Exploring the Impact of Artificial Intelligence on Digital Transformation of Businesses: A Bibliometric Analysis

Bellami, R., Dey, K., Hind, M. (2019). AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. IBM Journal of Research and Development, Vol.63, Issue 4/5. 10.1147/JRD.2019.2942287Search in Google Scholar

Belhadi, A., Mani., V., Kamble, S.S., Khan, S.A.R. & Verma, S. (2021). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation. Annals of Operations Research, 333:627–652. https://doi.org/10.1007/s10479-021-03956-xSearch in Google Scholar

Bertino, E., Kantarcioglu, M., Akcora, C.G., Samtani, S., Mittal, S. & Gupta, M. (2021). AI for Security and Security for AI. CODASPY ‘21: Proceedings of the Eleventh ACM Conference on Data and Application Security and Privacy, 333-334. https://doi.org/10.1145/3422337.3450357Search in Google Scholar

Brundage, M., Avin, S., Wang, J., Belfield, H., & Hadfield, G. (2020). Toward trustworthy AI development: Mechanisms for supporting verifiable claims. https://arxiv.org/abs/2004.07213Search in Google Scholar

Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42. https://doi.org/10.1007/s11747-019-00696-0Search in Google Scholar

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070Search in Google Scholar

European Parliament & The Council of the European Union (2024). REGULATION (EU) 2024/1689 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL. https://eurlex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689Search in Google Scholar

Holmström, J. (2022). From AI to digital transformation: The AI readiness framework. Business Horizons, 65(3), 329-339. https://doi.org/10.1016/j.bushor.2021.03.006Search in Google Scholar

Ivančić, L., Suša Vugec, D., & Bosilj Vukšić, V. (2019). Robotic process automation: systematic literature review. In Business Process Management: Blockchain and Central and Eastern Europe Forum: BPM 2019 Blockchain and CEE Forum, Vienna, Austria, September 1–6, 2019, Proceedings 17, 280-295. https://doi.org/10.1007/978-3-030-30429-4_19Search in Google Scholar

Kirby, A. (2023). Exploratory bibliometrics: using VOSviewer as a preliminary research tool. Publications, 11(1), 10. https://doi.org/10.3390/publications11010010Search in Google Scholar

Kraus, S., Durst, S., Ferreira, J. J., Veiga, P., Kailer, N., & Weinmann, A. (2022). Digital transformation in business and management research: An overview of the current status quo. International Journal of Information Management, 63, 102466. https://doi.org/10.1016/j.ijinfomgt.2021.102466Search in Google Scholar

Martínez-López, F. J., & Casillas, J. (2013). Artificial intelligence-based systems applied in industrial marketing: An historical overview, current and future insights. Industrial Marketing Management, 42(4), 489-495. https://doi.org/10.1016/j.indmarman.2013.03.001Search in Google Scholar

McKinsey (2024). The state of AI in early 2024: Gen AI adoption spikes and starts to generate value. Retrieved from https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-aiSearch in Google Scholar

Nkomo, N. & Mupa, M. N. (2024). The Impact of Artificial Intelligence on Predictive Customer Behaviour Analytics in E-commerce: A Comparative Study of Traditional and AI-driven Models. Iconic Research and Engineering Journals, Vol.8, Issue 5. https://www.irejournals.com/formatedpaper/1706548.pdfSearch in Google Scholar

OECD (2023). OECD AI Principles. https://oecd.ai/en/Search in Google Scholar

Öztürk, O., Kocaman, R., & Kanbach, D. K. (2024). How to design bibliometric research: an overview and a framework proposal. Review of managerial science, 1-29. https://doi.org/10.1007/s11846-024-00738-0Search in Google Scholar

Paul, J., Ueno, A., Dennis, C., Alamanos, E., Curtis, L., Foroudi, P., ... & Wirtz, J. (2024). Digital transformation: A multidisciplinary perspective and future research agenda. International Journal of Consumer Studies, 48(2), e13015. https://doi.org/10.1111/ijcs.13015Search in Google Scholar

Ransbotham, S., Kiron, D., Gerbert, P., & Reeves, M. (2017). Reshaping business with artificial intelligence: Closing the gap between ambition and action. MIT Sloan Management Review, 59(1), n/a-0. Retrieved from https://www.proquest.com/scholarly-journals/reshaping-business-with-artificial-intelligence/docview/1950374030/se-2Search in Google Scholar

Reier Forradellas, R. F., & Garay Gallastegui, L. M. (2021). Digital transformation and artificial intelligence applied to business: Legal regulations, economic impact and perspective. Laws, 10(3), 70. https://doi.org/10.3390/laws10030070Search in Google Scholar

Rudin, C. (2019). Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence, 1(5), 206-215. https://doi.org/10.1038/s42256-019-0048-xSearch in Google Scholar

Ruiz-Real, J. L., Uribe-Toril, J., Torres, J. A., & De Pablo, J. (2021). Artificial intelligence in business and economics research: Trends and future. Journal of Business Economics and Management, 22(1), 98-117. https://doi.org/10.3846/jbem.2020.13641Search in Google Scholar

Tîrnovanu, A. C., Năstase, M., Șișu, J. A., & Mujaya, J. (2023). Digital Transformation during COVID-19 Pandemic–a Bibliometric Analysis. In Proceedings of the International Conference on Business Excellence (Vol. 17, No. 1, pp. 2070-2084). Sciendo. https://doi.org/10.2478/picbe-2023-0181Search in Google Scholar

Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Managing digital transformation, 28 (2), 18-144. https://doi.org/10.1016/j.jsis.2019.01.003Search in Google Scholar