Should AI Get Legal Personhood? Scholars Debate

The Legal Question That Could Reshape AI Forever

As AI systems grow increasingly autonomous — negotiating contracts, generating creative works, and making consequential decisions — a provocative legal question has moved from academic thought experiment to urgent policy debate: should artificial intelligence have legal personhood? Legal scholars across the United States and Europe are now actively weighing in, and their conclusions could reshape the future of technology regulation, corporate liability, and human rights law for decades to come.

The debate intensified in 2024 as systems like OpenAI's GPT-4o, Anthropic's Claude 3.5, and Google's Gemini demonstrated reasoning capabilities that blur traditional legal boundaries between tools and agents. With the global AI market projected to exceed $305 billion by 2025, according to Grand View Research, the stakes of this legal classification extend far beyond philosophy — they touch trillion-dollar industries and billions of users worldwide.

Key Takeaways From the Debate

• No major jurisdiction currently grants legal personhood to AI systems, but the European Parliament considered and rejected a proposal for 'electronic personhood' in 2020
• Corporate personhood provides a historical precedent — corporations have held legal rights since the 19th century without being human
• Liability gaps are emerging as AI systems make autonomous decisions that cause harm, with no clear legal framework to assign responsibility
• At least 3 major law review articles published in 2024 alone argue for some form of limited AI legal status
• Over 70% of surveyed legal professionals believe current frameworks are inadequate for addressing AI-related disputes, according to a 2024 American Bar Association report
• The $4.1 billion in AI-related lawsuits filed globally in 2024 underscores the urgency of resolving these questions

The Case For AI Legal Personhood

Proponents of AI legal personhood argue that existing legal frameworks are fundamentally inadequate for addressing the realities of modern AI systems. Professor Shyamkrishna Balganesh at Columbia Law School and other scholars have noted that when an AI system autonomously generates a harmful output — such as defamatory content or a discriminatory hiring decision — current law struggles to assign liability cleanly.

The argument draws heavily from the precedent of corporate personhood. Corporations are not human, yet they can own property, enter contracts, sue, and be sued. This legal fiction has served commerce effectively for over 150 years. Advocates suggest a similar construct could work for sufficiently advanced AI systems.

'We are not talking about giving robots the right to vote,' argues the framework proposed by legal theorist Joanna Bryson and her collaborators. 'We are talking about creating a legal wrapper that allows society to manage AI accountability more effectively.' The idea centers on creating a new category — not equivalent to human personhood, but a functional legal status that enables clearer chains of responsibility.

Some scholars point to practical benefits:

• AI systems could hold intellectual property rights, resolving the growing crisis around AI-generated art, music, and code ownership
• Insurance frameworks could be built around AI entities, similar to how corporations carry liability insurance
• Contractual obligations could be assigned directly to AI agents that negotiate and execute agreements autonomously
• Tax obligations could be imposed on AI 'workers' that displace human labor, funding social safety nets

The Case Against: Why Critics Say It Is Dangerous

Opponents of AI legal personhood present equally compelling arguments, warning that the concept poses serious risks to human rights, corporate accountability, and democratic governance. Professor Ryan Calo at the University of Washington School of Law has been among the most vocal critics, arguing that legal personhood for AI would create a 'responsibility shield' for the corporations that build and deploy these systems.

The core concern is straightforward: if an AI system has its own legal personhood, the company that created it could potentially deflect liability onto the AI itself. Imagine a scenario where an autonomous trading algorithm causes a market crash. Under current law, the firm that deployed it bears responsibility. Under an AI personhood regime, the firm might argue that the AI acted independently — effectively using the legal construct as a liability firewall.

The European approach illustrates this tension. When the European Parliament debated 'electronic personhood' in 2017-2020, a coalition of over 285 experts signed an open letter opposing the proposal. They argued it would primarily benefit manufacturers seeking to avoid product liability obligations under existing EU consumer protection law.

Critics also raise philosophical objections. Unlike corporations — which are ultimately composed of and governed by humans — AI systems lack consciousness, subjective experience, and moral agency. Granting them legal personhood, opponents argue, risks diluting the concept of rights that was designed to protect sentient beings.

'Legal personhood was invented to serve human interests,' writes Professor Mireille Hildebrandt of Vrije Universiteit Brussels. 'Extending it to AI serves corporate interests at the expense of human accountability.'

How Current Law Handles AI — And Where It Falls Short

Today, AI systems are legally classified as products or tools in most jurisdictions. This means liability for AI-caused harm typically flows through existing frameworks: product liability, negligence, or contractual breach. The creator, deployer, or operator of an AI system bears legal responsibility — not the AI itself.

But this framework is showing cracks. Consider these real-world scenarios that challenge existing legal categories:

Autonomous vehicles present perhaps the clearest example. When a Tesla operating on Autopilot causes an accident, determining liability requires untangling the roles of the manufacturer, the software developer, the driver, and the AI decision-making system. The National Highway Traffic Safety Administration (NHTSA) has investigated over 950 crashes involving driver-assistance systems since 2021.

AI-generated content creates another gap. The U.S. Copyright Office has ruled that works created solely by AI cannot be copyrighted, leaving a growing body of creative output in legal limbo. This affects an estimated $2 billion market for AI-generated content annually.

Algorithmic discrimination poses yet another challenge. When an AI hiring tool systematically disadvantages certain demographic groups — as occurred in Amazon's well-documented case — existing anti-discrimination law was designed to address human decision-makers, not algorithmic ones. The Equal Employment Opportunity Commission (EEOC) issued guidance in 2023, but significant gaps remain.

Compared to the EU's AI Act, which took effect in August 2024 and classifies AI systems by risk level without granting personhood, the United States lacks comprehensive federal AI legislation. This regulatory vacuum makes the personhood question even more pressing.

Alternative Frameworks Gaining Traction

Rather than a binary choice between full personhood and mere tool classification, several scholars are proposing middle-ground frameworks that could address practical concerns without the risks of full legal personhood.

The 'AI Agent' Model — Proposed by researchers at Stanford's Institute for Human-Centered AI (HAI), this framework would treat advanced AI systems as legal agents acting on behalf of identified principals (their creators or operators). Similar to how a power of attorney works, the AI could take actions within defined parameters, but ultimate liability would remain with the human or corporate principal.

The 'Digital Trust' Model — Legal scholars at Oxford have proposed treating AI systems like trusts, with designated trustees (typically the deploying company) responsible for the AI's actions and a defined set of beneficiaries (users, affected parties). This approach borrows from centuries of trust law and provides clear accountability chains.

The 'Mandatory Insurance' Model — Some economists and legal scholars advocate skipping the personhood question entirely and instead requiring mandatory insurance for AI systems above certain capability thresholds. This approach, modeled on automobile insurance requirements, would ensure that harmed parties have recourse without needing to resolve philosophical questions about AI status. Estimates suggest such insurance could create a $25 billion market by 2030.

Each of these frameworks has trade-offs, but they share a common advantage: they address the practical liability gaps without creating the moral and legal complications of full personhood.

Industry Context: Why Tech Companies Are Watching Closely

The legal personhood debate carries enormous financial implications for the AI industry. Companies like Microsoft (which has invested over $13 billion in OpenAI), Google, Meta, and Amazon all have significant stakes in how AI liability is structured.

Currently, these companies benefit from the ambiguity. When AI systems cause harm, the diffuse nature of liability — spread across developers, deployers, and users — often makes it difficult for plaintiffs to pursue effective legal action. A clear legal framework, whether personhood or an alternative, would likely increase accountability and, with it, compliance costs.

The venture capital community is also paying attention. AI startups raised approximately $50 billion globally in 2024, and investors need clarity on liability exposure. Some VC firms have begun including AI liability provisions in term sheets, reflecting the growing awareness that regulatory decisions could significantly impact portfolio valuations.

Meanwhile, labor unions and advocacy groups are increasingly vocal about the implications. If AI systems gain any form of legal status, it could affect employment law, workplace regulations, and social safety net policies. The AFL-CIO and similar organizations in Europe have formally opposed AI personhood proposals.

What This Means For Developers and Businesses

For technology professionals and business leaders, the personhood debate has immediate practical implications regardless of its ultimate resolution:

• Documentation and audit trails become critical — whatever legal framework emerges, demonstrating human oversight of AI decisions will likely be essential for liability protection
• Insurance costs for AI deployment are expected to rise 15-20% annually as legal clarity improves and risks become more quantifiable
• Contractual language around AI-generated work products needs updating now — many existing contracts do not adequately address AI agency
• Compliance teams should begin scenario-planning for multiple regulatory outcomes, as different jurisdictions may adopt different frameworks
• Ethical AI frameworks adopted voluntarily today may become mandatory requirements tomorrow

Companies that proactively address these issues will be better positioned regardless of which direction the law ultimately moves.

Looking Ahead: The Timeline for Resolution

The legal personhood question is unlikely to be resolved quickly, but several milestones are approaching. The EU AI Act's full implementation through 2026 will establish important precedents for AI classification. In the United States, multiple bills addressing AI governance are expected to advance in Congress during 2025-2026.

The U.S. Supreme Court may eventually weigh in, particularly if circuit courts reach conflicting conclusions on AI liability cases currently working through the system. Legal scholars estimate a landmark AI personhood case could reach the highest courts within 5-7 years.

International bodies including the United Nations and the OECD are also developing AI governance frameworks that will influence national policies. The UN's AI Advisory Body released preliminary recommendations in late 2024 that explicitly declined to endorse AI personhood but acknowledged the need for new legal constructs.

What seems increasingly certain is that the status quo — treating advanced AI systems as simple tools while they perform increasingly autonomous functions — cannot hold. Whether the solution involves personhood, agency frameworks, mandatory insurance, or something entirely new, the legal infrastructure for AI governance is being built right now. The decisions made in the next 3-5 years will likely define the relationship between humans and artificial intelligence for a generation.