Building a Generative AI Toolkit for Leveraging Knowledge Processes: The GAIK Project Report
While Generative AI (GenAI) has the potential to transform knowledge work, its proper application in business remains a challenge. To obtain benefits from GenAI, companies must navigate a complex landscape of technologies and best practices for their implementation. The selection, integration, and implementation of specific GenAI solutions are complex, particularly for small and medium-sized enterprises. To address this issue, we have launched a research and development project named GAIK (Generative AI-enhanced Knowledge Management) to develop a business-oriented GenAI toolkit to improve three processes: knowledge capture, synthesis, and access. The toolkit will include software components (modules and code libraries), guidelines, process models, templates, and reusable knowledge models, enabling companies and technology providers to develop easy-to-deploy knowledge management solutions using business data. This paper describes the envisioned toolkit, its potential use cases, and the required research activities to develop and apply it.
Authors
- Jukka Remes (ORCID: https://orcid.org/0000-0003-1685-8346)
- Umair Ali Khan (ORCID: https://orcid.org/0000-0002-8560-764X)
- Yiheng Wu
- Dmitry Kudryavtsev (ORCID: https://orcid.org/0000-0002-1798-5809)
- Krista Sorri (ORCID: https://orcid.org/0000-0003-0062-8677)
- Lidia Pivovarova (ORCID: https://orcid.org/0000-0002-0026-9902)
- Roman Yangarber (ORCID: https://orcid.org/0000-0001-5264-9870)
- Janne Kauttonen (ORCID: https://orcid.org/0000-0003-2432-5072)
- Marko Seppänen (ORCID: https://orcid.org/0000-0003-2106-9528)
- Jussi Myllärniemi (ORCID: https://orcid.org/0000-0002-2846-0426)
- Timo Kaski
- Anne Wuokko
Institutions
- University of Helsinki (FI)
- Tampere University (FI)
- Haaga-Helia University of Applied Sciences (FI)
Publication Details
- Journal
- European Conference on Knowledge Management
- Published
- 2025-08-29
- DOI
- https://doi.org/10.34190/eckm.26.2.3701
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- European Regional Development Fund