Brief Summary
Insights into the administrative facets of chatbot deployment and management need to be improved. For this research, six companies used chatbots for customer assistance within the past three years. By 2022, Gartner expects AI-based technologies such as chatbots to be a common part of the majority of customer interactions throughout the globe (Zhang et al., 2021). Even with a great chatbot, performance may suffer if poorly implemented and maintained. An all-encompassing, big-picture strategy is required to make the most of emerging technologies.
This article aims to help designers and developers create chatbots that give users what they want and help businesses delight their customers. It has tremendous potential for enhancing the quality of customer service operations. Additionally, it is unclear how the introduction of chatbots affects businesses (Zhang et al., 2021). This research offers a novel understanding of the administrative facets of implementing chatbots, which may be helpful to companies in avoiding pitfalls.
Different leadership approaches may be needed at various points in the innovation process. Business gains from digital technology may only be realized if the company’s digital culture is prepared to handle them. Based on the research presented in this article, companies actively seek and maintain partnerships with vendors and consultants to help them innovate with new technologies (Zhang et al., 2021). Prior research has addressed the significance of performance goals and rewards for innovation implementation, particularly in the literature on innovation implementation.
The quality of chatbot-customer interactions primarily depends on the quality of the conservations fed into the chatbots. Many businesses have failed to implement AI successfully due to a lack of competent people and excessive expectations. Instead of replacing humans with machines, service providers should create novel communication methods for humans and machines. According to the survey results presented in the article, as much as 50% of businesses’ attempts to incorporate AI ultimately fail (Zhang et al., 2021). Regarding new technologies, having the backing of upper management and thought leaders is essential for successful rollouts.
Strengths and Weaknesses
The article succeeds because of the statistical projection of businesses that are expected to utilize chatbots by 2022 that it provides. The article also includes data on the frequent failure of chatbots when they are introduced to businesses. The company’s strength also lies in its admission to customers that multiple types of leadership are necessary for its continued success. However, the article’s failure to illustrate the many leadership and management styles required to implement successfully is a significant flaw.
Personal Position
In my view, leadership in providing superior service to customers is one of the essential strategies an organization can implement to boost its profitability. As a result, putting in place a chatbot is the ideal customer service leadership plan that can secure an increase in profit. This strategy should be applied with suitable vendors with a track record of success, despite some businesses reporting that it has failed.
Recommendations
Leadership in customer service that needs little in the way of oversight is ideal. This customer care model needs so little oversight from management that every business should adopt the chatbot. Companies should constantly look for reliable service providers to help make a chatbot that can attract and retain clients a reality (Andrade & Tumelero, 2022). Finally, I suggest that businesses providing the service enhance visibility by maintaining a reliable website.
References
Andrade, I. M., & Tumelero, C. (2022). Increasing customer service efficiency through artificial intelligence chatbot. Revista De Gestão, 29(3), 238–251. Web.
Zhang, J. J., Følstad, A., & Bjørkli, C. A. (2021). Organizational factors affecting successful implementation of chatbots for customer service. Journal of Internet Commerce, 1–35. Web.