Ethical Dimensions of Artificial Intelligence in the Digital Entrepreneurship Ecosystem: A Systematic Literature Review
Article Sidebar
Main Article Content
Abstract
The rapid adoption of artificial intelligence (AI) in digital entrepreneurship has created new opportunities for innovation, efficiency, and data-driven decision-making, while simultaneously raising ethical concerns related to fairness, transparency, privacy, accountability, and explainability. This study presents a systematic literature review to examine the ethical dimensions of AI within the digital entrepreneurship ecosystem. Guided by the PRISMA 2020 protocol and the PICO framework, searches were conducted across Web of Science, Scopus, and IEEE Xplore for studies published between 2020 and 2026. From 512 initially identified articles, 24 studies met the inclusion criteria and quality assessment requirements. The selected studies were analyzed using thematic coding, narrative synthesis, and quality-based evidence mapping to identify recurring ethical dimensions, operational mechanisms, and governance gaps. The findings reveal four dominant ethical problem clusters: algorithmic fairness in entrepreneurial decision-making, transparency deficits in black-box AI systems, data privacy and cybersecurity vulnerabilities, and weak accountability mechanisms in AI governance. The review further shows that responsible AI frameworks, explainability techniques, bias audits, data governance protocols, and risk-based regulatory approaches are central mechanisms for translating ethical principles into practice. The findings contribute to responsible AI scholarship, digital entrepreneurship governance, and policy-oriented debates by offering practical guidance for entrepreneurs, regulators, and researchers concerned with ethical AI adoption in resource-constrained business environments. This study provides an evidence-based roadmap for strengthening ethical, accountable, and socially responsible AI implementation in digital entrepreneurship ecosystems.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
With this statement, I hereby grant and transfer to RUBINSTEIN all exclusive copyright ownership rights for the aforementioned work. This includes, but is not limited to, the rights to publish, republish, modify, distribute, transmit, sell, or use the work and related materials globally, in whole or in part, in any language, and through any form of media whether electronic, printed, or any other medium known now or developed in the future. RUBINSTEIN also reserves the right to grant permission or license third parties to carry out any of these actions. I acknowledge that RUBINSTEIN will hold these exclusive rights from the date the article is accepted for publication. I also recognize that RUBINSTEIN, as the copyright holder, has the sole authority to license and permit the reproduction of the article. However, I understand that any other proprietary rights related to the work (such as patents or other rights to a process or procedure) remain with the author. Furthermore, I acknowledge that RUBINSTEIN allows authors to use their articles in accordance with the applicable Creative Commons license.
References
Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., ... & Herrera, F. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. https://doi.org/10.1016/j.inffus.2019.12.012
Balasubramaniam, N., Kauppinen, M., Rannisto, A., & Hiekkanen, K. (2023). Transparency and explainability of AI systems: From ethical guidelines to requirements. Information and Software Technology, 159, 107197. https://doi.org/10.1016/j.infsof.2023.107197
Bogdanova, O. (2025). Teaching Responsible AI Entrepreneurship: Experiences from the Erasmus+ Pathfinder Project. Proceedings of the 6th International Conference on AI Research (ICAIR 2025), 40–47. https://doi.org/10.34190/icair.5.1.4376
Buzinskiene, R., Miceikiene, A., & Saura, J. R. (2026). The knowledge of ethical AI decision-making: A behavioral economics perspective. Journal of Innovation & Knowledge, 14. https://doi.org/10.1016/j.jik.2026.100967
Chinnaraju, A. (2025). AI-driven strategic decision-making on innovation: Scalable, ethical approaches and AI agents for startups. World Journal of Advanced Research and Reviews, 25(02), 2219–2248. https://doi.org/10.30574/wjarr.2025.25.2.0575
Cristofaro, M., Baiocco, G., & Muldoon, J. (2026). Entrepreneurial decision-making in the age of AI: Sector knowledge at the balance of intuition and analysis. Technology in Society, 85, 103200. https://doi.org/10.1016/j.techsoc.2025.103200
Florea, A., & Hatos, R. (2026). Sustainability-Oriented Digital Transformation Under Industry 4.0: Managerial Perceptions of Digitalization and AI. Sustainability, 18(5), 1–24. https://doi.org/10.3390/su18052570
Floridi, L., Cowls, J., King, T. C., & Taddeo, M. (2021). How to Design AI for Social Good: Seven Essential Factors. Science and Engineering Ethics, 26, 1771–1796. https://doi.org/10.1007/s11948-020-00213-5
Ganuthula, V. R. R., & Indian, I. I. T. J. (2025). The Solo Revolution: A Theory of AI-Enabled Individual Entrepreneurship. ArXiv. https://doi.org/10.48550/arXiv.2502.00009
Hmieleski, K. M., & Lerner, D. A. (2023). Ethics and Entrepreneurship: A Study of Entrepreneur Ethical Orientation and New Venture Performance. Journal of Business Venturing, 38(1), 106172.
Huang, X., Kou, T., & Zhou, Q. (2026). Embedding AI ethics in the data lifecycle: A framework for enterprise AI governance. Technology in Society, 86, 103261. https://doi.org/10.1016/j.techsoc.2026.103261
Huseynov, V., & Nematova, U. (2026). Ethical Issues Regarding the Use of Artificial Intelligence in Business Enterprises. International Journal of Research and Scientific Innovation (IJRSI), XII, 768–780. https://doi.org/10.51244/IJRSI.2025.12120065
Ibrahim, S. M., Alshraideh, M. A., Leiner, M., & Aldajani, I. M. (2024). Artificial intelligence ethics: Ethical consideration and regulations from theory to practice. IAES International Journal of Artificial Intelligence, 13(3), 3703–3714. https://doi.org/10.11591/ijai.v13.i3.pp3703-3714
Irawan, H., Riwurohi, Y. E., & Irawan, I. (2025). Kecerdasan Buatan: Studi Kasus di Indonesia. JMIK (Jurnal Mahasiswa Ilmu Komputer), 6(2). https://doi.org/10.24127/ilmukomputer.v6i2.9545
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1, 389–399. https://doi.org/10.1038/s42256-019-0088-2
Kamil, A. Z. R., & Khoirunnisa, S. (2025). Optimalisasi Bisnis Lewat Penggunaan Artificial Intelligence dalam Perspektif Etika Islam. JURIKO: Jurnal Ilmu Ekonomi, 1(2), 39–48.
López, A. P., Gorneanu, A. E., & Martín, L. G. (2026). Ethics, Transparency, and Consumer Trust in AI-Enabled Pricing: Implications for Sustainable Technology Entrepreneurship. Sustainable Technology and Entrepreneurship, 5. https://doi.org/10.1016/j.stae.2026.100131
McGrath, Q., Hevner, A. R., & Vreede, G. De. (2024). Managing Ethical Risks of Artificial Intelligence in Business Applications. TechRxiv. https://doi.org/10.36227/techrxiv.170905835.50964792/v1
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2022). A survey on bias and fairness in machine learning. ACM Computing Surveys, 54(6), 1–35. https://doi.org/10.1145/3457607
Mittelstadt, B., Russell, C., & Wachter, S. (2022). Explaining explanations in AI. FAccT '18: Proceedings of the Conference on Fairness, Accountability, and Transparency, 279–288.
Mostafiz, I., Gali, N., Uddin, F., & Hughes, M. (2026). Generative Artificial Intelligence and Ethicality in Entrepreneurs' Creativity. Journal of Business Ethics. https://doi.org/10.1007/s10551-026-06301-z
Mardiah, D., Renggani, F. P., Aripin, N. S., & Irwansyah, R. (2025). Kewirausahaan Berbasis Teknologi: Memanfaatkan AI untuk Pertumbuhan Usaha. Karimah Tauhid, 4(7), 5086–5093. https://doi.org/10.30997/karimahtauhid.v4i7.19853
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Systematic Reviews, 10(89), 1–11. https://doi.org/10.1186/s13643-021-01626-4
Popa, I., & Breazu, A. (2025). A new framework for the artificial intelligence entrepreneurship ecosystem. Journal of Innovation & Knowledge, 10. https://doi.org/10.1016/j.jik.2025.100850
Saqib, H. M., & Amin, H. (2026). Comparative analysis of AI regulation for fintech cybersecurity and privacy in the European Union and Qatar. Discover Artificial Intelligence, 5(59). https://doi.org/10.1007/s44163-025-00736-5
Uriarte, S., & Huertas-Barros, E. (2026). Artificial intelligence technologies and entrepreneurship: A hybrid literature review. Review of Managerial Science, 20, 251–299. https://doi.org/10.1007/s11846-025-00839-4
Abstract views: 6
/ 
PDF downloads: 3