This study explored the intention to adopt various AI and related technologies by academic and public librarians. A survey was disseminated through various library organization lists to collect input on issues surrounding AI attitude and intentions among librarians in North America. We utilized the Unified Theory of Acceptance and Use of Technology (UTAUT) as a framework and performed structural equation modeling (SEM) and related statistical analyses (using SPSS and AMOS). Our findings confirm that the UTAUT can partially predict the likelihood of AI and related technologies adoption intentions among librarians. The model showed that performance expectancy (PE) and attitude toward use (ATU) of AI and related technologies had significant effects on librarians' intention to adopt AI and related technologies, while social influence (SI) and effort expectancy (EE) did not. We conclude that UTAUT is a viable integrated theoretical framework that, when properly designed and executed within a study, and lends itself to robust statistical analyses such as SEM. UTAUT is helpful as a framework for future approaches to designing and promoting adoption and use of emerging technologies by librarians.

本研究探讨了学术和公共图书馆员采用各种人工智能和相关技术的意图。一项调查通过各种图书馆组织名单进行传播，以收集北美图书馆员对人工智能态度和意图问题的意见。我们利用技术接受和使用统一理论 (UTAUT) 作为框架，并进行结构方程建模 (SEM) 和相关统计分析（使用 SPSS 和 AMOS）。我们的研究结果证实，UTAUT 可以部分预测图书馆员采用人工智能和相关技术的可能性。该模型表明，人工智能及相关技术的绩效预期（PE）和使用态度（ATU）对图书馆员采用人工智能及相关技术的意愿有显着影响，而社会影响（SI）和努力预期（EE）则没有。我们得出的结论是，UTAUT 是一个可行的综合理论框架，如果在研究中设计和执行得当，它有助于进行稳健的统计分析，例如 SEM。UTAUT 作为未来设计和促进图书馆员采用和使用新兴技术的方法的框架很有帮助。