How Costs Influence Preferences for Control in Generative Artificial Intelligence (GenAI): Human-Guided vs. GenAI-Based Delegated Search

As generative artificial intelligence (GenAI) platforms transition to paid models, concerns grow that usage costs will diminish service value. However, our study of 1.8 million prompts shows that economic constraints actually change how users search solutions with AI. We distinguish between GenAI-based delegated search, which relies on probabilistic sampling, and human-guided delegated search, where users exert active control through refined prompting. We find that salient costs drive users to prioritize controllability over simple cost-minimization. Instead of settling for lower quality, users adapt by crafting precise, detailed prompts and actively “controlling” the AI. This strategic shift increases more purposeful exploration, leading to higher satisfaction and superior outcomes. Ultimately, our work shows that charging for AI usage transforms users into more purposeful, deliberate cocreators with AI, indirectly enhancing the service value of AI platforms.

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Publication Details

Journal
Information Systems Research
Published
2026-04-30
DOI
https://doi.org/10.1287/isre.2025.1836
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

How Costs Influence Preferences for Control in Generative Artificial Intelligence (GenAI): Human-Guided vs. GenAI-Based Delegated Search

Ho Cheung Brian Lee, Lei Wang
Information Systems Research
AI in Service Interactions
article

How Costs Influence Preferences for Control in Generative Artificial Intelligence (GenAI): Human-Guided vs. GenAI-Based Delegated Search

Ho Cheung Brian Lee, Lei Wang
article en

Abstract

As generative artificial intelligence (GenAI) platforms transition to paid models, concerns grow that usage costs will diminish service value. However, our study of 1.8 million prompts shows that economic constraints actually change how users search solutions with AI. We distinguish between GenAI-based delegated search, which relies on probabilistic sampling, and human-guided delegated search, where users exert active control through refined prompting. We find that salient costs drive users to prioritize controllability over simple cost-minimization. Instead of settling for lower quality, users adapt by crafting precise, detailed prompts and actively “controlling” the AI. This strategic shift increases more purposeful exploration, leading to higher satisfaction and superior outcomes. Ultimately, our work shows that charging for AI usage transforms users into more purposeful, deliberate cocreators with AI, indirectly enhancing the service value of AI platforms.

Information Systems Research
Pennsylvania State University (US), Indiana University Bloomington (US)
Openalex Percentile: Top 7%
AI in Service Interactions
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