A Literature Review on the Impact of Artificial Intelligence on the Future of Banking and How to Achieve a Smooth Transition ()
1. Introduction
The banking industry significantly impacts individuals, businesses, and the economy. While it has made progress in adopting Artificial Intelligence (AI), it has also encountered some challenges. According to Kaur et al. (2020) , the banking industry is transforming significantly due to adopting AI-based technology across all banking disciplines, including the front, middle, and back offices. While the AI benefits are significant, its challenges require careful navigation (Achary, 2021; Fares et al., 2022; Fountaine et al., 2019; Naik et al., 2022) . Undoubtedly, AI will continue to significantly contribute to how banks conduct their business in the future. To remain competitive, banks must introduce the technology and continuously deepen its application. However, a sound upfront understanding of its potential benefits, challenges, and critical implementation milestones will be essential to achieve optimal success from its implementation. Based on an investigation of peer-reviewed literature, the paper explores the benefits and obstacles of incorporating AI technology into the banking industry and recommends critical success factors for its implementation. The research intends to enhance comprehension of the benefits and risks of integrating AI in the banking sector. It also aims to offer suggestions on how to surmount implementation challenges for successful AI deployment and how to encourage customer acceptance of the technology.
2. Background
Despite AI evolving rapidly, its presence in the banking industry is relatively new and developing. According to Kaur et al. (2020) , the idea of machines having precise cognitive artificial intelligence (AI) was initially considered in the 1950s by Alan Turing, who published a paper that gave rise to the term artificial intelligence. However, only after the advent of the Internet did the banking sector’s utilization of AI technology become the subject of investigation (Fares et al., 2022) . Over the following two decades, as per Kaur et al. (2020) , AI technology has primarily been utilized in the banking industry to analyze, approve, and oversee customer loans. During this time, ongoing research and development are also evident in human language analysis, image and voice recognition, deep learning, and analysis of human emotions (Fares et al., 2022) . It was not until 2011 that major tech companies started incorporating AI technology into their business applications, eventually leading to widespread adoption. As time progressed, the focus of AI use expanded to optimize processes and improve service delivery, resulting in increased efficiencies. According to Noreen et al. (2023) , AI intelligence has become vital in various sectors, including banking, in developed and developing countries. Despite being in its early stages of development, AI technology’s current and future uses appear significant and have a considerable impact. The widespread use of AI is causing a fundamental shift in how businesses, employees, and customers interact, and the acceptance and adoption thereof are primarily influenced by how people perceive their usefulness, ease of use, and trustworthiness (Qahtani & Alsmairat, 2023) . The evolution of AI has been rapid, and its impact is significant. The expectation is that this evolutionary curve will remain steep, bringing many advantages and challenges to banks.
3. Advantages of Implementing AI in the Banking Industry
Artificial intelligence has many advantages for banks (Table 1).
Therefore, implementing AI technology in banks significantly benefits organizations, employees, and customers. Its benefits enable banks to reduce risk, be more efficient and competitive, allow employees to be more productive, and boost customer satisfaction, loyalty, and usage. However, it is also essential to consider potential challenges with its use.
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Table 1. Advantages of AI implementation in the banking industry.
4. Challenges in Implementing AI in the Banking Industry
Besides understanding its significant benefits, banks must also thoroughly comprehend the potential challenges associated with AI technology before planning and implementing it (Table 2).
The AI challenges need careful navigation to overcome and ensure successful implementation, and employees have a significant role in this regard.
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Table 2. Challenges of AI implementation in the banking industry.
5. Achieving Leadership and Employees’ Comprehension and Acceptance of AI
To successfully implement AI within a banking organization, all leadership and employees must understand, accept, and welcome its direct and indirect role. Humans are distinct from artificial intelligence. Dumouchel (2019) explains that it is essential for leadership and employees to recognize that artificial intelligence is different from human intelligence. While computers can replicate certain aspects of human intelligence, human beings are more than just their brains. Dumouchel (2019) highlights three main distinctions to comprehend this: Firstly, how we interact with the world through our embodiment is essential for acquiring knowledge and shaping human intelligence, even in disagreement or criticism. Unlike humans, most AI systems operate through rules to process data and generate numerical responses. Secondly is the distinction between humans and AI to function autonomously. While humans can act outside established rules and create new ones, AI is limited to predetermined boundaries and can only apply rules learned through repetitive examples. To have moral autonomy, AI must be able to make decisions beyond a set of rules and without prior knowledge of a similar scenario. The third distinction between humans and AI is the ability to judge. While AI can follow the rules well, humans can uniquely discern what is fair and just, even in situations without precedent. Judgment involves understanding when laws apply and when they do not, an area where AI often falls short. Due to its limitations, AI technology is unlikely to reach humans’ cognitive abilities.
Nevertheless, human and artificial intelligence together can be a formidable force. According to Yao (2023) , the existence of AI and human intelligence in collaboration can create superior intelligence. Referring to it as “human-machine co-intelligence” (Yao, 2023: p. 2777) , banks can achieve this harmony by implementing three critical principles: unity, division of tasks, and mutual growth. When these principles are in place, humans and machines can work together effectively and achieve higher intelligence. Supportive of this finding, Achary (2021) emphasizes maintaining a balance between AI and human employees when servicing the bank’s clients, as AI currently lacks emotional intelligence. It is not about human intelligence versus artificial intelligence but rather about the coexistence of human and artificial intelligence that will ensure the successful incorporation of artificial intelligence into a bank, and leaders need to emphasize this.
Indeed, organizational leadership has a fundamental role in ensuring successful AI transformation. Fountaine et al. (2019) explain leadership’s essential role in communicating to employees the necessity for implementing AI to achieve an optimal state of coexistence. There may be resistance to AI, with employees fearing it will replace their jobs. However, leaders must explain to employees that AI enhances human workers’ effectiveness rather than replacing them. In addition to the fear of losing their jobs, leaders should anticipate, identify, and swiftly resolve further resistance from employees who are reluctant to hand over to AI as they take pride in their work or associate their status in the bank with the number of other employees they oversee. Fountaine et al. (2019) continue sharing that full implementation of an AI transformation can take up to three years [or longer]. During this time, leaders must encourage employees to recognize the benefits of AI for the organization and themselves. It is also a common mistake for AI implementation to be solely the responsibility of the IT team. Instead, business units should take the lead on these projects since the primary purpose of implementing AI is to address business problems. If leaders can influence employees to embrace AI, successful implementation is inevitable. After implementation, tracking and facilitating employees’ adoption of the technology is essential, and staff incentives will encourage the change. Lastly, according to Achary (2021) , continuous employee training is necessary to ensure the harmonious coexistence of AI and the human workforce. Throughout the entire journey of AI transformation, from its planning to execution, leadership should lead from the front. It is, therefore, essential for a bank to prioritize employee change management and for leaders to set an example. Effective change management can ensure employees are valuable allies to the bank in achieving successful AI transformation and overcoming critical implementation challenges.
6. Critical Success Factors for the Implementation of AI
For effective AI implementation, banking organizations must gain deep knowledge about its capabilities, evaluate its potential benefits, and prepare the organization thoroughly for successful integration. According to Achary (2021) , banks must comprehend how AI technology can optimize product and service solutions, enable process efficiencies, lower operational costs, and improve risk management. Making informed decisions about the deployment of AI will yield optimal returns for the banks, their employees, and their customers. The process begins with a well-thought-through business case that should precede a bank’s decision to onboard AI. According to (Alsheibani et al., 2020) , the business case should identify and critically assess the advantages and challenges of AI and be specific about the objectives for its deployment. They also mention that the business case should prioritize projects that will give quick wins to the organization. Undertaking overly complex or time-consuming AI projects upfront can hinder the bank’s ability to implement current and future AI projects (Fountaine et al., 2019) . For quick wins to be realized, AI deployment should be in areas of the bank where it can reduce the reliance on human intervention (Achary, 2021) . To ensure the successful deployment of AI technology, banks must validate their strategic intent against the business case. This case should guide the organization to determine the optimal implementation route and outline the necessary funding requirements for success.
In addition to adequate budget allocation being essential for AI deployment, sponsoring the AI transformation journey should be done by the most senior levels in the organization. Fountaine et al. (2019) find that securing adequate funding for AI transformation is necessary once the organization is clear about its priority projects. In Banks with decentralized budgets, obstacles can arise due to the complexity caused by budgeting realignment and forming of cross-functional teams for company-wide implementation, as noted by Alsheibani et al. (2020) . Sufficient allocation of funding is not only for acquiring the AI technology but also for its company-wide integration. Having the backing of the CEO is vital, in addition to the top-level executives and a proficient team responsible for AI design and execution. The CEO’s backing will motivate the leadership team to take ownership and promote the transformation wholeheartedly, showcasing the benefits and influencing acceptance and usage across the organization (Alsheibani et al., 2020) . Furthermore, Alsheibani et al. (2020) find that a team of competent designers and implementation managers can greatly minimize mistakes and costs. The most senior levels should lead AI transformation in the organization, and the design and implementation should be of the highest quality.
However, achieving optimal results is only feasible if AI functions on a solid IT platform and can access quality data to learn and evolve. A reliable IT foundation will provide an environment for AI solutions to meet high standards, inspire user trust, and showcase ease of use (Qahtani & Alsmairat, 2023) . Alsheibani et al. (2020) also highlight that access to high-quality data is essential for AI deployment. However, ensuring data security throughout the AI transformation process is critical, as Achary (2021) states. AI technology relies heavily on the information it can securely collect to learn and advance, and a robust IT infrastructure will ensure AI can evolve without technology barriers.
Finally, the critical success factors for successful AI deployment go beyond technology, data, and change management. A bank also must reconfigure its organizational structures, business models, and processes. Additionally, Fountaine et al. (2019) find that companies must restructure themselves to the compelling value-add of AI. Organizations that use AI should consider having a central division responsible for overseeing various company-wide aspects such as HR, performance management, partnerships, policies, and processes. This division is also responsible for maintaining AI-related systems and standards. The center division should oversee a network of business units with AI product managers and analysts who implement strategies, adopt solutions, and monitor performance at a business unit level. A cross-functional division between the center and business units must also exist to manage change and implement new projects, including developing data architecture and coding, defining user experience, reconfiguring IT infrastructure, deploying organizational capabilities, and securing funding. To prevent any possible mishaps during implementation, banks must also ensure that their internal processes are compatible with AI technology, as Alsheibani et al. (2020) find. Lastly, the study by Met et al. (2020) finds that banks must modify their business models and transform all aspects of their business, internal operations, and customer-facing processes to meet customer demands. Revamping outdated systems, procedures, and processes must be done meticulously. This task is formidable but necessary for companies that embark on the AI transformation journey. Leaders and employees must fully embrace the AI transformation, and the implementation should span company-wide to enable optimal customer experience, with careful navigation of the implementation process throughout.
7. Achieving Customer Take-Up and Utilization
After the internal rollout of AI, banks must ensure that their customers are willing to use and benefit from their AI-powered products and services. Customers must understand and embrace AI solutions’ advantages in their financial transactions. Their positive attitudes toward the solutions will increase adoption rates, utilization, and profitability. Al-Araj (2022) finds that artificial intelligence improves service quality. Banks can enable customer understanding through proactive and transparent communication about their AI journey, the anticipated changes, and how those changes will benefit their customers. With its embedded capabilities, banks can offer their customers personalized and transparent services, positively impacting customer satisfaction. Personalized services can range from personalized product offerings, personalized and proactive advice based on customer needs and behavior analysis, personalized pricing options, and personalized communication via platforms aligned to customers’ preferences. Customers expect consistent service delivery across all offerings, and AI has remarkable capabilities that meet this expectation. AI furthermore helps in building customer loyalty, profitability, and growth. Customers tend to utilize electronic banking services more often when acquainted with the different options provided by the bank (Noreen et al., 2023) . Customers’ awareness of AI features and benefits, upfront trust in the technology, compatibility with their needs, and perceived risk of financial loss influence their willingness to use the solutions (Inegbedion et al., 2020) . According to Safari et al. (2020) , promoting a positive image of AI-driven solutions can increase customers’ adoption and usage. Therefore, banks should prioritize ongoing customer marketing and awareness campaigns to assist customers in understanding their AI offerings’ features, benefits, and usefulness.
Banks can consider five dimensions of AI to engage with customers, as suggested by Cheng and Jian (2022) : interaction, information, accessibility, customization, and entertainment. These dimensions encompass how AI can engage with customers, provide relevant information, ensure ease of access, tailor products and services to individual needs, and offer an enjoyable experience. Nonetheless, entertainment is considered insignificant to the banking industry. Compared to other industries, customers in the banking sector prioritize utility and transactions over pleasure and amusement (Rodrigues et al., 2016) . Therefore, the research only considers the other four dimensions. Interaction denotes the communication exchange between customers and AI agents representing the brand. Social interaction with AI agents can improve customer experience (Godey et al., 2016) . Information involves providing product or service information and brand information through AI. AI can provide customers with relevant marketing communication, which is crucial in creating brand awareness and loyalty through extensive data analysis (Sadek et al., 2015) . Accessibility means responding to customer information quickly through AI technology. AI-assisted 24/7 services can enhance service quality, significantly impacting the brand image and performance (Sultan & Wong, 2019) . Customization entails providing personalized AI-assisted services to customers. Personalized AI-assisted services can help brands build more robust customer affinity and loyalty by allowing customers to express their individuality (Godey et al., 2016) .
Being transparent will help customers feel comfortable using these products and services and make informed decisions. Also, customers must know that these AI-based solutions will coexist with employees and that their financial dealings are not entirely dependent on technology. So, customer awareness, acceptance, and trust are essential to ensure the success of AI.
8. Conclusion
The incorporation of Artificial intelligence has become essential for banks to be competitive. However, implementing the technology can only be successful if the organization’s leadership, staff, and clients fully understand and embrace it. By adopting AI, banks can provide services that increase customer satisfaction, usage, and profitability. Also, employees can focus on valuable activities as AI takes over repetitive, time-consuming tasks; financial transactions are more secure and prevent losses, and leaders can make accurate and informed strategic decisions. Furthermore, integrating AI technology into CRM capabilities improves customer service delivery as banks can develop personalized offerings that cater to customer needs. However, banks have potential implementation challenges to consider. These include the ethical and legal implications of collecting and analyzing customers’ private information, ever-evolving and frequent cybercrime attempts, organizational cultural barriers, and potential limitations from an underdeveloped regulatory environment. In addition, while AI may detect anomalies, it needs sufficient repetitions of those anomalies to generate effective response plans. For AI implementation to succeed, leaders and employees must understand and accept its impact on the organization and acknowledge AI’s role in the company. AI is not replacing employees but supplementing their abilities. Throughout the AI transformation process, leadership must prioritize good employee change management before, during, and after implementation. By doing this, the bank can ensure that employees are essential allies in overcoming implementation challenges. The implementation process commences with a well-defined business case and sufficient funding for the technology and its implementation. From the outset, the CEO must lead the transformation from the front, supporting and motivating the leadership team to embrace and drive the change. Also, AI transformation will require revamping outdated systems, a competent development and implementation team, access to quality data, and reconfiguring organizational structures, processes, and business models. These are all critical milestones to achieve. The last implementation stage is a transparent process of ensuring customers understand and embrace the benefits of AI products and services to increase their adoption rates and utilization. Banks should actively promote and support their AI solutions to help customers make informed decisions and feel comfortable using them. Establishing trust and awareness among customers will be essential in utilizing AI solutions to their full potential. If properly understood and implemented, AI will continue positively transforming the banking industry.
The banking industry must fully integrate artificial intelligence to strengthen its future profitability and competitiveness. However, this transformation requires a deep understanding of AI, acceptance of its role, and proper implementation.
The suggestion is for future research to explore how the evolution of AI-based Fintech and Big Tech companies leading the AI race may further revolutionize banks’ competitive landscape. If joining forces with banks, they may be powerful allies, but if they compete with banks, they may be formidable adversaries.