Dennis D. Hirsch (Ohio State U (OSU) Michael E. Moritz College Law) et al. have posted “Responsible AI Management: Evolving Practice, Growing Value” on SSRN. Here is the abstract:

One hears often today of the need to choose between AI ethics and AI opportunity. Such statements are premised on a trade-off between responsible AI, and competitive AI. But does such a trade-off truly exist? This article reports the results of a survey of business managers knowledgeable about their firm’s responsible AI management (RAIM) practices. The study – conducted by Ohio State researchers in partnership with the IAPP – explored three questions: (1) What are the components of corporate RAIM programs? (2) Who in the organization is responsible for RAIM? and (3) Does RAIM create business value for organizations and, if so, what types of value does it generate?

The researchers found that: (1) Business responsible AI management programs consist of 14 main practices that range from tracking legal and policy developments, to adopting AI ethics principles, to appointing a responsible AI committee, and beyond; (2) Companies were most likely to assign the RAIM function to people with expertise in privacy, although they also relied significantly on those with risk and data analytics expertise. This could mean that effective AI governance requires a combination of skills; and (3) Responsible AI management creates significant business value by improving product quality, building trust and reputation, preparing the organization for future regulation, and enhancing employee relations. This suggests that there may be a win-win, rather than a zero-sum, relationship between responsible, and competitive, AI. If upheld in future work, this finding could move the conversation about RAIM beyond the realm of safety and values and into the sphere of business AI strategy.

Wulf A. Kaal (U St. Thomas Law (Minnesota)) has posted “How can we Best Monitor AI Agents?” on SSRN. Here is the abstract:

This paper examines the critical challenge of monitoring AI agent transaction execution within decentralized digital ecosystems, highlighting the deficiencies of traditional centralized AI-driven supervision, including opacity, bias, and systemic vulnerabilities. In response, it proposes a web3 Decentralized Autonomous Organization (DAO)-centric governance model that integrates blockchain technology, federated communication platforms, smart contracts, and Weighted Directed Acyclic Graphs (WDAGs) to deliver an alternative oversight framework. The proposed system ensures unparalleled transparency and accountability through blockchain’s immutable ledger, while decentralized decision-making via community consensus mitigates bias and single points of failure. Federated platforms enhance scalability and privacy by distributing data processing, and smart contracts automate real-time compliance, bolstered by WDAGs’ adaptive governance structure. Validation pools and reputation tokens further empower stakeholders, fostering a dynamic, inclusive monitoring process. By incorporating feedback loops, this model anticipates and adapts to AI evolution, overcoming scalability, interoperability, and regulatory gaps inherent in existing frameworks. This decentralized approach not only addresses current shortcomings but also establishes a forward-looking standard for secure, compliant, and efficient AI agent management in modern infrastructures.

Yashraj Srivastava (Amity U) has posted “The Philosophical Nature of Corporations: Examining Corporate Personality and Liability in the Context of Artificial Intelligence” on SSRN. Here is the abstract:

Identity plays a major role in philosophy to determine the recognition of an entity, and when we talk about identity, we need to determine in what capacity it effects the legal personhood of such entity. Determination of corporate legal personality of an entity is defined well over the years by courts of law; hence the aspects of philosophical identity embody corporate bodies by recognizing it as legal personality. There are two major aspects which determines the philosophical grounds of a corporations; firstly, the personality of a corporation and secondly, the liability which it holds with respect to such personality. With the advent of Artificial intelligence (Herein AI), there is major emphasis of various legal and social changes that it has to offer. Even the corporations are wrapped by the garb of this change. The duality of corporations (Personality and Liability) is also subject to change with the arrival of AI. There are two dimensions wherein the questions of personality and liability will be enquired; firstly, AI driven decisions by a corporation and secondly, companies who provide services featuring AI. The philosophical enquiry in such two dimensions will emphasize the nature of corporate legal personality in this new age of AI. Once there is determination of legal personality of corporation (which is already in this case determined by various courts of law around the world) there is a need to trace the dimensions and range of various rights, duties, liabilities, powers, immunities etc. in the Hohfeldian’s lens. The same will determine the jurisprudential essence of corporations which are subject to AI. In order to dive into the philosophical depths, we need to ascertain the deontological, utilitarianism and ethical implications of AI driven entities in a form of corporations. This will determine the various effects of AI driven corporations in a sociological and moral angle, which eventually will give us a better hold in analyzing it as a legal entity.

Alfonso Berumen (Pepperdine U Graziadio Business and Management) has posted “When Data Lies: Synthetic Data, AI, and the New Corporate Risk” on SSRN. Here is the abstract:

The case of Charlie Javice and the $175 million acquisition of her startup, Frank, by JPMorgan Chase (JPMorgan) provides a critical lens through which to examine the emerging corporate risks associated with synthetic data. Javice allegedly fabricated millions of student/user/customer profiles to inflate metrics, highlighting how internally generated synthetic data can be weaponized to mislead investors and bypass due diligence efforts. This white paper explores the broader implications of the Javice case, positioning it as a cautionary example of how synthetic data, while a powerful tool for innovation, machine learning, and privacy-preserving analytics, can also be exploited for fraud. As Artificial Intelligence (AI) becomes more deeply embedded across industries, this paper offers a set of regulatory, legal, and ethical recommendations aimed at addressing the dual-use nature of synthetic data and safeguarding corporate integrity.

David S. Filippi (Western U Health Sciences) et al. have posted “The Law and AI as “Apex Collaborator”: Legal Frameworks for Optimized Cooperation” (FIU Law Review (To appear.)) on SSRN. Here is the abstract:

Law fundamentally exists to enable human cooperation, providing frameworks for everything from basic contracts to complex international agreements. As artificial intelligence systems grow more sophisticated, they may enable new ways that collaborative activity can occur. We posit the possibility of a new kind of AI entity: the “Apex Collaborator”, a computational system with capabilities for cooperation and partnership that are superior, in at least some ways, to those of humans. Just as apex predators shape the ecosystems in which they live through predation, Apex Collaborators would shape human-AI networks through their ability to enhance peaceful coexistence, collective problem-solving, and shared decision-making. “AI as an Apex Collaborator” flips the normal scripts of “AI as danger” or “AI as passive deliverer of benefits to humans”, instead conceiving of AI as a catalyst and enabler capable of lifting human abilities to cooperate above their evolutionary trajectory. This article maps the legal architecture needed to guide AI development toward this collaborative potential, while simultaneously mapping fundamental implications particular coding decisions may have for the law. We address key areas requiring reform: liability regimes governing potential harms to humans, property, or other AIs, copyright law to enable AI training, structures and strictures for AI self-determination, clear accountability for AI-assisted actions and AI agents, interoperability standards, and alignment requirements. The article proposes specific proactive and enforcement mechanisms for AI-ogenic conflict resolution, military restrictions, and data protection including cross-border transfer controls. We outline pathways to foster beneficial collaboration while preventing harmful applications. In particular, we explore the potential for AIs acting as Apex Collaborators to support humanity’s transition to sustainability. Our framework recognizes that as AI systems advance toward apex collaboration capabilities, they may need to participate in their own governance, monitoring and responding to not only harmful AI developments but also previously impossible benefits to humanity.

Maria Lucia Passador (Bocconi U Law) has posted “The AI Act’s Silent Impact on Corporate Roles” on SSRN. Here is the abstract:

The European Union’s Artificial Intelligence Act (AI Act) introduces a profound shift in corporate governance and regulatory compliance, directly impacting directors, board secretaries, compliance officers, in-house counsels, and corporate lawyers. These professionals now face expanded responsibilities in ensuring AI transparency, regulatory compliance, and risk management.

This paper examines the AI Act’s implications for these corporate roles, highlighting the evolving regulatory expectations and the increasing intersection between AI governance, liability frameworks, and corporate strategy. As AI systems become integral to business operations, these figures must navigate complex legal and compliance challenges, ensuring adherence to AI-specific regulatory mandates while aligning corporate policies with broader governance principles. Board secretaries must integrate AI oversight into governance structures, ensuring board-level awareness of AI risks and compliance obligations. Compliance officers have to enforce risk management systems, conduct AI impact assessments, and oversee regulatory reporting. In-house counsels must navigate liability allocation, contractual safeguards, and cross-border compliance, while corporate lawyers play a pivotal role in advising on fiduciary duties, investor disclosures, and AI-driven legal risks. Hence, with stringent obligations on high-risk AI systems, post-market monitoring, and human oversight, the AI Act demands a proactive legal strategy.

Since the AI Act has extraterritorial reach, it mandates compliance for providers and deployers of AI systems whose outputs are utilized within the EU, thereby extending regulatory obligations to non-EU entities. Consequently, its influence transcends European boundaries, shaping international AI governance and impacting businesses and legal professionals across the globe.

This analysis focuses on the structural impact of the AI Act, rather than its granular requirements, offering strategic insights into the necessary adaptations for corporate and legal advisory functions. It examines broader regulatory trends influencing AI oversight, identifies potential challenges in enforcement, and provides a roadmap for corporate professionals to mitigate AI-related risks, align governance frameworks with regulatory mandates, and ensure AI adoption remains legally sound and ethically responsible. Ultimately, it presents a forward-looking perspective on the evolving role of legal and compliance professionals within the AI regulatory landscape.

Cheng-Chi Chang (Emory U Law) and Yilin “jenny” Lu (U Florida Levin College Law) have posted “Balancing Mission and Market: OpenAI’s Struggle With Profit vs. Purpose” (6 Corporate and Business Law Journal (Arizona State University) 1 (2025)) on SSRN. Here is the abstract:

This article examines OpenAI’s unique organizational structure, which juxtaposes its non-profit mission with for-profit business practices, and the legal and ethical implications arising from this hybrid model. Initially established under Section 501(c)(3) of the Internal Revenue Code to advance artificial general intelligence (AGI) for the collective benefit of humanity, OpenAI has increasingly integrated commercial interests, leading to the creation of a for-profit subsidiary, OpenAI LP. This evolution has sparked scrutiny regarding the alignment of OpenAI’s activities with its original charitable objectives.

The article is structured in three parts. Part I outlines the legal framework governing 501(c)(3) organizations, emphasizing the conditions under which they may establish for-profit subsidiaries while maintaining tax-exempt status. Part II explores the shifts in OpenAI’s mission statements, the consolidation of CEO Sam Altman’s influence, and the deepening relationship with Microsoft, which has invested heavily in OpenAI and gained significant strategic influence. This section also addresses the controversies surrounding increased secrecy in OpenAI’s operations, particularly concerning AGI safety and ethical considerations. Part III discusses the potential ramifications of OpenAI losing its non-profit status, including the legal requirements for distributing its charitable assets and the precedent set by the conversion of charitable healthcare organizations into for-profit entities. Part IV explores future implications and recommendations, proposing innovative governance structures, tailored regulatory approaches, and global frameworks for overseeing AGI development.

By analyzing OpenAI’s trajectory, this article contributes to the broader discourse on the governance of non-profit entities engaged in high-stakes technological development. It underscores the importance of balancing innovation with ethical responsibilities, ensuring that the pursuit of AGI does not compromise the foundational mission of benefiting humanity. The article concludes by emphasizing the need for comprehensive legal, ethical, and governance frameworks to address the unique challenges posed by organizations operating at the intersection of cutting-edge AI technology and public benefit.

Arun Sundararajan (New York U (NYU) Leonard N. Stern Business) has posted “How Corporate Boards Must Approach AI Governance” on SSRN. Here is the abstract:

As the landscape of artificial intelligence (AI) and generative AI evolves rapidly, AI oversight by corporate boards is essential for managing AI exposure and complying with new AI laws. Competitive pressure to stay ahead in the AI race is inducing CEOs to embrace innovation aggressively, making board oversight especially critical. I present a framework for corporate boards that identifies some key AI governance dimensions and provides guidelines for assessing their organizational risk and regulatory likelihood. The dual lenses of risk and regulation can simultaneously aid a board in prioritizing governance aspects to pay attention to and in choosing a robust oversight strategy. Mapping the risk-regulation matrix shapes appropriate recommended oversight strategies, ranging from proactive self-regulation and compliance monitoring to more passive wait-and-watch strategies. I provide a structured way to navigate the evolving regulatory and governance landscape while unshackling boards from the subjectivity and imprecision of terms like “responsible” or “ethical” AI, leading to oversight that aligns with a company’s unique risk profile and industryspecific regulatory context, while recognizing that AI governance touches a range of topics, from technology, intellectual property and sustainability to audit, measurement and risk assessment.

Adam J. Sulkowski (Babson College) has posted “AI, ESG, and Law: Potential, Limitations, and Strategies Concerning Artificial Intelligence in Sustainability Reporting” on SSRN. Here is the abstract:

Sustainability reporting, also known as environmental, social, and governance (ESG) reporting, is the practice of publishing information on an organization’s non-financial performance, including its impacts and actions related to climate change, human rights, and diversity, equity, and inclusion (DEI). ESG reporting, however inconsistently executed and questioned by some critics, is used by management to affect perceptions and relationships with stakeholders, including investors, employees, customers, and regulators. It can also, some argue, result in better management. This article will consider the deployment of artificial intelligence (AI) in the context of sustainability reporting. As with other technologies, like blockchain, AI may, on its own, be overhyped as single factor that could bring about substantive, widespread change in ESG reporting practices and outcomes. This is because, as in other contexts, some degree of human involvement and the quality of data inputted into systems will remain critical. Voluntary standards and regulations with consequences for non-reporting and fraud will remain salient. This paper explores the potential and limitations of AI in the context of ESG reporting, and suggests strategies for managers, attorneys, and policy makers in addressing related legal issues.

Paul Oudin (U Oxford) and Teodora Groza (Sciences Po Paris) have posted “The Governance of AI Companies: Reconciling Purpose with Profits” on SSRN. Here is the abstract:

Artificial intelligence (‘AI’) is both a critical driver of economic change and a source of potentially extreme negative externalities. For this reason, two leading AI companies, OpenAI and Anthropic, implemented customised governance structures with the double aim of addressing these externalities while remaining financially attractive to their investors. Other AI companies across the world adopted milder governance safeguards for that purpose. This paper studies these innovative governance frameworks by providing what is to the best of our knowledge the most comprehensive review of AI companies’ various governance structures available to date. It then shows that applicable rules are determinant in shaping companies’ ability to tailor their governance structure to their specific needs and examines the limitations of corporate laws in three European jurisdictions—France, Germany, and Italy—and, to a smaller extent, the US—more specifically, Delaware and Nevada—in enabling flexible governance structures that balance profit motives with public benefit objectives. Finally, it proposes recommendations for creating a new corporate form in the European Union to better support the peculiar needs of AI and other innovative companies, in line with the European Commission’s priorities for the next five years.