Building a Generative AI Toolkit for Leveraging Knowledge Processes: The GAIK Project Report

Authors

  • Dmitry Kudryavtsev Haaga-Helia University of Applied Sciences https://orcid.org/0000-0002-1798-5809
  • Umair Ali Khan Haaga-Helia University of Applied Sciences
  • Janne Kauttonen Haaga-Helia University of Applied Sciences
  • Timo Kaski Haaga-Helia University of Applied Sciences
  • Jukka Remes Haaga-Helia University of Applied Sciences
  • Anne Wuokko Haaga-Helia University of Applied Sciences
  • Roman Yangarber Helsinki University
  • Lidia Pivovarova Helsinki University
  • Yiheng Wu Helsinki University
  • Marko Seppänen Tampere university
  • Jussi Myllärniemi Tampere university
  • Krista Sorri Tampere university

DOI:

https://doi.org/10.34190/eckm.26.2.3701

Keywords:

knowledge management, generative AI, toolkit, software product lines, design science research

Abstract

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.

Author Biographies

Dmitry Kudryavtsev, Haaga-Helia University of Applied Sciences

PhD, Senior researcher, Digital transition & AI

He is an experienced professional in knowledge engineering, knowledge management, business analysis, enterprise modeling, digital business design and applied AI, proficient in different roles in academia and industry: researcher, consultant, lecturer, team lead, expert, scientific advisor, startup co-founder and reviewer.

 

Umair Ali Khan, Haaga-Helia University of Applied Sciences

PhD, Senior researcher, Digital transition & AI

Janne Kauttonen, Haaga-Helia University of Applied Sciences

PhD, Senior researcher, Digital transition & AI

Timo Kaski, Haaga-Helia University of Applied Sciences

PhD, Research Area Director, Digital transition & AI

Jukka Remes, Haaga-Helia University of Applied Sciences

PhD, Lecturer, Digital transition & AI

Anne Wuokko, Haaga-Helia University of Applied Sciences

Lecturer, Digital Services

Roman Yangarber, Helsinki University

PhD, Professor, Department of Digital Humanities

Lidia Pivovarova, Helsinki University

PhD, University Researcher, Department of Digital Humanities

Yiheng Wu, Helsinki University

PhD student, Department of Digital Humanities

Marko Seppänen, Tampere university

PhD, Dean, Faculty of Management and Business

Jussi Myllärniemi, Tampere university

PhD, University Instructor, Faculty of Management and Business

Krista Sorri, Tampere university

PhD, University Instructor, Faculty of Management and Business

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Published

2025-08-29