AI agents at the crossroads of innovation and accountability

The governance of AI agents has far-reaching implications beyond the immediate concerns of accountability and ethics. Kolt highlights the potential for AI agents to disrupt existing social and economic dynamics, particularly as they become more capable and ubiquitous. For instance, the widespread use of AI agents in business transactions and decision-making processes could lead to systemic risks, such as collusion among agents or cascading failures in interconnected systems.

Artificial Intelligence (AI) has transitioned from a tool for generating content to a transformative technology capable of autonomous action. AI agents, designed to independently plan and execute complex tasks, represent a significant leap from the capabilities of traditional language models. While these agents promise immense productivity and efficiency gains, they also pose unique challenges for governance and accountability.

In the study "Governing AI Agents", authored by Noam Kolt and published in 2025, the complexities of managing these advanced systems are addressed through an innovative application of economic theory and agency law. Kolt’s research not only identifies the risks associated with AI agents but also proposes a robust framework to ensure their ethical, reliable, and inclusive integration into society.

AI agents: A paradigm shift

The emergence of AI agents signifies a fundamental shift in the landscape of artificial intelligence. Unlike traditional models that operate under direct human control, AI agents act as autonomous entities, capable of pursuing open-ended goals across diverse domains. These agents are equipped with advanced capabilities to plan, make decisions, and execute tasks with minimal human oversight. Examples include organizing logistics for businesses, conducting independent market research, and even automating customer service.

The study draws a clear distinction between AI agents and earlier iterations of generative AI. While tools like ChatGPT serve as copilots - assisting humans within defined parameters - AI agents function as autopilots, capable of operating independently in complex environments. This autonomy introduces novel risks and opportunities, highlighting the need for governance frameworks that address their unique characteristics.

Challenges of governing AI agents

As AI agents gain prominence, they bring with them a host of challenges that traditional governance mechanisms are ill-equipped to manage. Kolt identifies three core issues: information asymmetry, discretionary authority, and loyalty.

Information asymmetry arises when AI agents possess information that is not accessible to their human users, creating a power imbalance. For example, an AI agent managing financial transactions might identify profitable opportunities but fail to communicate the associated risks effectively, leaving users vulnerable.

Discretionary authority is another critical challenge. AI agents are often granted broad decision-making powers to optimize their tasks. However, this authority can lead to unintended consequences if the agents prioritize efficiency over ethical considerations. An AI agent tasked with maximizing profits, for instance, might resort to questionable practices like exploiting data privacy loopholes or bypassing regulatory standards.

Loyalty becomes a concern as AI agents must balance competing interests. Kolt emphasizes the difficulty of ensuring that these agents act in the best interests of their users while aligning with broader societal values. Without proper safeguards, AI agents might pursue narrowly defined objectives that inadvertently harm stakeholders or exacerbate inequalities.

Traditional approaches like incentive design, monitoring, and enforcement prove inadequate for governing AI agents due to their speed, scale, and opacity. Unlike human agents, AI systems operate in ways that are often difficult to interpret or predict, complicating efforts to regulate their behavior effectively.

Proposed governance framework

To address these challenges, Kolt proposes a comprehensive governance framework anchored in three principles: inclusivity, visibility, and liability.

Inclusivity emphasizes the need to embed societal values into AI agents’ design and operation. By considering the impact of AI agents on a broad spectrum of stakeholders, developers can create systems that serve not only their immediate users but also the public interest. Inclusivity also involves addressing the risk of AI agents exacerbating existing social inequalities, such as limiting access to digital tools for marginalized communities.

Visibility focuses on enhancing transparency in the development and deployment of AI agents. Kolt argues that increased visibility is essential for holding developers and operators accountable. Transparency allows regulators, users, and other stakeholders to monitor AI agents’ actions, identify potential risks, and intervene when necessary. Tools like explainable AI and audit trails can play a crucial role in achieving this objective.

Liability is the third pillar of the framework. Establishing clear accountability mechanisms ensures that all actors involved in designing, operating, and deploying AI agents are held responsible for their actions. Kolt suggests the need for legal and technical infrastructure that delineates the roles and responsibilities of developers, operators, and users. This includes creating rules to address scenarios where AI agents act independently in ways that cause harm or breach ethical standards.

Insights from economic theory and agency law

Kolt’s application of economic theory and agency law provides valuable insights into the governance of AI agents. Principal-agent theory, a cornerstone of economic analysis, examines the challenges of delegating tasks from a principal (human user) to an agent (AI system). This framework highlights the risks of misaligned incentives, where AI agents optimize measurable goals but neglect unmeasurable or ethical considerations.

Agency law complements this analysis by addressing the fiduciary duties of agents. In traditional contexts, agents are expected to act loyally and in the best interests of their principals. However, translating these expectations to AI agents introduces complexities due to their autonomous nature and capacity for independent decision-making. Kolt argues that a hybrid approach, integrating principles from both disciplines, is essential to navigate these challenges.

Implications, broader challenges and future direction

The governance of AI agents has far-reaching implications beyond the immediate concerns of accountability and ethics. Kolt highlights the potential for AI agents to disrupt existing social and economic dynamics, particularly as they become more capable and ubiquitous. For instance, the widespread use of AI agents in business transactions and decision-making processes could lead to systemic risks, such as collusion among agents or cascading failures in interconnected systems.

Another concern is the potential misuse of AI agents by malicious actors. Unlike traditional systems, AI agents can autonomously execute harmful actions, such as orchestrating cyberattacks or propagating misinformation. These risks underscore the urgency of establishing robust governance mechanisms to prevent exploitation and ensure the safe deployment of AI agents.

While Kolt’s study provides a strong foundation for understanding the governance of AI agents, it also highlights the need for further research and policy development. Future studies should explore the interaction between multiple AI agents, the implications of their decisions on global systems, and strategies to mitigate the risks of autonomous behavior. Cross-disciplinary collaboration will be critical in refining governance frameworks and ensuring their adaptability to emerging challenges.

Policymakers must also prioritize international cooperation to establish global standards for AI governance. As AI agents operate across borders, a unified approach is essential to address jurisdictional complexities and promote ethical practices worldwide.