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Integrating artificial intelligence (AI) into various industries, including the financial sector, has transformed them. This paper aims to examine the influence of integrating AI, including machine learning, process automation, predictive analytics and chatbots, on financial institutions and explores its various aspects and areas. The study aims to determine the impact of AI integration on financial services, products and customer experience.

The research study uses quantitative and qualitative methods, as well as secondary data analysis. It investigates four AI subfields: machine learning, process automation, predictive analytics and chatbots.

The research findings indicate that integrating AI, particularly in machine learning and chatbot subfields, holds promise and high strategic potential for financial institutions. These subfields can contribute significantly to enhancing financial services and customer experience. However, the significance of predictive analytics integration and process automation is relatively lower. Although these subfields retain their usefulness, they might necessitate alternative workflows and tools that incorporate human involvement. Overall, AI integration minimizes human interactions and errors in financial institutions.

The research study contributes original insights by exploring the specific subfields of AI within the financial industry and assessing their strategic significance. It provides recommendations for financial institutions to adopt AI integration partially in multiple phases, measure and evaluate the impact of the transformation and structure internal units and expertise to strategize adoption and change.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

This study aims to explore the collaborative potential of Microsoft Copilot and Anthropic Claude AI as an assistive technology in education and library services. The research delves into technical architectures and various use cases for both tools, proposing integration strategies within educational and library environments. The paper also addresses challenges such as algorithmic bias, hallucination and data rights.

The study used a literature review approach combined with the proposal of integration strategies across education and library settings.

The collaborative framework between Copilot and Claude AI offers a comprehensive solution for transforming education and library services. The study identifies the seamless combination of real-time internet access, information retrieval and advanced comprehension features as key findings. In addition, challenges such as algorithmic bias and data rights are addressed, emphasizing the need for responsible AI governance, transparency and continuous improvement.

Contribute to the field by exploring the unique collaborative framework of Copilot and Claude AI in a specific context, emphasizing responsible AI governance and addressing existing gaps.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.

The integration of artificial intelligence (AI) technologies like conversational AI and HR chatbots in international human resource development (HRD) presents both productivity benefits and ethical challenges. This study aims to examine the ethical dimensions of AI-driven HR chatbots, emphasizing the need for fairness, autonomy and nondiscrimination. It discusses inherent biases in AI systems and addresses linguistic, cultural and accessibility issues. The paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework. By embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.

Systematic literature review.

The paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework.

By embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.

This study explores the intricate ethical landscape surrounding AI-driven HR chatbots, spotlighting the imperatives of fairness, autonomy, and nondiscrimination. Uncovering biases inherent in AI systems, it addresses linguistic, cultural, and accessibility concerns. Proposing a pioneering “risk management by design” framework, the study advocates for a holistic approach to ethical integration, ensuring organizations navigate the complexities of AI-driven HR technologies while prioritizing fairness and equity in global workforce management.

This study aims to analyse the ethical implications associated with the development of artificial intelligence (AI) technologies and to examine the potential ethical ramifications of AI technologies.

This study undertakes a thorough examination of existing academic literature pertaining to the ethical considerations surrounding AI. Additionally, it conducts in-depth interviews with individuals to explore the potential benefits and drawbacks of AI technology operating as autonomous ethical agents. A total of 20 semi-structured interviews were conducted, and the data were transcribed using grounded theory methodology.

The study asserts the importance of fostering an ethical environment in the progress of AI and suggests potential avenues for further investigation in the field of AI ethics. The study finds privacy and security, bias and fairness, trust and reliability, transparency and human–AI interactions as major ethical concerns.

The implications of the study are far-reaching and span across various domains, including policy development, design of AI systems, establishment of trust, education and training, public awareness and further research. Notwithstanding the potential biases inherent in purposive sampling, the constantly evolving landscape of AI ethics and the challenge of extrapolating findings to all AI applications and contexts, limitations may still manifest.

The novelty of the study is attributed to its comprehensive methodology, which encompasses a wide range of stakeholder perspectives on the ethical implications of AI in the corporate sector. The ultimate goal is to promote the development of AI systems that exhibit responsibility, transparency and accountability.

The purpose of this research paper is to explore the significance of language processing in library systems and evaluate the effectiveness of integrating artificial intelligence and generative pre-trained transformer (GPT) technology in modern libraries. Specifically, the paper focuses on SheetGPT, a Google Sheet and GPT Plugin and its impact on language processing in library systems.

This paper adopts a comprehensive analysis approach to evaluate the integration of SheetGPT in library systems. The authors outlined a user-friendly approach for installation and use of SheetGPT using its “beginner plan”, appropriate for personal/student use or extended experimentation. The study includes a quantitative analysis to provide a thorough understanding of the benefits and limitations of SheetGPT in library systems.

The findings of this research paper suggest that SheetGPT is a highly effective language-processing tool for library systems. Additionally, ChatGPT’s integration with Google Sheets and easy accessibility over Google Marketplace makes it an efficient and user-friendly tool for library professionals. Overall, this study highlights the potential of SheetGPT to enhance language processing in library systems

This research paper contributes to the existing literature by providing a comprehensive analysis of the effectiveness of SheetGPT in library systems. The study’s approach is unique in that it evaluates SheetGPT’s impact on language processing and provides insights into its benefits and limitations. The study’s findings are original and provide a valuable resource for library professionals and researchers interested in exploring the potential of SheetGPT to enhance language processing in library systems.

This study aims to present a research model to investigate the potential impact of human capital, structural capital and social capital on e-banking proactiveness. In addition, it reveals the potential impact of e-banking proactiveness on competitive intelligence and competitive agility. Also, it aims to explore the impact of competitive intelligence on competitive advantage and competitive agility. Finally, the impact of competitive agility on competitive advantage will be examined.

In order to gather data, a questionnaire was prepared and administered to 211 respondents in Jordan. The research model and hypotheses were then assessed using Structural Equation Modeling – Partial Least Squares (SEM-PLS).

The study demonstrated a significant impact of human capital, structural capital and social capital on e-banking proactiveness. The findings confirm that e-banking proactiveness significantly impacts competitive intelligence and achieving competition. Moreover, the findings confirm that competitive intelligence significantly impacts competitive agility. Also, the findings revealed a substantial relationship between competitive intelligence and competitive advantage. Finally, the results discovered that competitive agility significantly impacts competitive advantage.

The research gives valuable insights into the elements that drive e-banking proactiveness, which can beautify the proactiveness literature is well-known. By uncovering the position of intellectual capital in fostering proactiveness, this examination contributes to deeper information on the way financial institutions can successfully respond to market modifications, patron needs and technological advancements. Future scholars can build upon these findings to discover proactiveness in different sectors and industries, thereby broadening the understanding of proactive behaviors throughout numerous contexts.

The widespread integration of artificial intelligence (AI)-enabled personalization has sparked a need for a deeper understanding of its transformative potential. To address this, this study aims to investigate the mental models held by consumers from diverse cultures regarding the impact and role of AI-enabled personalization in their lives (i.e. individual well-being) and in society (i.e. societal well-being).

This paper uses the theories-in-use approach, collecting qualitative data via the critical incident technique. This data encompasses 487 narratives from 176 consumers in two culturally distinct countries, Belgium and Pakistan. Additionally, it includes insights from a focus group of six experts in the field.

This research reveals that consumers view AI-enabled personalization as a dual-edged sword: it may both extend and restrict the self and also contribute to an affluent society as well as an ailing society. The particular aspects of the extended/restricted self and the affluent/ailing society that emerge differ across respondents from different cultural contexts.

This cross-cultural research contributes to the personalization and well-being literature by providing detailed insight into the transformative potential of AI-enabled personalization while also having important managerial and policy implications.