The scientific monograph “AI-Driven Digital Transformation: Perspectives from a Business School” has been published by Routledge. The volume offers a multifaceted view of AI-driven digital transformation from the perspective of a renowned business school. It comprises 23 chapters divided into six thematic areas: decision support, data processing, marketing and product development, supply chains, finance, and broader social issues.
The monograph presents practical examples of how artificial intelligence (AI) can be applied within business school units, featuring accessible case studies that highlight both the benefits and potential risks associated with adopting new technologies. The authors emphasize the role of AI as a strategic enabler of innovation and the importance of business schools as catalysts for change in the digital economy. The publication also underscores ethical considerations and the need for collaboration between academia, industry, and policymakers. It serves as a valuable resource for researchers and students interested in AI, technology, innovation management, and business education. It will also appeal to business school leaders responsible for institutional strategies, program designers, curriculum specialists, and practitioners seeking guidance on implementing AI solutions within their organizations.
The editors of the monograph are scholars affiliated with the Department of Information Systems (DIS):
- Prof. Witold Abramowicz, former head of DIS (in 1990-2024),
- Prof. Marek Kowalkiewicz, former DIS member, currently serves as the head of the Department of Digital Economy at the Business School of Queensland University of Technology (Australia) and director of the QUT Centre for the Digital Economy,
- Prof. Krzysztof Węcel, head of DIS.
The volume also includes chapters co-authored by members of our Department:
- Krzysztof Węcel, Witold Abramowicz and Marek Kowalkiewicz: “Business Schools in the Era of Artificial Intelligence”
- Szczepan Górtowski, Daniel Korzeniowski and Emil Gościniak: “The Use of Generative AI in Automated Assessment of Data Models in Business Intelligence Systems”
- Krzysztof Węcel and Marcin Sawiński: “Bridging Knowledge Graphs and Large Language Models: Enhancing Text Generation and Knowledge Extraction”
- Szczepan Górtowski, Elżbieta Lewańska and Ihor Muzyka: “Enhancing Visual Reports Through Generative AI Image-Reading Capabilities”
- Remigiusz Napiecek, Milena Stróżyna and Elżbieta Lewańska: “Advancing EU VAT Systems with AI and E-Invoicing”