Artificial Intelligence on Call: The Physician's Decision of Whether to Use AI in Clinical Practice

Tinglong Dai & Shubhranshu Singh

Journal of Marketing Research2025https://doi.org/10.1177/00222437251332898article
FT50UTD24AJG 4*ABDC A*
Weight
0.57

Abstract

Artificial intelligence (AI) is reshaping the practice of medicine. This article examines a physician's decision regarding whether to use AI when prescribing a treatment plan for a patient. Using AI helps the physician generate an informative signal that lessens clinical uncertainty. It can also change the physician's legal liability in the event of patient harm. The authors analyze two patient-protection schemes that determine physician liability when using AI: The prevailing patient-protection scheme uses the AI signal to enforce the current standard of care, whereas an emerging scheme proposes using the AI signal as the new standard of care. They show that in both schemes, the physician has an incentive to use AI in low-uncertainty scenarios, even if AI provides little value. Furthermore, the physician may avoid using AI in higher-uncertainty scenarios where AI could have improved decision quality. As the quality of AI improves, the physician may become more hesitant to use it on certain patients. A comparison of the physician's decision to use AI under the two schemes reveals that using the AI signal as the new standard of care may mitigate AI underuse (overuse) for certain patients but may boost AI underuse (overuse) for some other patients.

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https://doi.org/https://doi.org/10.1177/00222437251332898

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@article{tinglong2025,
  title        = {{Artificial Intelligence on Call: The Physician's Decision of Whether to Use AI in Clinical Practice}},
  author       = {Tinglong Dai & Shubhranshu Singh},
  journal      = {Journal of Marketing Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/00222437251332898},
}

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Evidence weight

0.57

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.57 × 0.4 = 0.23
M · momentum0.78 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.