Decisions in the Agentic Era: Toward Agent-Native Decision Science

Éditeurs invités

• Yingjie Zhang, Peking University
• Shunyuan Zhang, Harvard University
• Tianshu Sun, Cheung Kong Graduate School of Business
• Liangfei Qiu, University of Florida
• Nagesh Murthy, University of Oregon

Synthèse

This special issue addresses how autonomous AI systems are fundamentally changing decision-making across organizations, markets, and society. It recognizes that AI has shifted from systems that respond to instructions to agents that initiate workflows, use tools, and operate with meaningful autonomy. The issue aims to advance rigorous understanding of how agentic AI reshapes decisions while developing research practices accessible to AI agents themselves.

Two tracks serve different purposes. Track A (preferred) focuses on original decision science research on agentic AI behavior and human-agent collaboration, requiring submissions to include agent-native research artifacts that allow future agents to reconstruct and extend studies. Track B addresses broader consequences of agentic AI for organizations, markets, labor, and society without such artifact requirements. Both tracks welcome rigorous empirical and analytical research grounded in decision science.

Thèmes proposés

• Agent reasoning, planning, and decision strategies in task environments
• Multi-agent coordination, competition, and emergent collective behavior
• Agent capabilities, limitations, and failure modes in decision-relevant contexts
• Agent identity, role-taking, and consistency under manipulation
• Trust, deception, and norm violation in agent systems
• Agent learning and behavioral change over repeated interactions
• Human reliance, override, and complementarity in agentic decision systems
• Oversight, accountability, and governance design in human-agent systems
• Human capacity in human-agent systems and AI Quotient (AQ)
• Interface and system design conditions that shape human-agent collaboration outcomes
• Societal consequences of agentic AI, including inequality, power, and human autonomy
• Organizational transformation involving strategy, structure, and governance
• Labor market change and workforce displacement
• Market and competitive dynamics when agents act for firms or consumers
• Accountability, transparency, and fairness in agentic decision pipelines
• Regulation and governance of autonomous AI systems

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