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Licensing AI-Supported Functionality in App Markets under User Base Restriction

EasyChair Preprint no. 13028

12 pagesDate: April 16, 2024


This research discusses the complexities and strategic responses associated with monetizing artificial intelligence (AI) in app markets, particularly in light of user base restrictions due to regulatory measures. As generative AI technologies enhance app functionalities, they also introduce new challenges, including competitive tensions and the need for adaptive pricing strategies among AI providers. This study utilizes a stylized model to explore optimal pricing strategies for licensing AI-supported features to app developers, analyzing scenarios that involve both independent AI providers and those in vertical integration with app developers. The findings highlight the delicate balance AI providers must maintain in licensing their technologies, ensuring widespread adoption while navigating the regulatory landscape and managing intellectual property rights.

Keyphrases: Artificial Intelligence, Licensing Strategies, User Base Restrictions

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Jyh-Hwa Liou and Sheng-Chih Wang and Meng-Ju Lee and Jhih-Hua Jhang-Li},
  title = {Licensing AI-Supported Functionality in App Markets under User Base Restriction},
  howpublished = {EasyChair Preprint no. 13028},

  year = {EasyChair, 2024}}
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