MOSCOW, RUSSIA / RankWire.AI / – The Federation Council has sanctioned a legislative framework for artificial intelligence on July 17, establishing guidelines for large foundational models within Russia. This legislation delineates the scope of applicable technology and grants authority to government agencies. It also sets standards concerning model ownership, local data storage, user notifications, and content generated by AI. The bill successfully passed the State Duma on July 8 and now awaits presidential approval and official publication to become law at the federal level.
The proposed law defines a large foundation model as a software capable of executing multiple intellectual tasks at a level comparable to humans. A system qualifies if it contains at least 1 billion parameters. Such models can provide information, support decision-making, or predict outcomes based on human-defined objectives. The framework emphasizes principles of technological sovereignty, human rights, personal choice, security, and legal compliance, which must be adhered to throughout the development, deployment, and application of qualifying AI systems.
The legislation introduces categories of sovereign and national models linked to Russian oversight. A sovereign model must originate from a Russian legal entity and operate on data centers located within Russia. Its developers must maintain the ability to reproduce the entire development process, including training and original parameters. A national model adheres to similar ownership and localization criteria but may integrate foreign software components released under open licenses, provided Russian entities maintain necessary control and operational capacity.
Legal Classifications for Domestic AI Models
The government may offer assistance to entities involved in creating, deploying, or managing qualifying foundation models. Such support could include access to state-held datasets for training purposes. Authorities might also mandate exclusive use of sovereign or national models within government information systems and other sensitive environments. Additional rules related to defense, security, public order, and property protection may be established through separate legislation or presidential directives. The framework assigns responsibility to state agencies for enforcing these requirements within their respective legal jurisdictions.
Large digital platforms are subject to distinct rules concerning AI-generated audio and video content. Platforms with over 500,000 daily users must implement tools allowing users to mark such material. This regulation applies to websites, applications, and social media platforms. It does not require automatic labeling of every piece of content. Instead, developers and users can agree on the format of disclosures through service agreements. The goal is to ensure creators and distributors have an option to disclose qualifying material.
Standards for Copyright and Content Disclosure
AI service providers must inform users about the rights ownership of generated content, including access conditions and whether users are permitted to download or transfer such content. The legislation also addresses the use of copyrighted works for machine learning. It allows analysis for extraction, comparison, classification, and pattern detection if lawful access was obtained. Training on protected works is permitted when no technical restrictions were bypassed to gain access. The rules tie model training practices to existing copyright and access regulations.
Most provisions are set to become effective on September 1, 2026, pending presidential approval and formal publication. Regulations concerning domestic model classification, developer obligations, content marking, and intellectual property rights will commence on March 1, 2027. Existing systems may operate until September 1, 2032, provided they process and store data within Russia. Until the legislation is officially signed and published, it remains an approved bill rather than an enacted law under Russia’s legislative procedure.