AbstractThe increasing deployment of artificial intelligence (AI) in e-commerce has enabled the emergence of delegated commerce, wherein consumers authorize AI agents to autonomously execute purchase and payment decisions. While such systems promise convenience, efficiency, and personalization, their widespread adoption remains constrained by unresolved issues of consumer trust, particularly in financially consequential contexts. Prior research has largely examined general AI acceptance or human-AI interaction, offering limited insight into the specific conditions under which consumers are willing to delegate economic decision authority to AI agents. This paper proposes a multidimensional conceptual framework for understanding consumer trust in delegated commerce. Drawing on an interdisciplinary synthesis of trust theory, consumer behavior, AI ethics, and regulatory scholarship, the framework articulates trust as a conditional and context-dependent construct shaped by perceived risk, transparency, control mechanisms, system infrastructure, personalization, and liability arrangements. To ground and refine the framework, the study incorporates illustrative insights from expert interviews spanning AI development, e-commerce, psychology, ethics, and user experience. Rather than empirically validating trust determinants, the study aims to clarify core constructs, delineate boundary conditions across transaction risk and delegation levels, and surface key governance challenges specific to AI-mediated purchase and payment decisions. The proposed framework offers a structured foundation for future empirical research and provides practical guidance for designers and policymakers seeking to support responsible, trustworthy deployment of autonomous commerce systems.
Arjun Wadwalkar (Wed,) studied this question.