Adoption Of Artificial Intelligence Technologies Research Articles

Artificial Intelligence-Based Conversational Agents Used for Sustainable Fashion: Systematic Literature Review

In the past five years, the textile industry has undergone significant transformations in response to evolving fashion trends and increased consumer garment turnover. To address the environmental impacts of fast fashion, the industry is embracing artificial intelligence (AI) and immersive technologies, particularly leveraging conversational agents as personalized guides for sustainable fashion practices. In this research article, we conduct a systematic literature review to categorize techniques, platforms, and applications of conversational agents in promoting sustainability within the fashion industry. Additionally, the review aims to scrutinize the solutions offered, identify gaps in the existing literature, and provide insights into the effectiveness and limitations of these conversational agents. Utilizing a predefined search strategy on IEEE Xplore, Google Scholar, SCOPUS, and Web of Science, 15 relevant articles were selected through a step-by-step procedure based on the guidelines of the PRISMA framework. The findings reveal a notable global interest in AI-powered conversational agents, with Italy emerging as a significant center for research in this domain. The studies predominantly focus on consumer perceptions and intentions regarding the adoption of AI technologies, indicating a broader curiosity about how individuals incorporate such innovations into their daily lives. Moreover, a substantial proportion of the studies employ diverse methods, reflecting a comprehensive approach to understanding the functionality and performance of conversational agents in various contexts. While acknowledging the historical precedence of text-based agents, the review highlights a research gap related to embodied agents. The conclusion emphasizes the need for continued exploration, particularly in understanding the broader impact of these technologies on creating sustainable and environmentally friendly business models in the e-retail sector.

Business environment and adoption of AI: Navigation for internationalization by new ventures in emerging markets

AbstractThis study explores the intersection of international business and artificial intelligence (AI), focusing on how new ventures navigate environmental challenges for international expansion within Africa's transportation sector. Despite a wealth of literature on AI in developed countries, a notable gap exists in the understanding of the challenges emerging economies face in implementing AI practices, particularly in the context of Africa‐to‐Africa internationalization. The current study delved into the transformative potential of AI, identifying institutional voids as opportunities for innovation on the continent. Employing the Technology Organization and Environment framework, the study investigated the adoption of AI technology in the African business environment. Qualitative data gathered through interviews with transport tech startup founders across Africa provided insights into technological innovation, institutional dynamics, and market peculiarities. The founders recognized hurdles such as data scarcity, human resource constraints, and regulatory obstacles amid institutional voids. The study underscores the importance of understanding expectations, balancing possibilities and realities, and fostering collaboration. It offers valuable insights into the complexities faced by and opportunities for new ventures leveraging AI in internationalization, with practical implications for strategic AI implementation, policy development, market expansion, technology solutions, and cross‐border transportation within Africa's unique business landscape.

The Impact of Artificial Intelligence on Legal Systems: Challenges and Opportunities

The integration of artificial intelligence into legal systems has engendered a paradigm shift in the legal landscape, presenting a complex interplay of challenges and opportunities for the legal profession and the justice system. This Comprehensive research delves into the multifaceted impact of artificial intelligence on legal systems, focusing on its transformative potential and implications. Through an extensive analysis of the integration of artificial intelligence technologies, including natural language processing, machine learning, and predictive analytics, the study illuminates the profound improvements in legal research, decision-making processes, and case management, emphasizing the unprecedented efficiency and accessibility that artificial intelligence offers within the legal domain. Furthermore, the research critically examines the ethical and societal challenges stemming from artificial intelligence integration, including concerns related to data privacy, algorithmic bias, and the accountability of artificial intelligence-driven legal solutions. By scrutinizing the existing regulatory frameworks governing artificial intelligence implementation, the study underscores the necessity of responsible and ethical artificial intelligence integration, advocating for transparency, fairness, and equitable practices in the legal profession. The findings contribute to the ongoing discourse on the ethical implications and effective management of artificial intelligence integration in legal systems, providing valuable insights and recommendations for stakeholders and policymakers to navigate the complexities and ensure the responsible adoption of artificial intelligence technologies within the legal sphere

FIWARE-Compatible Smart Data Models for Satellite Imagery and Flood Risk Assessment to Enhance Data Management

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due to the rapidly increasing volume of heterogeneous data generated by multiple technologies. Hence, there is a need for efficient harmonization and smart modeling of the data to foster advanced AI analytical processes, which will lead to efficient water data management. The main objective of this work is to propose two Smart Data Models focusing on the modeling of the satellite imagery data and the flood risk assessment processes. The utilization of those models reinforces the fusion and homogenization of diverse information and data, facilitating the adoption of AI technologies for flood mapping and monitoring. Furthermore, a holistic framework is developed and evaluated via qualitative and quantitative performance indicators revealing the efficacy of the proposed models concerning the usage of the models in real cases. The framework is based on the well-known and compatible technologies on NGSI-LD standards which are customized and applicable easily to support the water data management processes effectively.

Impressing Artificial Intelligence: Automated Job Interview Training in Professional English Subjects

More organizations are using automated job interview platforms to screen candidates at the early stages of the recruitment process. These platforms enable job candidates to take automated video interviews remotely using their personal devices. The interviews are analysed by artificial intelligence (AI) powered algorithms to produce analytics which inform hiring decisions. In this article, we explore the use of automated job interviewing within professional English subjects delivered to undergraduate students in Hong Kong. The innovation was introduced to help students to keep up with recruitment practices, provide speaking practice and explore AI-powered evaluation as a form of feedback. As well as outlining how automated interviewing was integrated into our teaching practice, we discuss student feedback on the experience and offer suggestions for future teaching practice with this technology. We also highlight considerations for practitioners such as the acceptance and adoption of AI technologies into language learning provision and the development of AI literacy skills. AI technologies have much potential for language teaching and this article offers a practical exploration into one such technology: automated job interviewing.

TAM-TOE Integrated Perspective Research on Adoption of Artificial Intelligence Technology in Construction Projects

TAM-TOE Integrated Perspective Research on Adoption of Artificial Intelligence Technology in Construction Projects

Thematic Analysis through Artificial Intelligence (AI)

Thematic analysis, a well-enforced qualitative analytic method, is likely to continue evolving with the adoption of AI technologies. This how-to report does not delve into the details of thematic analysis itself, as there are ample existing studies on the topic. Instead, it acknowledges the potential impacts, dynamics, and pitfalls of AI in thematic analysis while offering valuable advice, particularly for novice analysts, on how to incorporate and document AI tools in each phase of a thematic analysis. The author underscores the importance of not allowing AI to overshadow the analyst's critical evaluative and interpretive skills but instead supporting the use of AI as an aid in thematic analysis, enhancing the depth and breadth of analysis, provided certain criteria are adhered to. This approach ensures that AI serves as a complementary tool, augmenting rather than replacing human analytical inquiry.

AI: A knowledge sharing tool for improving employees’ performance

ABSTRACT The utilisation of artificial intelligence (AI) is progressively emerging as a significant mechanism for innovation in human resource management (HRM). The capacity to facilitate the transformation of employee performance across numerous responsibilities. AI development, there remains a dearth of comprehensive exploration into the potential opportunities it presents for enhancing workplace performance among employees. To bridge this gap in knowledge, the present work carried out a survey with 300 participants, utilises a fuzzy set-theoretic method that is grounded on the conceptualisation of AI, KS, and HRM. The findings of our study indicate that the exclusive adoption of AI technologies does not adequately enhance HRM engagements. In contrast, the integration of AI and KS offers a more viable HRM approach for achieving optimal performance in a dynamic digital society. This approach has the potential to enhance employees’ proficiency in executing their responsibilities and cultivate a culture of creativity inside the firm.

The impact of AI technology adoption on operational decision-making in competitive heterogeneous ports☆

Artificial Intelligence (AI) technology is changing the industrial paradigm and has been widely adopted in port operations. Although AI technology can improve the efficiency of port operations and service quality, ports need to bear some costs. Discussing the role of applying AI technology to ports in complex competitive environments has become an important issue in the operations of ports and shipping. In this study, we construct a game-theoretic model of competitive heterogeneous ports. The research conclusions indicate that the adoption of AI technology by heterogeneous ports can enhance port profits. Unfortunately, simultaneous adoption exacerbates homogenized competition, posing a threat to profit realization. Furthermore, while the hub port can leverage AI-empowered capabilities to strengthen own competitiveness, it can undermine the performance of competitors and society at large. Surprisingly, the adoption of AI technology by feeder port is more advantageous in achieving social welfare and achieving multiple benefits such as carbon reduction.

Determinants influencing the adoption of artificial intelligence technology in non-life insurers.

Although artificial intelligence (AI) technology has been widely used in the insurance industry at a global scale, studies examining the adoption of AI technology in emerging markets are few and far between. This paper fills this gap by using Cronbach’s alpha, exploratory factor analysis, confirmatory factor analysis, and structural equation model (SEM) to discover significant factors affecting their behavioral intentions to adopt AI technology in Vietnam, a developing country. Data is collected from nearly 470 employees in Vietnamese non-life insurance firms. Empirical findings show that the most important determinant influencing the adoption of AI technology in Vietnamese non-life insurers is attitudes toward adoption. Attitudes toward adoption are positively related to the perceived ease of use and perceived usefulness, consistent with Gupta et al. (2022). Although perceived risk has a negative influence on the behavioral intention to adopt AI technology, it is not a serious issue for insurance companies.

The Impact of Artificial Intelligence on Unemployment among Educated People with Disabilities: An Empirical Analysis

The impact of artificial intelligence (AI) on unemployment is a subject of debate among researchers and policymakers. This study investigates how AI affects unemployment among educated people with disabilities in 33 countries from 2004 to 2021. Several conclusions have been reached. First, both static and dynamic panel data estimators show that AI reduces aggregate unemployment and unemployment among educated men with disabilities. In contrast, there is no significant impact on the unemployment of educated women with disabilities. Second, the panel smooth transition regression model provides compelling evidence for the existence of two regimes and a nonlinear impact of AI on unemployment among educated women with disabilities. The impact is not significant when AI is low (first regime), but the situation changes when AI exceeds a given threshold level (second regime). Therefore, educated women with disabilities may have more opportunities to integrate into the job market due to the increased adoption of AI. Countries are recommended to foster an employment-friendly environment that promotes inclusion and equitable opportunity for educated people with disabilities by developing and encouraging the adoption of AI technologies.

Aligning artificial intelligence with ethical accountancy: A global perspective on emerging frameworks

This study meticulously examines the integration of artificial intelligence (AI) into the accounting sector, revealing transformative opportunities alongside emerging ethical challenges. Drawing inspiration from established principles of the American Institute of Certified Public Accountants (AICPA) Code of Professional Conduct (AICPA, 2016), an innovative Accounting Framework for AI Ethics (AFAIE) is introduced. This framework aims to provide a tailored approach that ensures that the adoption of AI technologies aligns with the fundamental professional values of trust and integrity. It aims to address the concerns and potential risks associated with the use of AI and establish guidelines that promote accountability and transparency in the development and deployment of AI systems. The essence of this research is underscored by the advocacy for resilient ethical paradigms that are instrumental in navigating the complexities introduced by AI in accounting. Emphasizing a global perspective, this study advocates universal ethical guidelines, ensuring adaptability to specific regional and professional contexts (Association of Chartered Certified Accountants [ACCA], 2016; Bertucci et al., 2021). This synthesis of technology and ethics aims to foster an environment in which innovation thrives alongside steadfast adherence to professional integrity and responsibility.

Role of Artificial Intelligence in Transforming Work Engagement on Unorganised Sector

Abstract: Technological advancement made a tremendous change among the workers. In India majority of the workers were in unorganized or in the informal sector. While considering our traditional economic system, these workers were considered as the margin of the economy. But artificial intelligence (AI) have the possibility to take these workers to the mainstream of the economy. Even these changes happen but still some of the people were also under the disparity to access these technologies effectively. If they use artificial intelligence (AI) at its full potential these workers can increase their productivity to a great extent. Work engagement means a person’s emotional attachment to his work; because he believes that his action can make changes in the current scenario. A highly engaged worker is considered an asset to the organization. By utilizing the possibilities of AI the workers in the unorganized sector can also create new trends of jobs. Even though these changes happened, some of the workers were struggling to adapt to these changes. This study mainly focused on how these issues can be solved through work engagement, how to increase the number of workers, and how to get them into the mainstream of the economy. The study primarily focused on the relationship between work engagement and the adoption of AI technology in the unorganized sector.

Explainability and Evaluation of Vision Transformers: An In-Depth Experimental Study

In the era of artificial intelligence (AI), the deployment of intelligent systems for autonomous decision making has surged across diverse fields. However, the widespread adoption of AI technology is hindered by the risks associated with ceding control to autonomous systems, particularly in critical domains. Explainable artificial intelligence (XAI) has emerged as a critical subdomain fostering human understanding and trust. It addresses the opacity of complex models such as vision transformers (ViTs), which have gained prominence lately. With the expanding landscape of XAI methods, selecting the most effective method remains an open question, due to the lack of a ground-truth label for explainability. To avoid subjective human judgment, numerous metrics have been developed, with each aiming to fulfill certain properties required for a valid explanation. This study conducts a detailed evaluation of various XAI methods applied to the ViT architecture, thereby exploring metrics criteria like faithfulness, coherence, robustness, and complexity. We especially study the metric convergence, correlation, discriminative power, and inference time of both XAI methods and metrics. Contrary to expectations, the metrics of each criterion reveal minimal convergence and correlation. This study not only challenges the conventional practice of metric-based ranking of XAI methods but also underscores the dependence of explanations on the experimental environment, thereby presenting crucial considerations for the future development and adoption of XAI methods in real-world applications.

A Study on the Impact of Artificial Intelligence in Small and Medium Enterprises

In the contemporary business landscape, the integration of Artificial Intelligence (AI) has emerged as a transformative force, reshaping traditional paradigms across various industries. This study delves into the specific realm of Small and Medium Enterprises (SMEs) to explore the profound impact of AI adoption on their operational efficiency, innovation capabilities, and overall competitiveness. The research employs a multi-faceted approach, incorporating both quantitative and qualitative analyses. Through surveys, interviews, and case studies, we investigate the extent to which SMEs have embraced AI technologies, identifying the key drivers and barriers to adoption. The study also assesses the impact of AI on workforce dynamics, shedding light on how automation and augmentation have influenced job roles and skills requirements within these enterprises. Furthermore, the research evaluates the role of AI in enhancing decision-making processes, resource allocation, and customer engagement for SMEs. By examining real-world applications and success stories, the study aims to provide practical insights into the ways in which AI can be leveraged to optimize business operations and foster innovation in smaller enterprises. An essential aspect of this research involves addressing the ethical considerations and challenges associated with AI implementation in SMEs. Privacy concerns, data security, and potential biases in algorithms are examined to offer a comprehensive understanding of the risks and responsibilities that accompany the adoption of AI technologies. Ultimately, this study contributes to the existing body of knowledge by offering a nuanced perspective on the impact of AI in SMEs. The findings aim to inform policymakers, business leaders, and researchers about the opportunities and challenges inherent in integrating AI into the fabric of small and medium-sized enterprises, thereby facilitating informed decision making and strategic planning for a technologically advanced future.

Revolutionizing Education: The Transformative Power of AI Technologies in PR

In the coming years, Artificial Intelligence (AI) is set to make a profound impact on higher education, particularly within the field of Public Relations (PR). This surge in the adoption of AI technologies in academia is fuelled by compelling factors. AI is on the verge of transforming PR practices, elevating the efficiency and effectiveness of communication strategies. The data-driven prowess of AI equips PR professionals with enhanced capabilities to understand and engage with target audiences, tailor messages with precision, automate routine tasks, such as content creation, social media management, and data analysis, and liberate practitioners from administrative burdens. As educational institutions increasingly recognize the value of AI in PR, investments in its implementation are expected, heralding a paradigm shift in higher education communication and stakeholder engagement. The current article aims to delve into the European framework for AI applications in education, present the landscape of existing technology tools used in the communication area, and review recent publications describing the benefits and possible drawbacks of using generative AI technologies in the sphere of teaching.

AI Ethics and Bias: Exploratory study on the ethical considerations and potential biases in ai and data-driven decision-making in banking, with a focus on fairness, transparency, and accountability

The integration of Artificial Intelligence (AI) and data-driven decision-making in the banking industry has ushered in unprecedented opportunities for efficiency, risk assessment, and customer service. However, this rapid adoption of AI technology comes with its own set of ethical considerations and potential biases. This research paper delves into the intricate landscape of AI ethics and bias within the banking sector, with a central emphasis on fairness, transparency, and accountability. In sum, this paper contributes to the ongoing discourse on AI ethics and bias by providing valuable insights into the ethical considerations and potential biases inherent in AI and data-driven decision-making within the banking sector. It underscores the necessity of fairness, transparency, and accountability as guiding principles in the responsible integration of AI technology in banking, while also presenting future research directions for this evolving field.

Factors Influencing the Adoption of Artificial Intelligence Technologies in Agriculture, Livestock Farming and Aquaculture: A Systematic Literature Review Using PRISMA 2020

Food production faces significant challenges, mainly due to the increase in the Earth’s population, combined with climate change. This will create extreme pressure on food industries, which will have to respond to the demand while protecting the environment and ensuring high food quality. It is, therefore, imperative to adopt innovative technologies, such as Artificial Intelligence, in order to aid in this cause. To do this, we first need to understand the adoption process that enables the deployment of those technologies. Therefore, this research attempts to identify the factors that encourage and discourage the adoption of Artificial Intelligence technologies by professionals working in the fields of agriculture, livestock farming and aquaculture, by examining the available literature on the subject. This is a systematic literature review that follows the PRISMA 2020 guidelines. The research was conducted on 38 articles selected from a pool of 225 relevant articles, and led to the identification of 20 factors that encourage and 21 factors that discourage the adoption of Artificial Intelligence. The factors that appeared most were of economic nature regarding discouragement (31.5%) and product-related regarding encouragement (28.1%). This research does not aim to quantify the importance of each factor—since more original research becoming available is needed for that—but mainly to construct a list of factors, using spreadsheets, which could then be used to guide further future research towards understanding the adoption mechanism.

What Makes Work “Good” in the Age of Artificial Intelligence (AI)? Islamic Perspectives on AI-Mediated Work Ethics

AbstractArtificial intelligence (AI) technologies are increasingly creeping into the work sphere, thereby gradually questioning and/or disturbing the long-established moral concepts and norms communities have been using to define what makes work good. Each community, and Muslims make no exception in this regard, has to revisit their moral world to provide well-thought frameworks that can engage with the challenging ethical questions raised by the new phenomenon of AI-mediated work. For a systematic analysis of the broad topic of AI-mediated work ethics from an Islamic perspective, this article focuses on presenting an accessible overview of the “moral world” of work in the Islamic tradition. Three main components of this moral world were selected due to their relevance to the AI context, namely (1) Work is inherently good for humans, (2) Practising a religiously permitted profession and (c) Maintaining good relations with involved stakeholders. Each of these three components is addressed in a distinct section, followed by a sub-section highlighting the relevance of the respective component to the particular context of AI-mediated work. The article argues that there are no unsurmountable barriers in the Islamic tradition against the adoption of AI technologies in work sphere. However, important precautions should be considered to ensure that embracing AI will not be at the cost of work-related moral values. The article also highlights how important lessons can be learnt from the positive historical experience of automata that thrived in the Islamic civilization.

The Transformative Potential of AI in Obstetrics and Gynaecology

The transformative power of artificial intelligence (AI) is reshaping diverse domains of medicine. Recent progress, catalyzed by computing advancements, has seen commensurate adoption of AI technologies within obstetrics and gynaecology. We explore the use and potential of AI in three focus areas: predictive modelling for pregnancy complications, Deep learning-based image interpretation for precise diagnoses, and large language models enabling intelligent health care assistants. We also provide recommendations for the ethical implementation, governance of AI, and promote research into AI explainability, which are crucial for responsible AI integration and deployment. AI promises a revolutionary era of personalized health care in obstetrics and gynaecology.