Convergence Fellowship Program
AI and Corporate Personhood
A Comparative Analysis
By
Mohammad Ghasemi
August 27, 2025
This paper is a comparative legal analysis examining AI personhood through corporate law precedent. It explores how centuries of non-human entity recognition could inform AI legal status, proposing hybrid frameworks and interim measures for autonomous AI systems.
Authors
Key Advisors
Originally Published
August 27, 2025
Research program
AI Economic Policy Fellowship: Spring 2025
This project was conducted as part of SPAR Spring 2025, a research fellowship connecting rising talent with experts in AI safety or policy.
Abstract
This paper examines the potential extension of legal personhood to artificial intelligence systems through a comparative analysis with corporate personhood. As AI systems grow increasingly autonomous, questions about their legal status become more pressing. Rather than viewing AI personhood as revolutionary, we frame it as an evolutionary development in legal thought, drawing parallels with how societies have historically granted personhood to non-human entities like corporations based on practical needs. The analysis explores multiple dimensions of comparison, including conferral of legal status, rights and duties, decision-making agency, representation accountability, and existence parameters. While corporations and AI systems share potential capacities to own assets, form contracts, and bear responsibility, AI's technical autonomy and emergent behaviors present unique challenges that corporate law does not fully address. This paper establishes a foundation for further research on adapting corporate personhood concepts to AI while developing novel approaches for AI's distinctive characteristics. We suggest that common law jurisdictions may have advantages in developing case-by-case precedents as AI capabilities evolve, and recommend interim measures such as mandatory registration, insurance requirements, and technical auditing to build regulatory frameworks that can accommodate future developments in AI personhood.
Executive Summary
This report examines whether artificial intelligence systems should receive legal personhood by comparing AI with corporations, which already exist as non-human legal entities. As AI systems grow more autonomous and influential, determining their legal status becomes increasingly critical for society. We argue that extending personhood to AI represents an evolutionary development in legal thought rather than a revolutionary change, building on centuries of precedent where societies have granted legal status to non-human entities based on practical needs.
Key Findings
Legal personhood is a practical tool that societies create to address real-world challenges. Ancient Indian guilds received legal recognition in 800 BC, Roman municipalities gained legal status, and modern corporations now possess extensive rights without consciousness or physical form. This historical flexibility indicates that legal personhood evolves to meet societal needs rather than following rigid philosophical requirements.
We identify several factors driving the AI personhood discussion:
AI systems increasingly make autonomous decisions affecting human lives
Current legal frameworks struggle to assign clear responsibility for AI actions
Emerging questions about AI ownership of intellectual property and assets
Growing need for accountability mechanisms as AI capabilities advance
Corporate personhood offers valuable lessons but cannot provide complete answers. While both corporations and AI can potentially own property, enter contracts, and bear legal responsibility, AI presents unique challenges. Corporate decisions always trace back to human judgment, while AI decisions emerge from algorithmic processes. Corporate identity remains stable, but AI identity becomes complex across updates and versions. These differences suggest we need both adapted corporate concepts and novel legal approaches.
Key Arguments and Considerations
The report examines major positions in the AI personhood debate:
Supporting arguments focus on practical benefits: Legal recognition would create clear liability pathways when AI causes harm. It would solve emerging problems around AI intellectual property and contractual relationships. Proactive frameworks could guide development before highly autonomous AI becomes widespread.
Opposition arguments emphasize risks: AI personhood might become an "ultimate liability shield" allowing companies to blame autonomous systems. Existing product liability and negligence laws might adequately address AI challenges. Granting rights to AI could conflict with human interests and welfare.
The consciousness question proves less central than expected: Corporate personhood demonstrates that legal status never required consciousness, only societal utility. We grant corporations rights to facilitate commerce, not because we believe they possess awareness. This precedent suggests evaluating AI personhood based on practical benefits rather than philosophical debates about machine consciousness.
Practical Approaches and Current Status
The report explores hybrid solutions that work within existing law. AI systems could operate as primary decision-makers within traditional corporate structures, gaining functional agency without requiring new legal frameworks. This "AI corporation" model offers immediate legal clarity while maintaining human oversight through boards and shareholders.
Globally, no jurisdiction currently recognizes AI as legal persons despite media attention. The European Union rejected "electronic personhood" proposals after expert opposition. Some US states explicitly prohibit AI personhood. Saudi Arabia's robot citizen publicity stunt carried no legal weight. AI remains classified as property or tools across all legal systems.
Recommendations for Moving Forward
We propose several immediate measures regardless of personhood decisions:
Mandatory registration systems for advanced AI models
Insurance requirements covering potential AI harms
Technical auditing standards ensuring transparency
Clear chains connecting AI actions to human responsibility
Explainability requirements for high-stakes AI decisions
Legal evolution suggests common law jurisdictions may adapt more readily than civil law systems. Courts in countries like the United States and United Kingdom can develop precedents responding to emerging AI capabilities, while comprehensive legal codes struggle to anticipate technological change.
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