Demystifying literature review in the AI Era

Updating the SSF method with Generative Artificial Intelligence support

Authors

DOI:

https://doi.org/10.5195/biblios.2025.1317

Keywords:

Literature review, SSF method, Generative Artificial Intelligence, Narrative review

Abstract

Objective. The study addresses the lack of a method that combines systematic reviews with Generative Artificial Intelligence (AI). It proposes improvements to the SSF (Systematic Search Flow) method, introducing new review categories and incorporating AI tools.

Method. It analyzed 44 types of literature reviews organized into seven distinct families with a narrative review approach. Based on this, the SSF method was updated with the support of generative AI.

Results. It presents the evolution of the SSF, which incorporates generative AI to optimize search strategy, article selection and scientific writing. This results in faster reviews by filtering the results and analyzing a large volume of data.

Conclusion. The update of the SSF Method represents a significant advance, offering a systematic and efficient guide for literature reviews. Although generative AI does not replace the critical judgment of the researcher, when guided by experienced researchers, it increases the efficiency of the process, making reviews more robust and methodologically rigorous.

Author Biographies

Helio Aisenberg Ferenhof, Universidade Federal de Santa Catarina

PhD in Production Engineering - PPGEP - UFSC (2015). Specialist in Higher Education Didactics - SENAC/SC (2012). Master in Knowledge Management - PPGEGC - UFSC (2011). MBA E-Business - FGV-RJ (2001). BA in Computer Science - Estácio de Sá University - RJ (1999). Bachelor in Business Administration - UniBF College - PR (2020). Has experience in Project Management, Innovation Management, Knowledge Management, Service Management, Systems Development, Product Development and Information Security. He was a Visiting Professor at the Postgraduate Program in Information and Communication Technologies (PPGTIC) - UFSC Araranguá. Researcher at GEPPS (Product, Process and Service Engineering Group) and NGS (Management Center for Sustainability) at the Federal University of Santa Catarina. Associate Researcher at KIM (Knowledge and Innovation Management), a research group at the University of Skövde (www.his.se). Member of ICAA - Intellectual Capital Accreditation Association (www.icaa.pt). Honorary member of the Red Iberoamericana para el desarrollo y difusión de la investigación educativa AC (https://redesdeinvestigacioneducativa.org/). Working mainly on the following topics: Project Management, Innovation Management, Knowledge at Risk, Knowledge Management, Service Management/Development, Product Management/Development, Stakeholder Management, Governance, Digital Transformation. A professional trained to develop and monitor projects, from the creation of the business model to implementation. He has over 20 years' experience in multinational companies and renowned consultancies.

Roberto Fabiano Fernandes, Universidade Federal de Santa Catarina

Especialista em Engenharia de Projetos de Software (2009), Ciência de Dados (2020), Governança de TI (2021) e Metodologias de Ensino a Distância (2021). Possui mestrado (2012) e doutorado (2017) em Engenharia e Gestão do Conhecimento pela Universidade Federal de Santa Catarina. Atua como avaliador do Sistema Nacional de Avaliação da Educação Superior (BASis) e do Conselho Estadual de Educação de Santa Catarina. Participou do grupo que recebeu o Prêmio Stemmer de Inovação na categoria Governo Inovador em 2022.

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Published

2025-03-21

How to Cite

Ferenhof, H. A., & Fernandes, R. F. (2025). Demystifying literature review in the AI Era: Updating the SSF method with Generative Artificial Intelligence support. Biblios Journal of Librarianship and Information Science, (88), e003. https://doi.org/10.5195/biblios.2025.1317

Issue

No. 88 (2025)

Section

Original

License

Copyright (c) 2025 Helio Aisenberg Ferenhof, Roberto Fabiano Fernandes

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