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The emergence of increasingly autonomous Artificial Intelligence (AI) agents is reshaping how consumers search for information, evaluate alternatives, and make purchasing decisions. While existing consumer journey models have incorporated AI primarily as a decision-support technology, they provide limited conceptual guidance for understanding situations in which AI agents perform purchasing activities on consumers’ behalf. Drawing on consumer journey theory, AI-enabled commerce, and human–AI collaboration research, this conceptual paper adopts a theory-adaptation approach to examine how established frameworks may be extended to account for emerging forms of delegated decision-making. We propose the Human–AI Collaborative Consumer Journey, a framework that conceptualizes purchasing as a collaborative process involving consumers and consumer-authorized AI agents across different stages of the journey. Its central contribution is the concept of Delegated Consumer Agency (DCA), defined as the configuration of authority consumers grant AI agents to perform cognitive or operational purchasing activities within predefined goals and constraints. The framework highlights how human and AI participation may vary across purchasing contexts and identifies implications for consumer autonomy, decision-making, and e-commerce management. Finally, six research propositions and a future research agenda are presented to guide empirical investigation.
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Dias et al. (2026) studied this question.
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