Adoption Of Artificial Intelligence Research Articles

Artificial intelligence and human integration: a conceptual exploration of its influence on work processes and workplace learning

ABSTRACT This paper examines the influence of Artificial Intelligence (AI) on job and organizational processes, drawing on sociotechnical systems (STS) theory. It discusses the emergence of AI and its implications for HRD on individual, group, and organizational learning. AI has changed the trajectory of work processes and outcomes, paving the way for the future of work. An AI-human integration process model is proposed to reinforce its influence on job design in response to AI applications in the workplace. Learning is experienced between humans and between humans and AI. AI’s cognitive intelligence is capable of learning from each other through a process of deep learning. Humans, too, can learn from AI to modify their response towards working with AI-enabled applications. The model illustrates the relationships between individuals, work processes, and sociotechnical systems through multilevel interactions. Of relevance to HRD are two critical processes, namely learning and innovating, that facilitate the continuation of AI-human integration, enabling employees to embrace AI as an integral part of their work life. The paper offers several implications for HRD research and practice, recognizing opportunities for workplace learning and the potential constraints and risks arising from AI adoption that are applicable globally and internationally.

Prefrontal Correlates of Passengers’ Mental Activity Based on fNIRS for High-Level Automated Vehicles

AbstractWith the spread adoption of artificial intelligence, the great challenges confronted by the intelligent safety concern-safety of the intended functionality has become the biggest roadblock to the mass production of high-level automated vehicles, notably arising from perception algorithm deficiencies. This paper focuses a cut-in scenario, dividing this scenario into low-risk and high-risk segments predicated on the kinetic energy field, and the mental activities of passengers on prefrontal cortex, are analyzed within these delineated segments. Two experiments are then conducted, leveraging driving simulators and real-world vehicles, respectively. Experiment results indicate that high risk may result in the passengers’ mental activity on prefrontal cortex change. This revelation posits a potential avenue for augmenting the intended functionality of automated vehicle by using passengers’ physiological state.

Navigating the ethical landscape of artificial intelligence in radiography: a cross-sectional study of radiographers’ perspectives

BackgroundThe integration of artificial intelligence (AI) in radiography presents transformative opportunities for diagnostic imaging and introduces complex ethical considerations. The aim of this cross-sectional study was to explore radiographers’ perspectives on the ethical implications of AI in their field and identify key concerns and potential strategies for addressing them.MethodsA structured questionnaire was distributed to a diverse group of radiographers in Saudi Arabia. The questionnaire included items on ethical concerns related to AI, the perceived impact on clinical practice, and suggestions for ethical AI integration in radiography. The data were analyzed using quantitative and qualitative methods to capture a broad range of perspectives.ResultsThree hundred eighty-eight radiographers responded and had varying levels of experience and specializations. Most (44.8%) participants were unfamiliar with the integration of AI into radiography. Approximately 32.9% of radiographers expressed uncertainty regarding the importance of transparency and explanatory capabilities in the AI systems used in radiology. Many (36.9%) participants indicated that they believed that AI systems used in radiology should be transparent and provide justifications for their decision-making procedures. A significant preponderance (44%) of respondents agreed that implementing AI in radiology may increase ethical dilemmas. However, 27.8%expressed uncertainty in recognizing and understanding the potential ethical issues that could arise from integrating AI in radiology. Of the respondents, 41.5% stated that the use of AI in radiology required establishing specific ethical guidelines. However, a significant percentage (28.9%) expressed the opposite opinion, arguing that utilizing AI in radiology does not require adherence to ethical standards. In contrast to the 46.6% of respondents voicing concerns about patient privacy over AI implementation, 41.5% of respondents did not have any such apprehensions.ConclusionsThis study revealed a complex ethical landscape in the integration of AI in radiography, characterized by enthusiasm and apprehension among professionals. It underscores the necessity for ethical frameworks, education, and policy development to guide the implementation of AI in radiography. These findings contribute to the ongoing discourse on AI in medical imaging and provide insights that can inform policymakers, educators, and practitioners in navigating the ethical challenges of AI adoption in healthcare.

Harnessing artificial intelligence to develop strategic marketing goals

In today's rapidly evolving business landscape, harnessing artificial intelligence (AI) has become imperative for organizations striving to remain competitive. This concept paper explores the integration of AI in developing strategic marketing goals, aiming to provide a comprehensive framework for leveraging AI's capabilities effectively. The paper begins by outlining the current state of AI in marketing, highlighting its transformative potential across various facets such as customer segmentation, personalized targeting, predictive analytics, and automation. It underscores the necessity for businesses to embrace AI-driven approaches to stay ahead in an increasingly data-driven marketplace. Moreover, the concept paper delves into the strategic implications of AI adoption in marketing. It emphasizes the need for alignment between AI initiatives and overarching business objectives, emphasizing the role of AI in enhancing customer experience, optimizing resource allocation, and driving revenue growth. Furthermore, the paper addresses key considerations and challenges associated with integrating AI into marketing strategies, including data privacy concerns, ethical implications, and organizational readiness. It advocates for a structured approach to AI implementation, encompassing robust data governance, talent acquisition, and continuous monitoring to mitigate risks effectively. Drawing upon industry best practices and case studies, the concept paper elucidates practical methodologies for leveraging AI in setting strategic marketing goals. It emphasizes the importance of data-driven decision-making, iterative experimentation, and agile adaptation to capitalize on AI's potential for driving innovation and competitive advantage. In conclusion, the concept paper advocates for a proactive stance towards embracing AI in marketing strategy formulation. By strategically harnessing AI's capabilities, organizations can not only enhance their marketing effectiveness but also cultivate long-term sustainable growth in today's dynamic business environment. Keywords: AI, Strategic, Marketing, Environment, Goals, Business.

Assessing AI Adoption: Investigating Variances in AI Utilization across Student Year Levels in Far Eastern University-Manila, Philippines

This study investigates the prevalent use of artificial intelligence (AI) among college students at Far Eastern University. Despite the risks, it aims to understand the primary reason behind the continuous use of AI. According to academics, the benefits of implementing AI in higher education include better inclusion, increased efficiency in administrative costs, and improvements in the learning-teaching process (Pisica et al., 2023). However, the extreme utilization of AI among students has led to cheating and plagiarism for many reasons that impact their personal lives and mental health. The researcher identified potential gaps while assessing possible solutions to lessen the student using Artificial Intelligence (AI) excessively. Moreover, the researcher used a quantitative method analysis involving 40 college students from 1st-year level to 4th-year level to explore the impacts of Artificial Intelligence on their academic tasks and learning styles. Thus, examining the utilization of AI from different year levels of Far Eastern University college students revealed that the researcher provides valuable insights into addressing the challenges posed by excessive dependency on AI while maintaining academic integrity and the need for the students to develop their critical thinking skills. After the researcher analyzed the collected data, it showed that the utilization of Artificial Intelligence (AI) for academic workloads varies among participants covering different college students, showing that first-year students rely on AI due to peer pressure. In contrast, the second-year students use it to improve their academic standing. Third-year students depend on AI because of time constraints, while fourth-year students use AI to minimize the possibility of human errors. The study conveys no significant differences in the probability of using AI for academic purposes, and it does not prevent the students from using AI regardless of their year level. Therefore, the researcher recommends proposing stricter AI checkers and educating the students on responsible Artificial Intelligence (AI) usage to mitigate academic misconduct.

Development and preliminary testing of Health Equity Across the AI Lifecycle (HEAAL): A framework for healthcare delivery organizations to mitigate the risk of AI solutions worsening health inequities

The use of data-driven technologies such as Artificial Intelligence (AI) and Machine Learning (ML) is growing in healthcare. However, the proliferation of healthcare AI tools has outpaced regulatory frameworks, accountability measures, and governance standards to ensure safe, effective, and equitable use. To address these gaps and tackle a common challenge faced by healthcare delivery organizations, a case-based workshop was organized, and a framework was developed to evaluate the potential impact of implementing an AI solution on health equity. The Health Equity Across the AI Lifecycle (HEAAL) is co-designed with extensive engagement of clinical, operational, technical, and regulatory leaders across healthcare delivery organizations and ecosystem partners in the US. It assesses 5 equity assessment domains–accountability, fairness, fitness for purpose, reliability and validity, and transparency–across the span of eight key decision points in the AI adoption lifecycle. It is a process-oriented framework containing 37 step-by-step procedures for evaluating an existing AI solution and 34 procedures for evaluating a new AI solution in total. Within each procedure, it identifies relevant key stakeholders and data sources used to conduct the procedure. HEAAL guides how healthcare delivery organizations may mitigate the potential risk of AI solutions worsening health inequities. It also informs how much resources and support are required to assess the potential impact of AI solutions on health inequities.

High School Teachers’ Adoption of Generative AI

In 2023, the breakthrough of generative artificial intelligence (AI) led to its adoption. While some teachers expressed frustration over pupil misuse of generative AI, others advocated for the availability of a school-relevant chatbot for pupil use. In October 2023, a local chatbot intended to meet that goal was launched by Oslo Municipality. After six weeks, an investigation was conducted to examine how 246 teachers perceived the opportunities and limitations of this new technology. The examination used structural equation modelling to explore antecedents of instructional AI utility. The analysis shows that the pathway between instructional self-efficacy and AI utility has the highest positively charged value, while the pathways between management and AI utility have low numerical value. This last finding can be interpreted as the influence of untapped management potential and must be seen in the context of the fact that no guidelines for the use of AI in schools existed when the survey was conducted. In addition, the pathway between colleague discussion and AI utility has relatively low numerical values. The potential for learning through discussion among colleagues can be utilized to an even greater degree. The pathway between management and colleague discussion is remarkable. Implications are discussed.

Challenges and Prospects of Artificial Intelligence in Nigerian Journalism Practice: A Narrative Review

The integration of artificial intelligence (AI) into Nigerian journalism practices presents both challenges and prospects for the industry. This paper explores the dynamic interplay between AI technologies and journalism in Nigeria, addressing key conceptual clarifications, theoretical frameworks, challenges, and prospects associated with AI utilization in the field. Drawing upon existing literature, the study examines the multifaceted nature of AI, ranging from its conceptual underpinnings to its practical applications in journalism. It utilizes the Technology-Organization-Environment (TOE) framework to analyze the factors influencing AI adoption within Nigerian newsrooms, considering technological, organizational, and environmental contexts. Identifying challenges such as infrastructural limitations, financial constraints, cultural resistance, and ethical considerations, the paper elucidates the complexities inherent in AI integration in Nigerian journalism. These challenges encompass issues of data quality, transparency, bias, and accountability, underscoring the need for responsible AI implementation and robust ethical frameworks. Additionally, the paper discusses the prospects offered by AI in enhancing journalistic efficiency, facilitating data-driven reporting, personalizing news delivery, and combating misinformation. By leveraging AI for fact-checking, multilingual reporting, predictive analytics, and automated content generation, Nigerian journalists can innovate and adapt to the evolving media landscape. Moreover, AI presents opportunities for improving audience engagement, storytelling, collaboration, and addressing bias and ethics concerns. Embracing AI in journalism also creates educational pathways for aspiring journalists, fostering skill development and innovation in the industry.

From crisis to prosperity: Leveraging robots, artificial intelligence, and service automation for sustainable tourism in Zimbabwe

AbstractIn an increasingly digital and interconnected world, the integration of advanced technologies such as robotics, artificial intelligence (AI), and service automation has become pivotal for shaping the future of various industries, including tourism. The paper investigates complex relationship between three independent variables: (robotic adoption, AI adoption, and service automation adoption) and three dependent variables: (social sustainability, economic sustainability, and environmental sustainability). Employing a quantitative research approach, the study gathered data from 608 randomly selected tourism supply chain stakeholders using the Krejcie and Morgan table to determine the sample size. Data collection was facilitated through Google Forms questionnaires, and the analysis relied on structural equation modeling. The statistical findings highlight positive direct significant relationships among these variables, as evidenced by t‐statistic values surpassing the threshold of 1.96. These values ranged from a minimum of 2.156 to a maximum of 10.083. These results suggest that by strategically integrating these technologies, tourism businesses and policymakers in Zimbabwe can enhance tourist experience, the industry's long‐term viability and its positive impact on society, the economy, and the environment. This study's outcomes provide a compelling foundation for informed decision‐making and the development of targeted strategies aimed at advancing sustainability objectives within the Zimbabwean tourism landscape.

Exploring the landscape of AI adoption in cosmetic medicine and surgery: Insights from the 25th IMCAS Congress (International Master Course in Aging Science).

The integration of artificial intelligence (AI) into cosmetic medicine promises to revolutionize the field by enhancing diagnosis, treatment planning, and patient care. This manuscript explores the current adoption and perceptions of AI among professionals in the realm of cosmetic dermatology and plastic surgery, utilizing insights from the IMCAS Congress 2024 attendees. A survey employing a digital questionnaire with 14 questions was distributed among attendees of the IMCAS Congress 2024 to evaluate their familiarity with AI, usage in clinical practice, perceived advantages, and concerns regarding data privacy and security. The survey revealed that a majority of respondents are familiar with AI's potential in cosmetic medicine, yet there is a notable discrepancy between awareness and actual application in practice. Concerns over data privacy and a pronounced need for further training were also highlighted. Despite recognizing AI's benefits in cosmetic medicine, significant barriers such as data privacy concerns and the need for more comprehensive training resources must be addressed. Enhancing education on AI-applications and developing strategies to mitigate privacy risks are imperative for leveraging AI's full potential in improving patient care and outcome in cosmetic medicine.

Study of adoption of artificial intelligence technology-driven natural large language model-based chatbots by firms for customer service interaction

Purpose The purpose of this study was to comprehend the adoption of artificial intelligence (AI) technology-driven natural large language model (LLM)-based chatbots by customers. Design/methodology/approach A qualitative research study method was conducted. This was to explore managerial perspectives towards consumer centric technology adoption of AI plus LLM-based chatbots. This was specifically for AI-driven natural LLM-based chatbots services. The author conducted conducted in-depth personal interviews with 32 experts of digital content AI + LLM chatbot services. Thematic content analysis was undertaken to analyse the data. Findings The advent of natural language processing tools driven by AI technology chatbots has altered human-firm interaction. The research findings indicated that the push-pull-mooring (PPM) factors captured the phenomenon in the most comprehensive way. A total of 15 key factors influencing the adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction were identified in this study by the author. The thematic content analysis unraveled insights regarding transformed consumer adoptions towards AI-driven LLM-based chatbots by means of the PPM framework factors. Research limitations/implications The empirical research investigation contributed to the literature on the PPM theoretical framework. This was specifically in the context of adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction. Practical implications The research study insights would help managers to restructure and reconfigure their organizational processes. This would neccessiated a shift in firm-customer interactions as demanded because of the availability of AI technology-driven natural LLM-based chatbots by customers. Originality/value This research study was based upon the PPM theoretical framework. This study provided a unique analysis of the altered firm customer interaction needs and requirements. This was one of the first studies that applied the framework of PPM theory regarding the adoption of AI technology-driven natural LLM-based chatbots by customers.

Maximizing CSR impact: Leveraging artificial intelligence and process optimization for sustainability performance management

AbstractThis study, which is anchored to Resource‐Based View (RBV) theory, explores the relationship between artificial intelligence (AI), process optimization, organizational flexibility, and sustainability performance in organizational settings. Leveraging the RBV framework's focus on internal resources as sources of competitive advantage, this research seeks to clarify how AI adoption, process optimization, and organizational flexibility foster sustainable growth. SPSS PROCESS Macro was used to analyze the data from 288 organizations. The findings derived from the empirical data, this study verify the positive relationships between AI and process optimization as well as AI and sustainability performance, revealing the strategic nature of AI as a resource to improve operational effectiveness and environmental responsibility. Further, our results indicate the mediating role of process optimization and the moderating effect of organizational flexibility in determining the link between AI and sustainability outcomes. Moreover, results confirmed the indirect effects of AI on sustainability performance via process optimization under the boundary conditions of the organizational flexibility. These findings add to the developing literature of sustainable operational practices and provide practical suggestions that might be useful for the practitioners aiming at using AI driven by organizational capabilities to deliver sustainability performance.

Artificial Intelligence (AI) in the Hospitality Industry: A Review Article

Purpose – Artificial intelligence (AI) adoption is critical in the age of digital technology. This review article aims to evaluate the literature on AI in the hospitality industry. Method – A narrative synthesis was used in this review article. Moreover, the literature was reviewed systematically to explore AI in the hospitality industry. The literature and information were obtained from various books and research articles on EBSCO, Google Scholar, Scopus, Web of Science, and Science Direct. The inclusion criteria were studies that clearly defined AI in all aspects of the hospitality industry, were published and written in English and were peer-reviewed. Content analysis was employed. Results – The use of AI is a strategic and critical factor in economic development. Furthermore, AI technologies are increasingly being used as digital assistants. They help businesses in the hospitality industry in a variety of ways, including improving customer service, expanding operational capability, and lowering costs. However, there are some risks associated with AI advancements, such as job loss in low-tech sectors, loss of control due to robot autonomy, and safety, security, and privacy concerns. Conclusion – AI technologies have both positive and negative effects on the workforce and job employment in the hospitality industry. Recommendations – The recommendation is to consider a quantitative study regarding AI adoption in the hospitality industry or other sectors. Also, a qualitative approach could give a clear view of insight results for further study. Research Implications – This review article contributed to the existing literature on AI adoption in the hospitality industry. Hence, it could be used to guide future research on AI adoption in the hospitality industry. It may also aid academics in broadening their research by incorporating more potential elements. Practical Implications – This review article could lead to a better understanding of AI adoption in the hospitality industry. Moreover, it may assist business owners, managers, and marketers in the hospitality industry or any sector to achieve and enhance high business performance by implementing appropriate strategies to meet the needs and expectations of both customers and employees through the use of AI.

Exploring cross-national divide in government adoption of artificial intelligence: Insights from explainable artificial intelligence techniques

Despite the recognized potential of artificial intelligence (AI) to improve governance, a significant divide in AI adoption exists among governments globally. However, little is known about the underlying causes behind the divide, hindering effective strategies to bridge it. Drawing on the AI capability concept and the Technology-Organization-Environment (TOE) framework, this study employs Explainable Artificial Intelligence (XAI) models to analyze the multifaceted factors influencing AI adoption by governments worldwide. The results underscore the critical roles of internet security and internet usage within the technological dimension, regulatory quality, government effectiveness, government expenditure, rule of law, and corruption control within the organizational dimension, and globalization, median age and GDP per capita within the environmental dimension. Notably, our analysis explores the intricate effects of these variables on government AI adoption, identifying inflection points where their impacts undergo significant shifts in magnitude and direction. This nuanced exploration provides a comprehensive understanding of government AI adoption globally and illustrates targeted strategies for governments to bridge the AI adoption divide, making theoretical, methodological and practical implications.

The use of artificial intelligence in marketing strategies: Automation, personalization and forecasting

The integration of Artificial Intelligence (AI) in marketing strategies is pivotal in the era of digital transformation, especially in automation, personalization, and forecasting. This research investigates the evolutionary role of AI in transitioning from traditional marketing frameworks to data-driven methodologies, thereby enhancing marketing efficiency and customer engagement. The increasing reliance on AI for strategic decision-making in marketing underscores the significance of this study. Employing a systematic literature review and thematic analysis, this research synthesizes data from an array of studies to thoroughly understand the impact of AI on marketing. The findings reveal that AI significantly streamlines marketing operations, fosters highly personalized marketing strategies, and enhances the accuracy of forecasting market trends and consumer behavior. However, this study also sheds light on the ethical and privacy concerns associated with the use of AI in marketing. Results point towards a significant transformation in marketing practices propelled by AI, marked by improvements in operational efficiency and customer interaction. Nevertheless, the study advocates the importance of addressing ethical considerations and privacy issues, emphasizing responsible AI deployment. The study offers a comprehensive perspective on the integration of AI in marketing and suggests insights into prospective trends. It recommends a balanced approach to leveraging AI’s capabilities while upholding ethical standards. The research’s practical implications aim to guide marketers and researchers towards responsible and effective AI adoption in marketing strategies, paving the way for a future where technology enhances marketing endevaours without compromising ethical integrity.

THE ROLE OF ARTIFICIAL INTELLIGENCE IN FINANCIAL DECISION-MAKING

In the realm of finance, decision-making processes have always been pivotal in determining the success or failure of individuals, businesses, and economies at large. With the advent of Artificial Intelligence (AI), this landscape is undergoing a profound transformation. The integration of AI technologies in financial decision-making is not merely an augmentation of existing processes but a fundamental shift in how decisions are conceived, analysed, and executed. This introduction seeks to delve into the evolving role of AI in financial decision-making, particularly within the context of the Indian financial sector. The rapid pace of technological advancement has propelled AI into the forefront of various industries, and finance is no exception. AI encompasses a spectrum of technologies, including machine learning, natural language processing, deep learning, and predictive analytics, among others. These tools offer the ability to process vast amounts of data, identify patterns, and generate insights at speeds and scales that were previously unimaginable. In the context of financial decision-making, this translates into enhanced capabilities for risk assessment, portfolio optimization, fraud detection, and customer service, among others. India, with its burgeoning economy and vibrant financial markets, stands at the cusp of this AI-driven revolution. The country's financial ecosystem, characterized by a diverse array of institutions ranging from traditional banks to fintech startups, is ripe for AI-led innovation. The adoption of AI in Indian finance is driven by several factors, including the proliferation of digital technologies, the increasing availability of data, and the imperative for efficiency and competitiveness in a globalized economy. Furthermore, initiatives such as the government's Digital India campaign and regulatory efforts to promote fintech innovation have created a conducive environment for AI adoption in the financial sector.

Adoption Intention of Employees Towards AI in Technology

The rapid advancement of artificial intelligence (AI) technology has led to its increasing adoption by businesses, promising transformative changes across various industries. However, despite its potential benefits, many organizations are still in the early stages of AI adoption, grappling with complexities and uncertainties surrounding its integration into operations. Concerns about the future of work, including issues related to data privacy, human value, biases, and transparency, have accompanied the rise of enterprise AI. Nevertheless, there is also optimism regarding AI's potential to enhance decision-making, stakeholder relationships, and innovation. Top management support plays a crucial role in facilitating AI adoption within organizations, with strong leadership seen as essential to overcoming adoption-related challenges. The technology-organizational-environment (TOE) framework provides a useful lens for understanding the adoption of AI within socioenvironmental and technological contexts. Despite significant progress in understanding AI adoption from an organizational perspective, the perspectives of employees remain relatively understudied. This research aims to address this gap by exploring how employees' cognitive and affective attitudes toward AI influence their behavioral responses during the pre-adoption phase. By utilizing the cognitive appraisal theory, this study seeks to uncover the factors shaping employees' attitudes toward AI and their intentions to use or leave organizations. Understanding these dynamics is essential for promoting a conducive environment for AI adoption and fostering creativity and innovation in the workplace. Additionally, this study utilized a Google Form questionnaire to collect data from employees.

Transforming Healthcare with AI: Promises, Pitfalls, and Pathways Forward.

This perspective paper provides a comprehensive examination of artificial intelligence (AI) in healthcare, focusing on its transformative impact on clinical practices, decision-making, and physician-patient relationships. By integrating insights from evidence, research, and real-world examples, it offers a balanced analysis of AI's capabilities and limitations, emphasizing its role in streamlining administrative processes, enhancing patient care, and reducing physician burnout while maintaining a human-centric approach in medicine. The research underscores AI's capacity to augment clinical decision-making and improve patient interactions, but it also highlights the variable impact of AI in different healthcare settings. The need for context-specific adaptations and careful integration of AI technologies into existing healthcare workflows is emphasized to maximize benefits and minimize unintended consequences. Significant attention is given to the implications of AI on the roles and competencies of healthcare professionals. The emergence of AI necessitates new skills in data literacy and technology use, prompting a shift in educational curricula towards digital health and AI training. Ethical considerations are a pivotal aspect of the discussion. The paper explores the challenges posed by data privacy concerns, algorithmic biases, and ensuring equitable access to AI-driven healthcare. It advocates for the development of comprehensive ethical frameworks and ongoing research to guide the responsible use of AI in healthcare. Conclusively, the paper advocates for a balanced approach to AI adoption in healthcare, highlighting the importance of ongoing research, strategic implementation, and the synergistic combination of human expertise with AI technologies for optimal patient care.

An Analysis of Artificial Intelligence Adoption in the Human Resource Management

An Analysis of Artificial Intelligence Adoption in the Human Resource Management

Implementing AI in banking customer service: A review of current trends and future applications

In the dynamic realm of banking, the advent of Artificial Intelligence (AI) has catalyzed a transformative shift, redefining the paradigms of customer service and operational efficiency. This scholarly paper delves into the intricate interplay between AI and banking, aiming to elucidate the multifarious impacts of AI integration within this sector. Anchored in a robust thematic analysis and an exhaustive literature review, the study meticulously navigates through the evolution, current applications and prospective future of AI in banking, with a particular focus on enhancing customer experience and addressing the operational challenges. The methodology adopted herein, comprising both qualitative and quantitative analyses, facilitates a comprehensive exploration of AI's role in banking, unveiling its potential to revolutionize service delivery, risk management and customer engagement. The findings from this investigation underscore the significant enhancements in customer service metrics attributed to AI, alongside the emergence of personalized banking experiences. Furthermore, the study illuminates the strategic implications for banks adopting AI technologies, highlighting the necessity of navigating ethical and privacy concerns meticulously. The conclusions drawn advocate for a balanced approach towards AI adoption, emphasizing the imperative of ongoing research and development, coupled with ethical considerations, to harness AI's full potential responsibly. In essence, this paper offers a scholarly synthesis of AI's transformative impact on banking, providing a roadmap for future explorations in this domain. It lays down the gauntlet for banks to leverage AI's potential judiciously, guiding the banking sector towards a future where technology and human ingenuity converge to redefine banking's essence. The recommendations proffered herein underscore the importance of ethical governance and continuous innovation in navigating the AI-driven future of banking.