AI in the Pen: How Real-time AI Writing Guidance Shapes Online Reviews

Fangyan Wang, Sai Liang and Zaiyan Wei

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Abstract: Recent advancements in artificial intelligence (AI) are reshaping user-generated content (UGC). Online reviews, an important form of UGC, exert significant influence on consumer decisions and business reputation. Yet, the impacts of AI-powered tools employed during review generation remain underexplored. We examine Yelp's AI writing guidance adopted in April 2023, a novel human-AI collaboration in content creation. Drawing on Self-Determination Theory, we evaluate the impacts of this intervention on review outcomes. Our findings reveal that, first, the AI guidance was effective in shaping topical composition, encouraging broader coverage across aspects of the dining experience. Second, the AI writing guidance increases review length while reducing overall review volume, revealing a trade-off between depth and productivity. Third, the expansion of topic coverage comes at the cost of increased textual complexity and reduced readability, ultimately diminishing the number of helpfulness votes. Lastly, effects are heterogeneous: less experienced users expand length and topic coverage more, whereas experienced users exhibit greater complexity and sharper declines in perceived helpfulness. These findings advance our understanding of AI-powered tools during content generation. We also discuss implications for platforms aiming to leverage AI in managing online content and for other stakeholders involved in the production and consumption of online content.

Date: 2025-11
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