AI customer service: Task complexity, problem-solving ability, and usage intention (original) (raw)

Intention to use analytical artificial intelligence (AI) in servicesthe effect of technology readiness and awareness

Journal of Service Management, 2021

Purpose-The automation of services is rapidly growing, led by sectors such as banking and financial investment. The growing number of investments managed by artificial intelligence (AI) suggests that this technology-based service will become increasingly popular. This study examines how customers' technology readiness and service awareness affect their intention to use analytical AI investment services. Design/methodology/approach-Hypotheses were tested with a data set of 404 North American-based potential customers of robo-advisors. In addition to technology readiness dimensions, the potential customers' characteristics were included in the framework as moderating factors (age, gender and previous experience with financial investment services). A post-hoc analysis examined the roles of service awareness and the financial advisor's name (i.e., robo-advisor vs. AI-advisor). Findings-The results indicated that customers' technological optimism increases, and insecurity decreases, their intention to use robo-advisors. Surprisingly, feelings of technological discomfort positively influenced robo-advisor adoption. This interesting finding challenges previous insights into technology adoption and value co-creation as analytical AI puts customers into a very passive role and reduces barriers to technology adoption. The research also analyzes how consumers become aware of robo-advisors, and how this influences their acceptance. Originality/value-This is the first study to analyze the role of customers' technology readiness in the adoption of analytical AI. The authors link the findings to previous technology adoption and automated services' literature and provide specific managerial implications and avenues for further research.

The Role of Artificial Intelligence on Enhancing Customer Experience

International Review of Management and Marketing

The main aim of the study is to examine the role of artificial intelligence (AI) on Enhancing Customer Experience in Palestine through different industries, such as banks and telecommunication companies. Interviews and a structured questionnaire were the primary data of this study. The results of the study revealed that there is a positive significant relationship between AI and Customer Experience. AI explained 26.4% of the variance of the customer experience (R²=0.264, F (1,89)=28.634, P < 0.05). Customer Experience has two dimensions; Customer service and after-sale support, the study shows that AI predicted 22.9% of the variance of customer service, whereas it predicted 7% of After-Sale Support. Moreover, providing Personalized Customer Service throughout the customer's buying journey has a great impact on customer experience. The study recommends enterprises to offer more personalized services for customers which it influences their overall experience with the enterprise. Likewise, it's highly recommended to employ AI in call centers and the other after-sales support services to shortening the customers waiting time.

AI in Customer Service - A Service Revolution in the Making

Artificial Intelligence in Customer Service: Next Frontier for Personalized Engagement, 2023

The industrial revolutions of the late 18th century provided a tremendous boost to our economy by introducing automated manufacturing processes. This revolution paved the way for higher quality, cost-effective products available to mass markets and freed people from tedious and laborious manual work - drastically improving our standard of living! With the proliferation of technology and its quick integration into service organizations, we believe that a digital revolution in services is just beginning - much like the industrial revolution brought sweeping changes to manufacturing. As cost savings will be competed away in market economies, this digital service transformation has the potential to drastically improve our quality of life by mechanizing and streamlining services like banking, insurance, logistics, healthcare, and education.

Intention to use analytical Artificial Intelligence in services. The effect of technology readiness and awareness

Journal of Service Management, 2021

The automation of services is rapidly growing, led by sectors such as banking and financial investment. The growing number of investments managed by artificial intelligence (AI) suggests that this technology-based service will become increasingly popular. This study examines how customers' technology readiness and service awareness affect their intention to use analytical-AI investment services. Design/methodology/approach: Hypotheses were tested with a data set of 404 North American-based potential customers of robo-advisors. In addition to technology readiness dimensions, the potential customers' characteristics were included in the framework as moderating factors (age, gender and previous experience with financial investment services). A post-hoc analysis examined the roles of service awareness and the financial advisor's name (i.e., robo-advisor vs. AI-advisor). Findings: The results indicated that customers' technological optimism increases, and insecurity decreases, their intention to use robo-advisors. Surprisingly, feelings of technological discomfort positively influenced robo-advisor adoption. This interesting finding challenges previous insights into technology adoption and value co-creation, as analytical-AI puts customers into a very passive role and reduces barriers to technology adoption. The research also analyzes how consumers become aware of robo-advisors, and how this influences their acceptance. Originality: This is the first study to analyze the role of customers' technology readiness in the adoption of analytical-AI. We link our findings to previous technology adoption and automated services' literature and provide specific managerial implications and avenues for further research.

Understanding artificial intelligence experience: A customer perspective

International Journal of Data and Network Science

The engagement between customers and brands is being transformed by artificial intelligence (AI). However, there has been little study into AI-powered customer experiences; hence, this research aims to examine how the incorporation of AI in purchasing might result in a better AI-powered customer experience. This research will develop a conceptual model based on the service quality model and trust-commitment theory. Further to this, an online questionnaire was distributed to individuals who had utilised an AI-powered service provided by a particular brand, and consequently, a total of 354 responses were analysed using Structural Equation Modelling (SEM). The results that were deduced from the responses demonstrated that relationship commitment has begun to substantially impact AI-powered customer experiences. In addition to this, the results also revealed that perceived sacrifice and trust both play an important role in mediating the impacts of perceived convenience, personalisation,...

The Effect of Artificial Intelligence on End-User Online Purchasing Decisions: Toward an Integrated Conceptual Framework

MDPI, 2022

This study was an investigation into the effect of selected artificial intelligence tools and the consideration set on the end-user purchasing intentions of convenient and shopping products of Saudi Arabian customers. The consideration set was the factor that the researcher sought to associate directly with the online purchasing intention variable. The selected AI tools and approaches were machine learning, purchase duration, social product recommendation, and social media dependency. The four served as the indirect factors, as their effect was measured against the consideration set variable. The theoretical framework employed in this study comprised the unified theory of acceptance and use of technology (UTAUT) and the theory of reasoned action. The researchers used an online survey with a sample of 148 customers. In analyzing the findings, the researchers opted for the structural equation modeling (SEM) approach. The findings indicated evidence of association with a consideration set of three independent variables, namely, machine learning, purchase duration, and product recommendation. The study also established that customer consideration sets influence end-user purchase decisions for online customers.

Artificial Intelligence Transforming Customer Service Management Embracing the Future

Journal of the Oriental Institute (ISSN: 0030-5324), 2023

The introduction of Artificial Intelligence (AI) has resulted in disruptive developments in a variety of industries, including customer service management. The purpose of this narrative analysis study is to investigate the role of AI in revolutionizing customer service management and its potential future consequences. The research focuses on four major AI integration components in customer service: social media monitoring, voice recognition, speech analytics, chatbots, and self-service portals. This study gives insights into the revolutionary potential of AI in customer service management through rigorous narrative analysis. It delves into the advantages and future possibilities of incorporating AIpowered elements such as customer sentiments, speech analytics, chatbots, and self-service portals. Understanding the growing environment of AI in customer service allows organization to better react to their customers' changing requirements and expectations, eventually improving customer happiness and loyalty in the digital era.

Investigating Factors Impacting Customer Acceptance of Artificial Intelligence Chatbot: Banking Sector of Kuwait

International Journal of Applied Research in Management and Economics

The Purpose: This study investigates the role of Artificial Intelligence- chatbot (AI chatbot) quality and AI chatbot users across various banking needs and its impact on customer acceptance of AI chatbots through the mediating role of perceived usefulness and ease of use. Design/methodology/approach – This quantitative study uses a cross-sectional time dimension. The questionnaire of this study was developed using multiple academic sources. Partial least square structural equation modeling was used to analyze the data, and the SmartPLS 4 software was used for the calculation. Finding - The findings indicated a significant positive direct relationship between AI chatbot quality and acceptance of AI chatbot (path coefficient of 0.138 and p-value of 0.022). At the same time, the direct relationship between the AI-chatbot user and the acceptance of the AI chatbot was insignificant (path coefficient = 0.0.096, and p-value = 0.246). While the results of the indirect relationship reveal t...

"A Study on the Impact of Artificial Intelligence(AI) Technology-Enabled Digital Banking Services on Consumer Loyalty"-A Conceptual Framework

Educational Administration: Theory and Practice, 2024

In this tech era, the service industry, such as banks, becomes more digitalized, as they provide digital banking or online banking services additionally, in order to gain a competitive advantage and also achieve a significant market share. Artificial Intelligence (AI) is one of the more advanced form of technology used in computer designs that allow us to execute the task which generally needs the intelligence of human beings, including speech reputation, visible identification, translation of languages and hassle-solving. AI technology used in banking provides personalized and customized high-quality customer satisfaction and loyalty with effective and efficient services. The systematic literature review in this study covers the different trends in digital banking such as service-related quality dimensions, AI technology factors, customer satisfaction, and consumer loyalty. Personal demographic factors too, impact digital banking, and hence a conceptual model and its structure equation modeling (SEM) are proposed which validates the model so as to demonstrate the impact of AI technology on loyalty of banking customers. This study focuses on how AI-enabled banking devices might increase consumer loyalty. Service quality dimensions (Reliability, Assurance, Customization, Empathy and Responsiveness) and Technology Acceptance Model (TAM) factors (perceived usefulness, perceived ease of use, perceived risk, perceived trust & perceived benefits) significantly impacts customer satisfaction and consumer loyalty.

Developing a Service Quality Scale for Artificial Intelligence Service Agents

European Journal of Marketing, 2022

Service providers and consumers alike are increasingly adopting artificial intelligence service agents (AISA) for service. Yet, no service quality scale exists that can fully capture the key factors influencing AISA service quality. This study aims to address this shortcoming by developing a scale for measuring AISA service quality (AISAQUAL). Based on extant service quality research and established scale development techniques, the study constructs, refines and validates a multidimensional AISAQUAL scale through a series of pilot and validation studies. AISAQUAL contains 26 items across six dimensions: efficiency, security, availability, enjoyment, contact and anthropomorphism. The new scale demonstrates good psychometric properties and can be used to evaluate service quality across AISA, providing a means of examining the relationships between AISA service quality and satisfaction, perceived value as well as loyalty. Future research should validate AISAQUAL with other AISA types as they diffuse throughout the service sector. Moderating factors related to services, the customer and the AISA can be investigated to uncover the boundary conditions under which AISAQUAL is likely to influence service outcomes. Longitudinal studies can be carried out to assess how ongoing use of AISA can change service outcomes. Service managers can use AISAQUAL to effectively monitor, diagnose and improve services provided by AISA, whilst enhancing their understanding of how AISA can deliver better service quality and customer loyalty outcomes. Anthropomorphism is identified as a new service quality dimension. AISAQUAL facilitates theory development by providing a reliable scale to improve the current understanding of consumers’ perspectives concerning AISA services.