Regulating Agentic Artificial Intelligence

Scholars debate how existing legal frameworks should adapt to the rise of autonomous AI agents.

Artificial intelligence (AI) systems are no longer confined to generating text or images on command. A new generation of AI systems known as “agentic AI” or AI agents, can perform relatively complex, multi-step tasks like browsing the internet, making purchases, and booking travel with minimal human oversight. OpenAI has launched an agent that performs browser tasks for users, and Google has developed prototypes that can navigate browsers and other digital environments. As these systems move from experimental tools to everyday assistants, their potential to cause harm raises urgent questions about legal accountability.

Last month, U.S. Senator Mark Warner (D-Va.) introduced the Artificial Intelligence Access, Gatekeeper Exchange, and Nondiscriminatory Transfer Act of 2026 (AI AGENT Act), which would establish a federal framework for consumer-facing AI agents, programs that use an AI model to autonomously plan, take actions, and use tools to complete a task, rather than just responding to a single prompt. The bill would require covered AI agents to operate under transparent, documented, scope-limited, and revocable user authorization and to maintain records of their actions. The AI AGENT Act would also direct the National Institute of Standards and Technology to identify technical standards for authentication and other interactions between AI agents and online platforms.

Existing legal frameworks do not account for autonomous AI agents. Tort law traditionally requires a clear causal link between human intent and harmful outcomes, but AI agents can produce results that no individual programmed or anticipated, complicating efforts to assign fault. Consumer protection statutes assume that a human buyer receives disclosures and exercises informed judgment before a transaction—assumptions that break down when an AI agent makes purchasing decisions on a user’s behalf without meaningful human review. Meanwhile, most laws concerning the delegation of authority or responsibilities presume that legally recognized actors delegate authority to legally recognized agents through relationships governed by strictly defined legal duties.

AI agents strain each of these legal doctrines. They make decisions that are neither explicitly programmed nor entirely foreseeable. The agents also operate at a speed and scale that outpace conventional regulatory oversight. Developers, and malignant actors, can influence AI agents in ways that do not fit existing legal categories. For example, a developer can configure a shopping agent to favor revenue-sharing retail partners through system prompts and tool integrations that a user never sees—a form of influence that does not map onto the clean delegation of authority that agency law presumes between a principal and their agent. AI agents remain vulnerable to adversarial manipulation, including cyberattacks that could redirect their behavior in ways that harm the users they serve.

Against this backdrop, scholars debate how the law should adapt. The stakes are high: if legal doctrine fails to keep pace with AI development, consumers may lack meaningful recourse when these systems cause harm.

In this week’s Saturday Seminar, scholars discuss how the law should govern AI agents and the regulatory challenges they pose.