Mapping AI Adoption across Europe: A Cluster Analysis of National Responsibility
References
- AI Watch. (2020). Artificial Intelligence in Europe: Trends and Developments. European Commission.
- Brynjolfsson, E., & McAfee, A. (2017). Machine, Platform, Crowd: Harnessing Our Digital Future. W.W. Norton & Company.
- Bughin, J., et al. (2019). Tackling Europe’s Gap in AI and Digital Transformation. McKinsey & Company.
- Chui, M., Manyika, J., & Miremadi, M. (2018). AI Adoption and Workforce Readiness. McKinsey Global Institute.
- European Commission. (2021). Europe’s Digital Decade: Digital Compass 2030.
- European Commission. (2020). The AI Policy Framework in Europe.
- Everitt, B., Landau, S., Leese, M., & Stahl, D. (2011). Cluster Analysis (5th ed.). Wiley.
- Floridi, L., & Cowls, J. (2019). A Unified Framework of Five AI Ethics Principles. Minds and Machines, 29(4), 563-591.
- Frey, C. B., & Osborne, M. (2017). The Future of Employment: How Susceptible are Jobs to Computerization? Technological Forecasting and Social Change, 114, 254-280.
- Hagendorff, T. (2020). The Ethics of AI Ethics: An Evaluation of Guidelines. Nature Machine Intelligence, 2(6), 423-429.
- ITU. (2021). Measuring Digital Development: Facts and Figures 2021. International Telecommunication Union.
- Jobin, A., Ienca, M., & Vayena, E. (2019). The Global Landscape of AI Ethics Guidelines. Nature Machine Intelligence, 1(9), 389-399.
- Liao, S. H. (2019). Clustering Analysis in Digital Transformation Research. Journal of Business Research, 101, 145-157.
- Manyika, J., et al. (2017). Artificial Intelligence: The Next Digital Frontier? McKinsey Global Institute.
- McKinsey Global Institute. (2018). Notes from the AI Frontier: Modeling the Impact of AI on the World Economy.
- OECD. (2020). Artificial Intelligence, Digital Transformation and Productivity. Organization for Economic Co-operation and Development.
- OECD. (2021). Digital Economy Outlook 2021. Organization for Economic Co-operation and Development.
- Pajarinen, M., Rouvinen, P., & Ylhäinen, I. (2019). AI and Work: Evidence from the Nordic Countries. ETLA Working Papers.
- Ribeiro-Navarrete, S., Saura, J. R., & Palacios-Marqués, D. (2021). Towards a New Era of Mass Data Collection: Assessing Digitalization through Cluster Analysis. Journal of Innovation & Knowledge, 6(1), 15-23.
- Veale, M., & Binns, R. (2017). Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 1-14.
- Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2020). Artificial Intelligence and the Public Sector— Applications and Challenges. International Journal of Public Administration, 43(7), 596-616.
- World Economic Forum. (2020). The Future of Jobs Report 2020. World Economic Forum.
DOI: https://doi.org/10.2478/picbe-2025-0119 | Journal eISSN: 2558-9652
Language: English
Page range: 1532 - 1545
Published on: Jul 24, 2025
Published by: Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Related subjects:
© 2025 Eduard-Mihai Manta, Maria Cristina Geambasu, Ioana Birlan, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.