SCDI AI Business Lab Celebrates Landmark 2024–2025 Publication Record
The SCDI AI Business Lab has achieved a significant milestone with its research output in 2024 and 2025. Over this period, the Lab’s researchers published 13 peer-reviewed journal articles to date, in a range of academic journals. This accomplishment underlines not only the quality of the Lab’s research but also its thematic breadth, addressing critical issues in artificial intelligence from multiple angles. The SCDI AI Business Lab was founded in 2020 through a donation from the Kempe Foundation, and had a distinct ambition to provide tangible value for partners in the public and private sector.
Taken together, these 13 studies illustrate this ambition by addressing three overarching themes in AI research and application:
- Technological Innovation: Several studies explore how emerging AI technologies can drive innovation. For instance, the recent JMIS paper examines generative AI as a “boundary resource” that can reshape platform ecosystems, while another discusses techniques like prompt engineering to spur creativity in the age of AI. The Lab also contributed insights on low-code and no-code platforms as tools for digital innovation, highlighting new opportunities and challenges these technologies bring to organizations.
- Organizational Transformation: A core focus of the Lab’s work is how AI is transforming business and organizational practices. Researchers from the Lab developed an “AI Transformation Framework” to guide organizations on their AI adoption journey, published in a leading business journal. Another study offers guidance on how organizations can innovate with conversational AI (e.g. ChatGPT), reflecting practical strategies for business leaders. Additionally, the Lab’s publications examine how companies navigate the hype and reality of AI, helping managers balance optimistic possibilities with realistic limitations when implementing AI-driven solutions.
- Societal Impact: Many of the Lab’s publications look beyond the organizational level, considering the broader impact of AI on society and communities. One article provides a public-sector perspective by fusing domain knowledge with machine learning, illustrating how government agencies can leverage AI while respecting expertise and context. Another investigates AI’s role in education, detailing a teaching approach that uses no-code AI tools to demystify machine learning for students – an important step in building future AI literacy. The Lab’s researchers also delve into sustainability and ethics, such as studying digital platforms for the circular economy and analyzing “myth vs. hype” in AI management discourse.
Across all these publications, the SCDI AI Business Lab demonstrates a blend of theoretical advancement and practical relevance. The Lab’s findings are informing scholarly debates in information systems and management while simultaneously offering actionable insights for practitioners in industry and the public sector. From frameworks that help organizations structure their AI initiatives, to empirical studies on innovation processes and critical reflections on AI narratives, the Lab’s output contributes to a deeper understanding of how AI technologies can be effectively and responsibly integrated into business and society.
References (2024–2025 Publications):
Mayer, A. S., Kostis, A., Strich, F., & Holmström, J. (2025). Shifting Dynamics: How Generative AI as a Boundary Resource Reshapes Digital Platform Governance. Journal of Management Information Systems
Holmström, J. & Magnusson, J. (2025). Navigating the Organizational AI Journey: The AI Transformation Framework. Business Horizons
Sundberg, L. & Holmström, J. (2025). Innovating by Prompting: How to Facilitate Innovation in the Age of Generative AI. Business Horizons
Holmström, J. & Carroll, N. (2025). How Organizations Can Innovate with ChatGPT. Business Horizons.
Carroll, N., Holmström, J., & Matook, S. (2024). Low-Code and No-Code for Digital Transformations: Challenges and Future Opportunities. MIS Quarterly Executive, 23(3), Article 2.
Sundberg, L. & Holmström, J. (2024). Fusing Domain Knowledge with Machine Learning: A Public Sector Perspective. Journal of Strategic Information Systems, 33(3), 101848.
Kostis, A., Nicol, C., Lindström, J., & Holmström, J. (2024). Scaling Digital Platforms for Circular Economy: The Evolution of Boundary Work Frames Among Davids and Goliaths in Corporate Incubation.Technological Forecasting & Social Change, 208, 123651.
Kostis, A., Lindström, J., Nair, S., & Holmström, J. (2024). Too Much AI Hype, Too Little Emphasis on Learning? Entrepreneurs Designing Business Models Through Learning-by-Conversing with Generative AI. IEEE Transactions on Engineering Management, 71(4), 15278–15291.
Carroll, N., Holmström, J., Stahl, B. C., & Fabian, N. E. (2024). It’s a Balancing Act: Navigating Hype and Dystopia of Artificial Intelligence. Communications of the Association for Information Systems, 55(1), 32.
Holmström, J. (2024). A Layered Organizing Logic for Generative AI Evolution: Insights from Digital Infrastructure Theory. Scandinavian Journal of Information Systems, 36(1), 93–104.
Holmström, J., Kostis, A., Galariotis, E., Roubaud, D., & Zopounidis, C. (2024). Stalled Data Flows in Digital Innovation Networks: Underlying Mechanisms and the Role of Related Variety. Industrial Marketing Management, 121, 16–26.
Koukouvinou, P. & Holmström, J. (2024). AI Management Beyond Myth and Hype: A Systematic Review and Synthesis of the Literature. Pacific Asia Journal of the Association for Information Systems, 16(2), 1–21.
Sundberg, L. & Holmström, J. (2024). Teaching Tip: Using No-Code AI to Teach Machine Learning in Higher Education. Journal of Information Systems Education, 35(1), 56–66.