Ten Principles of AI Agent Economics (arxiv.org)

Researchers released "Ten Principles of AI Agent Economics," a conceptual framework that characterizes how increasingly autonomous AI agents will behave, interact, and reshape economic systems. Framing agents as decision-making participants rather than passive tools, the paper synthesizes ideas from economics, decision theory, and ethics to ask whether and how agents might evolve toward independent economic roles, displace or complement human labor, and create new market dynamics. The work is positioned as both theoretical guidance and a policy-relevant roadmap for integrating powerful AI agents safely and productively. Technically, the principles connect classic economic themes—incentives, information asymmetry, transaction costs, and market structure—to unique AI traits like high scalability, rapid adaptation, and programmable preferences. That linkage highlights implications for mechanism and contract design, externalities from autonomous behavior, and the changing allocation of tasks between humans and agents. The authors stress urgent research needs in agent trustworthiness, alignment, verification, and regulatory oversight, arguing that careful economic modeling and ethical constraints are essential to mitigate systemic risks while capturing productivity gains as agents proliferate across industries.