An Approach to Secure Collaborative Recommender System Using Artificial Intelligence, Deep Learning, and Blockchain

Objective: The existing literature on artificial intelligence is reviewed with the aim of identifying interesting and novel research avenues. This leads to a focus on experiences, customisation, diversity and strategy as the main issues requiring further investigation. Research Design & Methods: A systematic literature review was conducted on articles related to artificial intelligence and business using various databases including Scopus, Web of Science and Google Scholar. Findings: Artificial intelligence is a hot topic particularly for international business managers who are incorporating technological innovation for competitive reasons. This article focuses on the link between artificial intelligence and international business in terms of future research opportunities. Implications & Recommendations: The results of this study will help business managers and practitioners understand the main trending areas related to artificial intelligence in a business setting. It is recommended that academic researchers and policy makers consider the future research suggestions stated in the article in order to help them derive new research directions. Contribution & Value Added: Potential research topics and questions are stated that help international business researchers and practitioners focus on key important areas. Thereby helping to consolidate the existing research but also offering new possibilities regarding the use of artificial intelligence in international business.

The lack of scientific research on whether there are, and if so, how big are the differences in the attitudes of population about the effects of artificial intelligence on increasing the effectiveness of marketing messages is a research problem. Descriptions of the strength of attitudes of different groups of respondents are broken down by gender, age, highest level of education and work status on whether does the use of artificial intelligence in marketing increases the effectiveness of marketing messages and explanations of reasoning for such strong attitudes represent goal and science contribution of this research. Results of the research are positive, in other words, there is a general understanding among the respondents that artificial intelligence should be used in marketing to increase its effectiveness. The authors consider that over time there will be an increase of the understanding of the benefits in using artificial intelligence in marketing and overall business because increase of usage of artificial intelligence in business is also trending in Croatia.

The purpose of this paper is to review the use of knowledge-based systems and artificial intelligence (AI) in business. Part I of this paper examines domain applications, the use of different knowledge representations, unique contributions for knowledge acquisition from the development of systems for business applications, and models of explanation for systems developed for business. In addition, the paper discusses the use of both normative and descriptive AI systems to model business judgments. Finally, the paper provides a summary of publication sources and meetings on business systems.

The role of artificial intelligence (AI) in business and management decision-making has become one of the most intensively studied areas in recent years. The present study conducts a bibliometric analysis based on 4,165 publications in the Web of Science database in order to map the main structural and thematic characteristics of the scientific discourse. It is possible to identify three dominant scientific clusters based on the co-occurrence of keywords, co-citation networks, and scientific collaborations between countries. The following three approaches have been identified: firstly, technology- and algorithm-focused approaches; secondly, organisational and human-centred interpretations; and thirdly, research based on business decision support and information management. The objective of the present study is to emphasise that AI is not merely a technological innovation, but rather an interdisciplinary phenomenon that fundamentally transforms the organisational, ethical and strategic frameworks of decision-making. The results obtained contribute to a more accurate understanding of research trends in the field and provide a basis for further analysis.

This systematic review research with bibliographic analysis, aimed to analyze the use of artificial intelligence in business. The PRISMA methodology was used to obtain a final set of (n = 43) articles from the Scopus database over a 4-year period from 2020 to 2024. The final set of articles is classified into a taxonomy comprising five groups: (1) finance (n = 8), (2) production (n = 9), (3) customer service (n = 9), (4) technology and business innovation (n = 8) and (5) human resources (n = 9). It also presents a bibliographic analysis based on the annual scientific production, of 108 articles found in a period of 5 years from 2018 to 2023, from databases such as Scopus, Science direct and google academic. It concludes that the use of artificial intelligence (AI) in business has a significant impact in various areas.

Artificial Intelligence (AI) is transforming business operations by providing advanced solutions that enhance efficiency, productivity, and data-driven decision-making across multiple sectors.AI technologies such as machine learning, natural language processing, and automation systems are being widely adopted to optimise processes, reduce operational costs, and improve overall performance.However, alongside these benefits, AI adoption also raises significant ethical challenges, including algorithmic bias, data privacy violations, and job displacement, particularly in industries reliant on routine tasks.This study investigates the impact of AI on both operational efficiency and ethical decision-making with a particular focus on three key industries: healthcare, automotive, and telecommunications.Through a mixed-method approach combining quantitative surveys of 500 business owners and qualitative case studies from 12 organizations, the research tests four hypotheses.These hypotheses examine AI's impact on operational efficiency, ethical challenges, job displacement, and factors influencing adoption based on the Technology Acceptance Model (TAM).The findings demonstrate that while AI adoption leads to substantial efficiency gains, the risks associated with bias, privacy concerns, and workforce displacement require careful governance.To ensure responsible AI implementation, this study advocates for the adoption of Ethical AI Frameworks grounded in both deontological and utilitarian ethical principles.These frameworks provide businesses with strategies to mitigate risks while maintaining a competitive advantage.The study concludes with practical recommendations for businesses on how to integrate AI into their operations in a way that balances the benefits of enhanced efficiency with the responsibility of addressing ethical concerns, ultimately bridging the gap in the literature on the dual role of AI in modern business.

The application of artificial intelligence in business is increasing as it enables the automation of business processes and faster decision-making. Artificial intelligence can be used in marketing, production, sales, and finance. The key advantage of its use lies in improving business efficiency and reducing costs. Business automation leads to faster operations and cost reduction. In the field of customer relations, artificial intelligence can analyze large amounts of user behavior data to suggest personalized products and services, thereby creating a better user experience. However, the use of artificial intelligence in business also comes with challenges. One of the biggest challenges is the ethical use of artificial intelligence in business, as well as the shortage of experts in this field. Additionally, many aspects of AI implementation in business remain unexplored and unclear, creating opportunities for various types of fraud. Whenever a new technology like artificial intelligence emerges, there will always be individuals who seek to exploit it for personal gain through fraudulent activities.

Although AI is a helpful tool for the evolving business environment, its uncontrolled and fast integration into business processes can bring legal and ethical challenges. This research paper delves into the legal and ethical considerations essential for effectively regulating AI in business environments. As AI systems increasingly influence decisionmaking processes and operational efficiencies, the need for comprehensive and forward-thinking regulation becomes imperative. Thus, in the aspects of ethics, algorithms are utilized to protect rights or prohibit discrimination and ensure the openness of AI’s decisions. This paper examines key legal issues such as data privacy, intellectual property rights, and liability. For example, while the General Data Protection Regulation (GDPR) provides a framework for data protection, it remains unclear how these provisions apply to AI's sophisticated data handling and automated decision-making processes.. Ethical considerations further complicate the regulatory landscape. AI systems can inadvertently perpetuate biases present in their training data, leading to discriminatory practices and fairness concerns. This paper explores the ethical implications of such biases and the need for transparency in AI algorithms to ensure that they operate in a manner consistent with societal values. To address these challenges, the paper proposes a regulatory approach. It advocates for the modernization of existing legal frameworks to better encompass AI-related issues, and the establishment of ethical standards to guide AI deployment. Indeed, this article will explore some legal and ethical aspects of using Artificial Intelligence in the business world. Ethical AI guidelines and policies will be discussed, annual checkers will be conducted, and ethical AI standards will be promoted. In addition, identifying potential opportunities and threats likely to emerge when AI is even more entrenched in organizational activities will be relevant. After reviewing this article, you should know how to harness AI's power while avoiding legal issues.

Artificial intelligence (AI) has emerged as one of the most transformative technologies shaping contemporary organisations, economies and managerial practices. Although recent advances—particularly in machine learning, deep learning and generative AI—have intensified academic and managerial interest, the foundations of AI research in business and management extend well beyond the current wave of technological enthusiasm. This study aims to provide a comprehensive review of the evolution of artificial intelligence and to examine how AI-related technologies have been conceptualised, adopted and analysed within the business and management literature. Drawing on an extensive review of international studies, the article synthesises research across key managerial domains, including strategic decision-making, human resource management, innovation, governance, ethics and organisational performance. The findings indicate that AI has moved beyond its role as an operational efficiency tool and increasingly functions as a strategic and organisational capability, reshaping managerial decision processes, organisational structures and human–machine collaboration. At the same time, the literature highlights persistent challenges related to algorithmic bias, transparency, data governance, regulatory uncertainty and workforce adaptation. By integrating theoretical discussions with practical examples, this study contributes to the growing body of management research by clarifying dominant research streams, identifying conceptual gaps and outlining future research directions. The article concludes that while artificial intelligence offers significant opportunities for enhancing organisational performance and competitiveness, its effective and responsible integration requires careful managerial, ethical and institutional consideration.

In the 21st century, artificial intelligence has been recognized as the main driver of universal progress. It has already gained a place in the economy of developed countries. It is used in both public and private sectors: in education, transport, finance and banking sector, medicine, and so on.Based on the scientific papers of artificial intelligence researchers, it is clear that small and medium-sized businesses can get significant benefits from artificial intelligence use. Small and medium-sized enterprises often work with limited resources, and automating repetitive tasks that can be performed with the help of artificial intelligence can help them save time and costs. Through artificial intelligence, SMEs are empowered to make data-driven decisions, improve their products or services, and identify new opportunities.The paper discusses the possibilities of using artificial intelligence in business, how AI can transform business operations and, therefore, the global economy, highlights the positive and negative aspects of AI, and expresses opinions in the direction of reducing the challenges associated with the introduction of artificial intelligence.

- The rapid technological developments in recent decades provide most effective expertise business environment for the Entrepreneurs. In this digital era, the Entrepreneurs need to respond quickly to the increasing demands from the consumers. Artificial intelligence (AI) is a dominant technology with machine learning capabilities, which are currently used in all the business sectors. A recent trend in Artificial Intelligence highly concentrates on the development of machine learning based applications which change the landscape of business industry. The emerging AI tools handles massive amount of business data efficiently and facilitate almost every business operation which in turn increases productivity. Eventually, the advance in technology also brings several business risks and challenges. This paper briefly describes the impact of Artificial Intelligence in Business and explores latest Artificial Intelligence applications and tools available in business environment which lowers the operational expenses and become boon for Entrepreneurs. This paper also discusses some of the major challenges in business and supportive AI tools which offers operative solution to overcome these challenges particularly in the three major business fields namely Finance, Marketing and Human Resources, as well as to improve the business efficiency. Keywords: Artificial Intelligence, Business Challenges, AI Tools, Finance, Marketing, Human Resources.

This paper studies the impact of Artificial Intelligence (AI) in modifying business practices in the banking and finance industry, mainly as it applies in India. It considers important AI tools like machine learning, natural language processing and robotic process automation to check their influence on service pleasure, customer happiness, accurate solutions and managing problems. With a quantitative study of 60 participants, the paper finds that and that AI-based financial services are highly appreciated, especially for fraud detection and customer support. At the same time, it reveals major issues about privacy, clear explanations of how algorithms work and threats to people’s jobs. AI in finance, according to these findings, boosts workflow and user service, but also asks for close monitoring, revised regulations and trainings for users. This paper takes part in the debate about good AI practices and gives useful advice to banks, policymakers and those working in fintech. Keywords- Artificial Intelligence, Banking, Finance, Customer Satisfaction, Fraud Detection, Data Privacy, Automation, Decision-Making, Ethical Concerns, India.

Artificial Intelligence (AI) refers to using human intelligence in machines through technological innovations. AI is already widely diffused in different sectors to provide quality services. Recently, organizations worldwide have also started adopting different types of AI for a wide range of Human Resource Management (HRM) practices aimed at efficiently and effectively designing jobs; employing, training, and compensating people; and developing strategies to retain them. Nevertheless, little is known about the objectives and consequences of AI use for HRM. The existing literature is fragmented and rarely discusses actual AI applications.

Artificial Intelligence (AI) has emerged as a transformative force in business and management, significantly impacting operations, decision-making, customer experience, and overall organizational effectiveness. This paper explores the applications of AI in various sectors, focusing on how businesses integrate AI technologies to optimize efficiency, enhance customer satisfaction, and drive innovation. Through an extensive literature review and case studies, the study identifies the current trends, challenges, and future implications of AI adoption in business practices. The research also presents the impact of AI on managerial strategies, decision-making, and organizational change. Recommendations for companies looking to implement AI solutions are provided, emphasizing the need for strategic planning, skilled talent, and ethical considerations.

Cutting through the hype, a practical guide to using artificial intelligence for business benefits and competitive advantage. In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM's Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient. Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed—important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning (“analytics on steroids”), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise. Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI. A book in the Management on the Cutting Edge series, published in cooperation with MIT Sloan Management Review.