Artificial intelligence (AI) is a future-defining technology, and AI applications are becoming mainstream in the developed world. Many consumers are adopting and using AI-based apps, devices, and services in their everyday lives. However, research examining consumer behavior in using AI apps is scant. We examine critical factors in AI app adoption by extending and validating a well-established unified theory of adoption and use of technology, UTAUT2. We also explore the possibility of unobserved heterogeneity in consumers’ behavior, including potentially relevant segments of AI app adopters. To augment the knowledge of end users’ engagement and relevant segments, we have added two new antecedent variables into UTAUT2: technology fear and consumer trust. Prediction-orientated segmentation was used on 740 valid responses collected using a pre-tested survey instrument. The results show five segments with different behaviors that were influenced by the variables of the proposed model. Once known, the profiles were used to propose apps to AI developers to improve consumer engagement. The moderating effects of the added variables—technology fear and consumer trust—are also shown. Finally, we discuss the theoretical and managerial implications of our findings and propose priorities for future research.

人工智能（AI）是定义未来的技术，人工智能应用已成为发达国家的主流。许多消费者在日常生活中采用和使用基于AI的应用程序，设备和服务。然而，很少有研究研究使用AI应用程序的消费者行为。我们通过扩展和验证公认的统一的技术采用和使用理论UTAUT2，研究了AI应用采用的关键因素。我们还探讨了消费者行为中未观察到的异质性的可能性，包括AI应用程序采用者的潜在相关细分市场。为了增加对最终用户参与度和相关细分市场的了解，我们在UTAUT2中添加了两个新的前变量：技术恐惧和消费者信任。以预测为导向的细分用于使用预先测试的调查工具收集的740个有效响应中。结果表明，五种不同行为的段受到所提出模型变量的影响。众所周知，这些配置文件用于向AI开发人员推荐应用，以提高消费者参与度。还显示了增加的变量（技术恐惧和消费者信任度）的调节作用。最后，我们讨论了研究结果的理论和管理意义，并提出了未来研究的重点。还显示了增加的变量（技术恐惧和消费者信任度）的调节作用。最后，我们讨论了研究结果的理论和管理意义，并提出了未来研究的重点。还显示了增加的变量（技术恐惧和消费者信任度）的调节作用。最后，我们讨论了研究结果的理论和管理意义，并提出了未来研究的重点。