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This study examines the impact of financial services employees’ engagement on the attitude toward artificial intelligence (AI) in Sri Lanka. The model developed in this study comprises three constructs to demonstrate employee engagement (EE), namely, psychological state engagement (PSE), trait engagement (TE), and cognitive engagement (CE). Further, the model tests the moderating effect of age and gender on the relationship between EE and attitude toward AI. The authors conducted this research through a survey of 200 employees at Sri Lankan financial service firms. The findings indicate that EE substantially impacts attitudes regarding AI. Additionally, PSE, CE, and attribute engagement substantially affect how people feel about AI. Further, age has a moderating effect on the association between EE and attitude toward AI among financial services personnel. Based on the findings and discussion, the researcher recommends AI’s most significant importance in promoting a high level of engagement. The results would be helpful for both academic researchers and practitioners, especially HR managers, to understand the status of AI in Sri Lanka and formulate strategies to expedite EE.

Digital transformation has made enormous changes in the banking domain, where FinTech is the salient driving force inside it. Especially in the banking industry, Artificial Intelligence (AI) and Blockchain technology act as the most innovative technologies. Similarly, Chatbots in commercial banking and Robo-advisors in investment banking has shifted banks into the entire virtual environment. In this context, the main objectives of this chapter are: to determine the current application of AI and blockchain in the banking industry, to identify the challenges faced by banks in adapting AI and blockchain technology, and to provide new insights on future banking in the industry 5.0 in this digital era. This chapter discusses the application of two robotic platforms widely used in banking, chatbots, and Robo-advisors. Chatbots are more like frontline employees of banks who are commonly engaged in customer relationship management, sales, and marketing. In contrast, Robo-advisors are a relatively advanced AI tool involved in investment and portfolio management. Blockchain will accelerate digital transformation where a decentralized digital ledger system is used for banking transactions. However, this is entirely the opposite of conventional centralized digital banking, and the adoption of these technologies is still in its infancy. Employment, performance, security, privacy and trust, cost, ethical and regulatory challenges are the most common challenges. To avoid the challenges, banks should concern with strategies like collaboration with robots, increasing the platforms’ performance, etc. Finally, the chapter provides insights on banking at industry 5.0. In the future, banking customers can experience completely virtual and customer-oriented banking services. In this regard, the fusion of all technologies and collaborative human effort is essential.

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.