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Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform

Author

Listed:
  • Lingli Wang

    (School of Information, Renmin University of China, Beijing 100872, China)

  • Ni Huang

    (Miami Herbert Business School, University of Miami, Coral Gables, Florida 33143)

  • Yumei He

    (A. B. Freeman School of Business, Tulane University, New Orleans, Louisiana 70118)

  • De Liu

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

  • Xunhua Guo

    (China Retail Center, School of Economics and Management, Tshinghua University, Beijing 100084, China)

  • Yan Sun

    (Alibaba Group, Hangzhou 310023, China)

  • Guoqing Chen

    (School of Economics and Management, Tsinghua University, Beijing 100084, China)

Abstract

Livestream technology enriches consumers’ online shopping experience, enabling streamers to demonstrate products in real time while interacting with a large number of consumers for product sales. However, tension arises between streamers’ constrained service capacity and consumers’ individual service demands on livestream selling platforms. Streamers can only handle a finite number of interactions and inquiries because of time and capacity constraints, whereas consumers expect immediate, tailored responses. In this work, we examine whether and how an artificial intelligence-powered streaming assistant (termed “AI streaming assistant”), which helps consumers with interactive chat-based support for information acquisition and processing, can mitigate this tension in livestream selling. We report a randomized field experiment on a leading livestream selling platform, where the consumers in the treatment group had access to an AI streaming assistant during livestream sessions and the control group did not. Our results reveal that implementing an AI streaming assistant increases sales by 3.00% and reduces the product return rates by 12.55%. Our exploration of plausible mechanisms suggests that access to an AI streaming assistant increases consumers’ perception of intelligent information provision (and, in parallel, interruption), which in turn reduces (and increases) uncertainty in decision making. Overall, the benefits of the AI streaming assistant’s intelligent information provision outweigh its interruptions, subsequently increasing consumers’ purchase intention and decision-making confidence. We also differentiate and explore two distinct modes of human-AI interaction, AI’s proactive and reactive interactions, and our correlational results show that these interaction modes reinforce each other in increasing purchases and reducing product return rates. This study contributes to the literature on human-AI interactions, livestream selling, and product returns in online commerce. Our findings also provide actionable implications for online commerce platforms in designing and implementing AI artifacts.

Suggested Citation

  • Lingli Wang & Ni Huang & Yumei He & De Liu & Xunhua Guo & Yan Sun & Guoqing Chen, 2025. "Artificial Intelligence (AI) Assistant in Online Shopping: A Randomized Field Experiment on a Livestream Selling Platform," Information Systems Research, INFORMS, vol. 36(4), pages 2358-2374, December.
    • Handle: RePEc:inm:orisre:v:36:y:2025:i:4:p:2358-2374
    DOI: 10.1287/isre.2023.0103
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    References listed on IDEAS

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    Cited by:

    1. Xu, Xiaoping & Chen, Xinru & Choi, Tsan-Ming & Cheng, T.C.E., 2026. "Employee or influencer live streaming? A manufacturer’s strategy for virtual character adoption considering live streaming reviews," International Journal of Production Economics, Elsevier, vol. 293(C).
    2. Xu, Dongyang & Chen, Haoran & Liu, Baoshan & Guan, Xu, 2026. "The interaction between E-tailer’s AI live-stream strategy and supplier encroachment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 205(C).
    3. Soogand Alavi & Salar Nozari, 2026. "When Agents Shop for You: Role Coherence in AI-Mediated Markets," Papers 2604.26220, arXiv.org.

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