How US Companies are Using AI to Enhance Business Agility

According to Mathiassen and Pries-Heje (2006), business agility is a company's capacity to effectively use resources, such as technology, to detect and solve opportunities and risks. Companies must improve their business agility to respond to market developments by implementing appropriate IT. IT-enabled agility is crucial for sustained corporate performance (Chuang, 2020; Trischler et al., 2020). To use chatbots in customer service, practitioners must realize their ability to increase company agility (Akhtar et al. 2018). Chatbots can improve corporate agility and fulfill changing client expectations (Akhtar et al., 2018; Chuang, 2020).

The literature suggests that IT use can improve corporate agility.

According to Chuang (2020), enhancing social media agility through customer cocreation improves consumer-firm connections. With the advancement of AI, firms have increasingly employed chatbots to assist people with their work, which is likely to result in new business agility. However, to the best of our knowledge, few studies have looked into how the employment of chatbots improves company agility and customer service. Researching the use of chatbots in business agility is important since IT usage might change over time (Petter, DeLone, & McLean, 2012). As a result, our general study topic is: How do chatbots increase company agility and improve customer service? Our study will specifically look at: (a) how chatbot use leads to chatbot-enabled business agility, and (b) how chatbot-enabled business agility affects customer service quality. We use the dynamic capability view (DCV) (Teece, Peteraf, & Leih, 2016) to create our research model. DCV is an acceptable theory for understanding how the usage of chatbots can assist firms in developing dynamic capabilities, such as identifying and exploiting opportunities, which eventually improve customer service performance. We performed a study and evaluated our model with 294 marketing employees from the United States. Our study makes two significant contributions. First, our research shows how different types of chatbots can help businesses achieve greater agility.

According to Li et al. (2013) and Roberts et al.

(2016), enterprises employ chatbots in two ways: routinely and innovatively. Li et al. (2013) identified routine and inventive use as separate post-acceptance IS using behaviors, which we chose for our study. According to Tams, Thatcher, and Craig (2018), focusing solely on routine usage of IT might lead to underutilization. However, engaging in innovative use allows employees to explore new applications. As a result, fully understanding the role of routine versus innovative use is critical to developing techniques for maximizing the value of chatbots. Our study can clarify how chatbots assist agility and which form of chatbot use is more essential by looking at their routine and creative uses separately. Because different forms of IT can be utilized in a variety of ways, the impacts of routine and innovative use will most likely differ in other circumstances. Our research adds to the literature by capturing the distinctiveness of chatbots and emphasizing how chatbot-enabled agility may be attained through routine and inventive application. Second, our research offers fresh insights by illustrating the value of chatbot-enabled agility in improving customer service. Research indicates that agility affects both internal operations and external business environments (Akhtar et al., 2018; Lokshin, Belderbos, & Carree, 2008). Therefore, it's important to consider both internal and external factors when assessing its impact on customer service. Our study distinguishes between internal and external agility, in line with previous research (Chuang, 2020).

Our findings indicate that while both internal and external agility can considerably improve customer service, external agility is more crucial.

Our study adds to the literature by describing how chatbot-enabled agility can improve customer service. Our research may also offer a substantial original contribution to the AI literature, as it is one of the first studies to attempt to conceptualize agility and investigate its implications in the context of new AI tools. AI-enabled business agility will be the next frontier, and the study's findings provide useful advice for businesses looking to gain new business Related studies on chatbots Chatbots are recognized as a key technology for improving customer service (see Table 1). Some research have looked into chatbot adoption. According to Rese, Ganster, and Baier's (2020) technology acceptance model and satisfaction theory, users' adoption of chatbots depends on criteria such as conversation authenticity, perceived usefulness, and perceived enjoyment. While several studies have explored the adoption of chatbots in industries like telecoms and apparel (Etemad-Sajadi and Ghachem, 2015; Roy and Naidoo, 2021), few have examined their actual use. McLean and Osei-Frimpong (2019) found that website aesthetics and perceived personalization can lead to increased chatbot use. Shumanov and Johnson (2021) found that when a consumer's personality matches that of the chatbot, they are more likely to utilize it for longer periods of time. Both studies looked at the use of chatbots from the consumer's perspective and within the context of mobile services.