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India is a rapidly developing economy with a rapidly expending internet infrastructure and among the largest Generation Z population. This generation is tech savvy and the access to technology and network creates a conducive environment for such usage. Internet banking for the same reasons is growing leaps and bounds. The introduction of artificial intelligence (AI) has created disruptions in the traditional banking also. This paper aims to analyze the comfort level and usage of AI-enabled banking services by Generation Z.

The data is collected from 272 Generation Z members. The differential aspects, that is, the relationship of independent variables with dependent variables (AI-enabled internet banking), were analyzed using the structural equation modeling approach.

Defining factors for AI-enabled internet banking were identified. The results of factors were consistent with previous studies. It was found that the usage of AI-enabled internet banking services is insignificant, indicating that Generation Z does not perceive any advantage in using AI-enabled internet banking services.

This paper does not incorporate age groups other than Generation Z. Further research could throw light on the difference based on age groups. Further research is required to deeply understand why Generation Z does not perceive AI-enabled internet services as very important.

It has been observed that internet banking is important for Generation Z, but they also place greater importance on interpersonal communication. Banks need to consider this in designing their internet banking services.

This paper addresses the gap between comfort with and usage of AI-enabled internet banking services, by Generation Z. This paper indicates that the comfort with AI-enabled internet banking services does not translate to usage.

Purpose: This chapter aims to unveil the challenges of adopting and using banking chatbots in India and identify the challenges of Chat Generative Pre-trained Transformer (ChatGPT) for future banking.

Need for the study: Unveiling the challenges of chatbots and ChatGPT in the banking industry in India is crucial to understand the limitations and areas of improvement to enhance customer experience, ensure data security, and maintain regulatory compliance.

Methodology: The researchers conducted a narrative review systematically summarising and analysing existing literature on chatbots and ChatGPT, providing a comprehensive overview of the challenges faced in the industry.

Findings: The authors identify perceived risk, platform quality, connectivity and infrastructure, data privacy and security, user education and acceptance, existing legacy systems, and regulatory guidelines as the challenges of adopting chatbots. Additionally, the findings reveal that the challenges posed by ChatGPT in future banking include the potential reduction of traditional banking jobs, linguistic diversity, data privacy and security, ethical considerations and bias mitigation, explainability and accountability, integration with existing banking systems, and user trust and acceptance. However, implementing these new technologies also presents opportunities for individuals with unique human skills, such as critical thinking, empathy, and creativity, which are difficult to replace with technology.

Practical implications: By minimising the challenges of ChatGPT and chatbots, the banking industry could achieve improved customer service, cost efficiency, automation of routine tasks, and 24/7 availability, leading to enhanced customer satisfaction and operational efficiency in the banking industry. Additionally, these artificial intelligence (AI) tools enable data-driven insights, personalised experiences, scalability, and efficient handling of large customer volumes, contributing to better decision-making and enhanced customer engagement.

This study aims to examine factors driving millennial loyalty towards artificial intelligence (AI)-enabled mobile banking services in Islamic banks.

This research collected the data from 204 millennial customers of Islamic banks in Aceh, Indonesia. Partial least square (PLS) was used to evaluate the effect of service factors (the need for service and service quality), technology-based factors (attitudes towards AI, relative advantage, security and trust) and religiosity on millennial loyalty towards AI-enabled mobile banking.

This inquiry reveals that service quality, attitude towards AI and trust are determinants important for millennial loyalty towards AI-enabled mobile banking. Further, this research notes the significant role of religiosity on millennial loyalty towards mobile banking services.

This study suggests Islamic banks focus on developing millennial trust and attitude towards AI to increase their loyalty towards AI-enabled mobile banking services. Further, Islamic banks operation that complies with Islamic law is strongly suggested to develop millennial loyalty.

To the best of the authors’ knowledge, this is the first study that tries to scrutinize loyalty towards AI-enabled mobile banking.

As disruptive technologies, such as the use of artificial intelligence (AI)-enabled customer relationship management (CRM) systems, alter the processes and strategies that banks use in service delivery models, the impact of such technologies on consumer acceptance and buying behavior must continue to be examined. This research studies the impact of technology usage and acceptance of AI-enabled banking CRM systems in Nigeria on consumer buying behavior via the mediation of customer satisfaction and service quality. The study also investigates the negative impact of technology downtime, a frequent phenomenon in the emerging market, which has not, to this point, been studied on a large scale.

The authors collect quantitative data via a face-to-face administered questionnaire from four hundred customers of ten different Nigerian banks regarding their perceptions of technology use in the banking sector.

While the research finds that technology usage has positive and direct effects on service quality, customer satisfaction and consumer buying behavior, service quality was found not to have a significant effect on consumer buying behavior. The study also establishes that technology downtime has a moderating effect on technology usage, consumer buying behavior and customer satisfaction in the banking context.

Scant literature exists that explores the importance of culture in technology usage and acceptance, specifically in developing countries like Nigeria. This study explores the impact of technology usage along with acceptance in the Nigerian setting on Nigerian consumers and their resulting satisfaction. Technology usage has been known to impact customer satisfaction in various ways, but no study has looked specifically at how technology in the banking sector can further be of help or harm from a Nigerian perspective. This study explores the technology usage in banking sector of Nigeria and its impact on the consumer buying behaviour. No studies in our knowledge have been known to consider the role of technology downtime, a frequent phenomenon in emerging market, as a factor, which will affect the customer satisfaction and buying behavior. Thus, this study (1a) explores the negative outcomes of technology downtime on both service quality and customer satisfaction, (b) explores the moderating relationship of technology downtime on the technology usage and consumer-related outcomes.

The rapid growth of technology, including artificial intelligence (AI), in the banking industry has played a disrupting role in traditional banking channels. This study aims to investigate factors that influence the attitudes and perceptions of digital natives pertaining to mobile banking and comfort interacting with AI-enabled mobile banking activities.

Data were collected from 218 digital natives. This paper uses multivariate regression and two separate multiple regression analyses to examine the differential effects of technology-based (i.e. attitudes toward AI, relative advantage, perceived trust and security in specific mobile banking activities) and non-technology based (i.e. need for service, quality of service) factors on mobile banking usage and AI-enabled mobile banking services.

This study identifies determining factors for mobile banking and AI-enabled mobile banking services. Results indicate a divide in how digital natives perceive relative advantage between our two dependent variables. Consistent with previous studies, the relative advantage construct has the most impact on mobile banking usage. However, relative advantage was not significant for AI-enabled mobile banking, suggesting an extra layer of complexity that goes beyond convenient fast banking.

A limitation of this study is that it does not incorporate age groups outside of digital natives. Further research is needed to test for differential effects between age groups. In addition, the discovery of no significant impact of relative advantage on AI mobile banking warrants more research on the similarities and differences between mobile banking and AI-enabled mobile banking.

To better appeal to digital natives, it is suggested that the banking industry emphasize mobile banking’s anywhere/anytime access to financial accounts, as this is important to college-age customers who may not live near their local banking institution. Moreover, the paper suggests that improvement to mobile banking features for one-on-one interpersonal contact with bank employees is needed.

This study addresses the gap in the understanding of how digital natives perceive mobile banking in comparison to AI-enabled mobile banking services.

The development of mobile technology has changed the traditional financial industry and banking sector. While traditional banks have adopted artificial intelligence (AI) techniques to deepen the development of mobile banking applications (apps), the current literature lacks research on the use of AI-based constructs to explore users' mobile banking app adoption intentions. To fill this gap, based on stimulus-organism-response (SOR) theory, two AI feature constructs as stimuli are considered, namely, perceived intelligence and anthropomorphism. This study then develops a research model to investigate how intelligence and anthropomorphism affect task-technology fit (TTF), perceived cost, perceived risk and trust (organism), which in turn influence users' AI mobile banking app adoption (response).

This study used a convenience nonprobability sampling approach; a total of 451 responses were collected to examine the model. The partial least squares technique was utilized for data analysis.

The results show that intelligence and anthropomorphism increase users' willingness to adopt mobile banking apps through TTF and trust. However, higher levels of anthropomorphism enhance users' perceived cost. In addition, both intelligence and anthropomorphism have insignificant effects on perceived risk. The results provide theoretical contributions for AI-based mobile banking app adoption and offer practical guidance for bank planning to use AI to retain users.

Based on SOR theory, this study reveals that as features, AI-enabled intelligence and anthropomorphism help us further understand users' perceptions regarding cost, risk, TTF and trust in the context of AI-enabled app adoption intentions.

Innovative firms have rapidly developed artificial intelligence (AI) capabilities into their service ecosystems, essentially changing perceptions of what is service quality and service delivery in their respective industries. Nonetheless, the issues surrounding AI services remain relatively unknown. The purpose for this paper is to offer a digital servitization framework for understanding how AI services impact value perceptions, consumer engagement and firm performance measures. The authors use the financial service ecosystem to explore this topic.

The authors explore relevant literature on digital servitization, service-dominant logic and AI/disruptive innovation. Next, a conceptual framework, organized by AI-Service Exchange Antecedents, Context of AI Usage and Digital Servitization Consequences, is developed. The authors conceptualize consequences for consumers and firms.

The main findings suggest that the linkages between consumers, financial institutions and fintech companies with AI usage in a service ecosystem should be identified; how value is created among multiple SD Logic-AI network actors should be analyzed; and the effects of AI-consumer interactions (lower-level and higher levels of engagement) on firm performance measures should be explored.

The conceptual framework identifies gaps in the literature and suggests research questions for future studies.

This paper may assist practitioners with the development of AI-enabled banking activities that involve direct consumer engagement.

To the authors’ best knowledge, this research agenda is the first comprehensive framework for understanding value co-creation in the context of AI in financial services, linking antecedents, usage and consequences.

This paper examines and empirically validates the artificial intelligence-enabled human resource management (AI-enabled HRM) dimensions and sustainable organisational performance (SOP) relationship. It also examines the mediation and moderation of employee engagement (EE) and fusion skills (FS).

The indirect effects of AI-enabled HRM dimensions on SOP were found using structural equation modelling (SEM), bootstrapping and FS’s moderation effect by AMOS 22.

Results showed that AI-enabled HRM dimensions indirectly affected SOP through EE as a full and partial mediator with no moderation effects of FS.

This is the first study to link AI-enabled HRM dimensions, EE and SOP and determine how FS moderates EE and SOP.

Artificial intelligence (AI)-based human capital management (HCM) software solutions represent a potentially effective way to leverage and streamline a bank’s human resources. However, despite the attractiveness of AI-based HCM solutions to improve banks’ effectiveness, to the best of the authors’ knowledge, there are no current studies that identify critical success factors (CSFs) for adopting AI-based HCM in the banking sector. This study aims to fill this gap by investigating CSFs for adopting AI-based HCM software solutions in the banking sector.

Full consistency method methodology and technology–organization–environment, economic and human framework are used for categorizing and ranking CSFs.

The study identifies the technological and environmental dimensions as the most and least important dimensions for AI-based HCM adoption in banks. Among specific CSFs, compatible technology facilities, sufficient privacy and security and relative advantages of technology over competing technologies were identified as the most important. Implementation of AI-based HCM solutions requires significant outlays of resources, both human and financial, for banks.

The study provides bank administrators a set of objective parameters and criterion to evaluate the feasibility of adopting a particular AI-based HCM solution in banks.