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Ai Technologies and Contractual Obligations: Challenges in Legal Identification and Risk Sharing

https://doi.org/10.26794/1999-849X-2026-19-4-183-192

Abstract

The significance of this research lies in the fast-paced digitalization of the economy and the absence of a legal definition for AI contracts in Russian legislation, leading to risks for those involved in contractual agreements. This research examines the subject of legal considerations surrounding AI in contractual settings, covering automated transactions, evidence of algorithmic choices, and liability distribution. The study aims to pinpoint systemic flaws in laws and enforcement, then suggest solutions. The methodological basis of the study includes a formal legal analysis of arbitration court rulings from 2022 to 2026, a comparative legal method (analysis of EU and US approaches), a systemic analysis of doctrinal approaches, a legal forecasting method, a content analysis of scientific publications, and a method for interpreting legal norms as they relate to new technological phenomena. First, the scientific novelty comes from the authors’ classification of AI-involved contracts, which is based on the algorithm’s autonomy (passive tool, assistant, autonomous executor); second, in the original system of distributed liability between the developer, operator, owner, and user; and, thirdly, in specific proposed amendments to the Civil Code of the Russian Federation (Articles 153.1, 1079.1). Russian courts generally don’t consider smart contracts as standalone legal facts. They usually require written proof of the parties’ intentions, which poses challenges for autonomous AI systems. The authors identified various approaches to the admissibility of evidence from distributed ledgers. The paper suggests methods for aligning Russian laws with global AI regulations, drawing on international examples like the 2024 EU AI Regulation and US strategies. As an outcome, the study concluded that high-risk systems require mandatory algorithmic audits and that AI contract “sandboxes” need to be more widely available.

About the Authors

M. V. Demchenko
Financial University under the Government of the Russian Federation
Russian Federation

Maxim V. Demchenko — Cand. Sci. (Law), Assoc. Prof., Head of the Department of Legal Regulation of Economic Activity, Faculty of Law

Moscow



Yu. I. Frolovskaya
Financial University under the Government of the Russian Federation
Russian Federation

Yulia I. Frolovskaya — Cand. Sci. (Law), Assoc. Prof., Assoc. Prof. of the Department of Legal Regulation of Economic Activity, Faculty of Law

Moscow



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Review

For citations:


Demchenko M.V., Frolovskaya Yu.I. Ai Technologies and Contractual Obligations: Challenges in Legal Identification and Risk Sharing. Economics, taxes & law. 2026;19(4):183-192. (In Russ.) https://doi.org/10.26794/1999-849X-2026-19-4-183-192

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ISSN 1999-849X (Print)
ISSN 2619-1474 (Online)