Revisiting Civil Liability Attribution for Organizational Use of Intelligent Contract Management Systems

Document Type : Original Article

Authors

1 PhD in Private Law, Department of Private Law, Faculty of Law, Tarbiat Modares University, Tehran, Iran.

2 Assistant Professor, Department of Private Law, Faculty of Law and Political Science, University of Mazandaran, Babolsar, Iran.

Abstract
The increasing deployment of artificial intelligence systems in organizational contract management has challenged traditional models of civil liability. In such systems, risk assessment, clause evaluation, and contractual recommendations are conducted through algorithmic processes that may become structurally integrated into the formal decision-making framework of legal entities. When harm occurs, classical doctrines—whether based on individual fault, vicarious liability, or liability arising from things—do not always adequately address the complexity of technology-driven decision-making. Focusing on the organizational use of intelligent contract management systems under Iranian law, and distinguishing between contractual and non-contractual liability, this article examines how liability should be attributed where non-contractual harm occurs. It argues that when an AI system plays an effective and systematic role in the formation of a legal entitys will, the resulting decision is directly attributable to the organization itself, without disregarding the fault-based foundations of Iranian civil liability law. In such cases, liability analysis must be conducted at the structural level of the entitys decision-making framework. Accordingly, a theory of organizational (structural) liability—conceived as complementary to traditional doctrines—offers a coherent basis for effective compensation and prevents gaps in attribution in the context of AI-assisted contractual governance.

Keywords


- Persian
1. Ebrahimi, Jiran, (1404), Civil Liability for Robots and Artificial Intelligence: Legal Challenges and Solutions in the Age of New Technologies, Legal Civilization Quarterly, 8 (25), 371-394.
2. Ehsangar, Noura, Yazdanian, Ali (1404), Analysis of Civil Liability Arising from the Performance of Artificial Intelligence with the Criteria of Ownership or Maintenance with a Comparative Study in French Law, Private Law Research, 14 (53), 53-90.
3. Irvani, Ali, Khorsand, Ali and Mohammadi, Seyyed Baqer (1404), Jurisprudential Foundations of Civil Liability Arising from the Application of Artificial Intelligence, Teachings of Civil Jurisprudence, doi: 10.30513/cjd.2025.7030.2066
4. Bagheri, Parviz, (1404), Legal Personality and Civil Liability of Artificial Intelligence; Legal Difficulties and Solutions, Private Law Research, 13 (51), 47-82.
5. Bahrami Ahmadi, Hamid (2015), Civil Law 4, Civil Liability, Mizan Legal Foundation.
6. Haji Esmaili, Milad (2014), Challenges of Civil Liability of Artificial Intelligence in the Iranian Legal System with a View to the Regulation of the European Union, Quarterly Journal of State and Law, 5(1), No. 15, 81-98.
7. Darabpour, Mehrab (2017), Civil Law 4, Non-Contractual Liabilities, Majd.
8. Zakerinia, Hanieh (2014), The Nature and Basis of Civil Liability Arising from Artificial Intelligence in the Law of Iran and the Countries of the European Union, Private Law, 20 (1), 135-152.
9. Zakerinia, Hanieh and Gholampour, Zahra (2014), Reasonable and Conventional Algorithms and Strengthening the Theory of Attribution of Civil Liability of Artificial Intelligence, Law of New Technologies, 5(9), 155-168.
10. Razavi, Seyed Mehdi and Daemi, Mohammad Esmaeil (2014), Civil Liability Due to Errors in Smart Contracts, Legal Studies in Cyberspace, 3(2), 15-28.
11. Safaei and Rahimi (2015), Civil Liability (Extra-Contractual Obligations), Samt.
12. Abbaslou, Bakhtiar (2015), Civil Liability (With a Comparative Perspective), Mizan Legal Foundation.
13. Esaiasi Tafreshi, Mohammad (2016), Law of Commercial Companies, Volume One, Tarbiat Modares University Press.
14. Katouzian, Naser (2015), Extra-Contractual Obligations (Civil Liability), Volume One, Tehran University Press.
15. Katouzian, Naser (2015), Non-Contractual Obligations (Civil Liability), Volume 2, Tehran University Press.
16. Katouzian, Naser (2009), The Evolution of the Concept of Fault in Civil Liability Law, Private Law Studies, 39 (1), 189-214.
17. Katouzian, Naser (2009), Civil Law Course (General Rules of Contract Law), Volume 2, Joint Stock Publishing Company.
18. Ghasemzadeh, Morteza (2011), Non-Contractual Obligations and Civil Liability, Mizan Legal Foundation.
- English
19. Betts, K. D., & Jaep, K. R. (2016). The dawn of fully automated contract drafting: Machine learning breathes new life into a decades-old promise. Duke L. & Tech. Rev., 15, 216-233.
20. Calo,R. (2015) Robotics and the Lessons of Cyberlaw, 103 Calif. L.Rev. 513, University of Washington School of Law UW Law Digital Commons, https://digitalcommons.law.uw.edu/faculty-articles
21. Corrales Compagnucci, M., Fenwick, M., & Haapio, H. (2022). Digital technology, future lawyers and the computable contract designer of tomorrow. Research Handbook on Contract Design. Edward Elgar Publishing. Available at SSRN: https://ssrn.com/abstract=3908370
22. Dabass, J., & Dabass, B. S. (2018). Scope of artificial intelligence in law. Preprints, 2018060474. doi:10.20944/preprints201806.0474.v1
23. Dale, R. (2019). Law and word order: NLP in legal technology. Natural Language Engineering, 25(1), 211-217. Cambridge University Press. doi:https://doi.org/10.1017/S1351324918000475
24. Foster, W. E., & Lawson, A. L. (2018). When to praise the machine: The promise and perils of automated transactional drafting. South Carolina Law Review, 69(3), 597-634.
25. Martin-Bariteau, F., & Pavlović, M. (2021) “AI and Contract Law”, Florian Martin-Bariteau & Teresa Scassa, eds., Artificial Intelligence and the Law in Canada (Toronto: LexisNexis Canada), ch. 3. https://ssrn.com/abstract=3730385
26. Giuffrida, I., Lederer, F., & Vermeys, N. (2018). A legal perspective on the trials and tribulations of AI: How artificial intelligence, the internet of things, smart contracts, and other technologies will affect the law. Case Western Reserve Law Review, 68(3), 747-781.
27. Gravett, W. H. (2020). Is the dawn of the robot lawyer upon us? The fourth industrial revolution and the future of lawyers. Electronic Law Journal (PER/PELJ), 23, 1-37. doi: http://dx.doi.org/10.17159/1727-
28. Gredka-Ligarska, I. (2025) Employer's Vicarious Liability for Damage Caused by an AI Worker: Comparative Law Perspective. Utrecht Law Review, 21(1), 36–48. DOI: https://doi.org/10.36633/ulr.1063
29. Hendrycks, D., Burns, C., Chen, A., & Ball, S. (2021). CUAD: An expert-annotated NLP dataset for legal contract review. Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS 2021) Track on Datasets and Benchmarks.
30. Herbosch, Maarten and Mertens, Floris, The Future of Mergers & Acquisitions? Risk Allocation in AI-Guided Transactions (2025). Forthcoming in European Business Organization Law Review 2026., Available at SSRN: https://ssrn.com/abstract=5275610 or http://dx.doi.org/10.2139/ssrn.5275610
31. Semmler, S., & Rose, Z. (2017). Artificial Intelligence: Application today and implications tomorrow. Duke L. & Tech. Rev., 16, 85-99.
32. Vladeck, D.C. (2014). Machines Without Principals: Liability y Rules and Artificial Intelligence, 89 Wash. L.Rev. 150-117.
Available at: https://digitalcommons.law.uw.edu/wlr/vol89/iss1/6
33. Wendehorst C. (2022), Liability for Artificial Intelligence: The Need to Address Both Safety Risks and Fundamental Rights Risks. In: Voeneky S, Kellmeyer P, Mueller O, Burgard W, eds. The Cambridge Handbook of Responsible Artificial Intelligence: Interdisciplinary Perspectives. Cambridge Law Handbooks. Cambridge University Press; 187-209.
34. Williams, S. (2019). Predictive contracting. Golden Gate University School of Law, 2019(2), 621-695.
35. Yamane, N. (2020). Artificial Intelligence in the Legal Field and the Indispensable Human Element Legal Ethics Demands. Geo. J. Legal Ethics, 33, 877-890.
Volume 1, Issue 2 - Serial Number 2
Autumn 2025
Pages 93-113

  • Receive Date 27 July 2025
  • Revise Date 29 August 2025
  • Accept Date 29 November 2025
  • First Publish Date 22 December 2025
  • Publish Date 22 December 2025