Artificial intelligence: Building a research agenda

This paper aims at highlighting the increasing role of artificial intelligence in business and making familiar its various aspects vis-a-vis its immediate requirement in the present Indian business scenario. The paper takes into account the aspects of blockchain and deep learning components with regard to the business as future of artificial intelligence in business scenario. The study also includes the benefits and challenges of the use of artificial intelligence in business with influence of blockchain and deep learning. The relation between blockchain and deep learning and artificial intelligence has been discussed in this paper. The research collates findings from the use and implementation of components of blockchain and deep learning. The model is recommended in regard to future of artificial intelligence in business. The algorithm is written used for the implementation of artificial intelligence in business. The study concludes with the observations, future, and recommendations with respect to artificial intelligence in business with the implementation of blockchain and deep learning.

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.

The concept of Artificial Intelligence (AI) as a business-disruptive technology has developed in academic and professional literature in a chaotic and unstructured manner. This study aims to provide clarity over the phenomenon of business activation of AI by means of a comprehensive and systematic literature review, aimed at suggesting a clear description of what Artificial Intelligence is today. The study analyses a corpus of 3780 contributions through an original combination of two established machine learning algorithms (LDA and hierarchical clustering). The review produced a structured classification of the various streams of current research and a list of promising emerging trends. Results have shed light on six topics attributable to three different themes, namely Implications, Applications and Methods (IAM model). Our analysis could provide researchers and practitioners with a meaningful overview of the body of knowledge and research agenda, to exploit AI as an effective enabler to drive business value.

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.

Generative artificial intelligence is used to create new content and solutions through its ability to discover relationships in raw data, thus simulating the human thinking process. One particularly popular tool of this type is ChatGPT, which generates text and helps to solve a variety of problems. Consequently, it can also support company management by helping in the performance of various functions. By automating routine tasks, for example, it allows employees to focus on more strategic activities, while the use of data to identify trends supports informed decision-making, which enhances a company’s competitiveness and efficiency. The primary objective of the presented paper was to identify the key areas of application of ChatGPT in management. Accordingly, a quantitative and qualitative bibliometric analysis of the literature on this subject from the Web of Science and Scopus databases was undertaken, with a targeted selection of examples for case studies made based on the main research areas identified through bibliometric mapping. The article not only outlines the general trends related to the growth of the literature on ChatGPT in the field of management and quality sciences, but also specifies the main ways in which this tool supports management. It was noted that due to its ability to generate, automate, analyse and optimise, ChatGPT in management practice primarily supports (internal and external) communication, data use and problem solving.

- 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.

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.

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.