic, real-time knowledge flows. The review also highlights a critical need to balance automation with human oversight.</p>Discussion<p>Key gaps were identified in understanding cost–benefit trade-offs, ethical implications, and governance mechanisms. These insights suggest directions for future research focused on practical, accountable, and empirically validated KM strategies. As part of an ongoing research project, the synthesized findings will inform the design of future empirical studies. The evidence suggests that, when strategically implemented, AI can serve as a competitive enabler in knowledge-driven organizations.</p>2025-07-04T05:14:40ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.3389/frai.2025.1595930.s001https://figshare.com/articles/dataset/Data_Sheet_1_Navigating_the_AI_revolution_challenges_and_opportunities_for_integrating_emerging_technologies_into_knowledge_management_systems_Systematic_literature_review_docx/29475803CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/294758032025-07-04T05:14:40Z
spellingShingle Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx
Teona Gelashvili-Luik (21659153)
Knowledge Representation and Machine Learning
artificial intelligence
emerging technologies
knowledge management
organizational performance
digital transformation
status_str publishedVersion
title Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx
title_full Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx
title_fullStr Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx
title_full_unstemmed Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx
title_short Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx
title_sort Data Sheet 1_Navigating the AI revolution: challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review.docx
topic Knowledge Representation and Machine Learning
artificial intelligence
emerging technologies
knowledge management
organizational performance
digital transformation