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How Consumers Respond to AI- versus Human-Generated Review Summaries: The Moderating Role of Verbal versus Numerical Probability Expressions

Author

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  • Chai, Shaowei
  • Chang, Yaping
  • Wang, Han

Abstract

While AI-generated review summaries are increasingly prevalent on digital platforms, their influence on consumer behavior remains insufficiently understood. This research examines when and why AI-generated review summaries outperform human-generated ones under two common probability formats: verbal probabilities (e.g., most) and numerical probabilities (e.g., 89%). Across four studies, we find that consumers respond more favorably to AI- than to human-generated review summaries when the summaries use verbal probability expressions. This effect is sequentially driven by perceived objectivity and consumer trust. However, this advantage of AI disappears when the summaries use numerical probability expressions. These findings reveal that AI’s lack of experience and agency, often viewed as deficiencies in prior research, can serve as persuasive strengths in contexts where subjective judgment is undesirable. This research advances literature on AI-human communication, AI adoption, and probability expressions of uncertainty, and further offers actionable guidance for marketers deploying AI in dispersive information communication.

Suggested Citation

  • Chai, Shaowei & Chang, Yaping & Wang, Han, 2026. "How Consumers Respond to AI- versus Human-Generated Review Summaries: The Moderating Role of Verbal versus Numerical Probability Expressions," Journal of Business Research, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:jbrese:v:214:y:2026:i:c:s0148296326002808
    DOI: 10.1016/j.jbusres.2026.116245
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