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Articles de revues sur le sujet « Trends in AI »

Auteur : Grafiati

Publié le 7 juin 2025

Mis à jour le 2 août 2025

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1

Mucsková, Monika. "Transforming Banking with Artificial Intelligence." Trends Economics and Management 18, no. 42 (2024): 21–37. http://dx.doi.org/10.13164/trends.2024.42.21.

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Purpose of the article: The purpose of this article is to provide a comprehensive analysis of the role of artificial intelligence (AI) in the banking sector, focusing on its applications, challenges, and implications. By synthesizing existing research and empirical studies, the article aims to inform researchers about the transformative potential and inherent challenges of AI-driven innovation in banking. Methodology/methods: Using a systematic review approach, the relevant literature on AI integration in banking was identified from electronic databases and leading corporate research departmen

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Alok, Kumar. "AI-Driven Market Trend Analysis." Journal of Research and Innovation in Technology, Commerce and Management Volume 2, Issue 4 (2025): 2454–61. https://doi.org/10.5281/zenodo.15301748.

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Artificial Intelligence (AI) has changed market trend analysis through real-time scanning and accurate forecasting of trends. AI technologies, such as machine learning, natural language processing (NLP) and big data analytics, allow organizations to uncover trends, take actions and displace the constraints of traditional methods. This research studies AI-oriented methods, including sentiment analysis, deep learning and predictive modeling. It demonstrates the ability of AI to process significant amounts of data, the areas AI might be used and discusses limitations, such as data quality issues,

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Li, Meng, Ronghao Chu, Abu Reza Md Towfiqul Islam, Yuelin Jiang, and Shuanghe Shen. "Attribution Analysis of Long-Term Trends of Aridity Index in the Huai River Basin, Eastern China." Sustainability 12, no. 5 (2020): 1743. http://dx.doi.org/10.3390/su12051743.

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This paper aims to combinedly investigate the spatiotemporal trends of precipitation (Pre), reference evapotranspiration (ET0), and aridity index (AI) by employing nonparametric methods based on daily datasets from 137 meteorological stations during 1961–2014 in the Huai River Basin (HRB). The dominant factors influencing ET0 and AI trends were also explored using the detrended and differential equation methods. Results show that (1) Pre, ET0, and AI were much larger in summer than in other seasons, and AI had a nonsignificant increasing trend in annual time scale, while Pre and ET0 exhibited

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Y, Sanjai, and Kotteswaran D. "Emerging Trends in Marketing and AI." International Journal of Research Publication and Reviews 6, no. 4 (2025): 6074–80. https://doi.org/10.55248/gengpi.6.0425.15197.

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Bahcecik, Serif Onur. "I TRENDS Security Politics and Artificial Intelligence: Key Trends and Debates." International Political Science Abstracts 73, no. 3 (2023): 329–38. http://dx.doi.org/10.1177/00208345231182638.

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This article delves into the academic discourse surrounding the security implications of artificial intelligence (AI). It highlights the lack of consensus on what AI truly encompasses, which poses challenges for regulating the technology. While some express concerns about the security risks of AI, there are proponents of ethical AI who believe in the possibility of programming the technology to operate ethically, and supporters of AI for Good (or AI for Social Good) who see potential for AI to address sustainable development challenges. Scholars agree that AI will have a significant impact on

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Cho, Bo ram. "Research Trend of University AI-based education." Korean Association For Learner-Centered Curriculum And Instruction 25, no. 1 (2025): 447–62. https://doi.org/10.22251/jlcci.2025.25.1.447.

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Objectives This study aims to analyze research trends in university AI-based education and provide implications for future university AI-based education research. Methods This study was conducted from August 2024 to October 2024. This study analyzed previous studies to set analysis categories and collected 60 domestic academic journals as analysis target papers. This study analyzed and described the research period, research type, research content, major field, related variables, class type, class period, AI tools, etc. Results First, the most research on university AI utilization was conducte

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Chavan Shruti, Pardeshi Janhavi, Pingle Shubhangi, Sonawane Raksha, and Vipin K Wani. "AI Driven Fashion Trend Prediction." international journal of engineering technology and management sciences 9, no. 2 (2025): 254–66. https://doi.org/10.46647/ijetms.2025.v09i02.033.

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Fashion manufacturers and brands are unaware of what customers desire because they still dependon old school manual methods. This challenge becomes more acute with Generation Z, who aredemanding one-of-a-kind and environmentally-friendly shopping experiences. Using machinelearning to improve the preciseness of the categorical results of fashion trends can be the solutionfor the problems discussed above. It predicts precisely, relying on past sale data, social mediatrends, and extra components to stay ahead of the businesses. It can process data in real-time,allowing it to continuously learn an

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Aalijah, Kanwal. "Utilizing Social Media Analytics to Detect Trends in Saudi Arabia’s Evolving Market." International Journal of Scientific Research and Management (IJSRM) 13, no. 02 (2025): 1936–43. https://doi.org/10.18535/ijsrm/v13i02.ec01.

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Saudi Arabia' faced a swift economic growth and societal transformation under Vision 2030. This offers a unique opportunity to track emerging trends in the region, which will ultimately pave the way for new business and investment possibilities. This paper explores how AI and social media analytics can identify and track trends across sectors such as construction, food and beverage, tourism, technology, and entertainment thereby helping the businesses make informed decisions. By leveraging a tailored AI-driven methodology, we analyzed millions of social media posts each month, classifying disc

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Yazdani, Ali, and Shoaleh Darbani. "The Impact of AI on Trends, Design, and Consumer Behavior." AI and Tech in Behavioral and Social Sciences 1, no. 4 (2023): 4–10. http://dx.doi.org/10.61838/kman.aitech.1.4.2.

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This study aims to explore the multifaceted impact of AI on trends, design innovations, and shifts in consumer behavior. It seeks to identify the main themes that characterize AI's influence across these domains, providing insights into how AI is reshaping consumer interactions, design practices, and market dynamics. Utilizing a qualitative research approach, the study conducted semi-structured interviews with 27 participants from various professional backgrounds, including digital design, AI research, trend analysis, consumer psychology, and product development. Thematic analysis was employed

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Jose Miguel, Penalva Tebar, та Ken Nah. "멀티모달 및 생성 AI를 통한 디자인 연구방법: 민족지학적 방법론을 데이터 기반 분석으로 강화하기". Korea Institute of Design Research Society 8, № 4 (2023): 27–38. http://dx.doi.org/10.46248/kidrs.2023.4.27.

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This research examines the application of Multimodal and Generative AI in analyzing interior design trends within the South Korean market. The objective is to enhance traditional ethnographic research methods with AI's quantitative capabilities, offering a more comprehensive understanding of design preferences. This methodology uses AI tools to systematically analyze and categorize design elements from a large dataset of interior design images sourced from a relevant online platform. This process involves extracting key visual trends and patterns using AI-driven semantic analysis and clusterin

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Oyelude, Adetoun A. "AI and libraries: trends and projections." Library Hi Tech News 38, no. 10 (2021): 1–4. http://dx.doi.org/10.1108/lhtn-10-2021-0079.

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Purpose This paper aims to focus on the trends and projection for future use of artificial intelligence (AI) in libraries. AI technologies is the latest among the technologies being used in libraries. The technology has systems that have natural language processing, machine learning and pattern recognition capabilities that make service provision easier for libraries. Design/methodology/approach Systematic literature review is done, exploring blogs and wikis, to collect information on the ways in which AI is used and can be futuristically used in libraries. Findings This paper found that uses

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Solodovnyk, Dmytro, Inna Havryliuk, Inna Sypchenko, Olena Ishchenko, and Oksana Kyrylenko. "Data journalism visualization in Ukraine and in Europe: a comparative analysis." Revista Amazonia Investiga 12, no. 64 (2023): 102–16. http://dx.doi.org/10.34069/ai/2023.64.04.10.

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The article aims to investigate the peculiarities of data visualization in Ukrainian and European data media, which will help outline trends and development tendencies in data journalism. The research results will form a list of promising methods and forms of data visualization in journalistic practice. The research used the method of content analysis of journalistic materials and comparative analysis of Ukrainian and European data media. The use of such a methodological toolkit is due to the visual component of the analyzed objects and the need to fill a gap in data journalism research as a c

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Nicknam, Reza, Seyyed Rouhollah Hadj Zargarbashi, and Abtin Safavipour. "AI Development in Germany After the Publication of German Nation AI Strategy, Problems and Solutions." Journal of Humanities and Education Development 6, no. 5 (2024): 68–81. http://dx.doi.org/10.22161/jhed.6.5.11.

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Germany’s effort to develop AI and make progress in this field became coherent and systematic after the publication of the German National AI Strategy in 2018. Germany’s effort in AI development has four trends, namely the integration of AI in society and economy, building and maintaining the AI ecosystem, strengthening the country in terms of infrastructure and data, and finally research and development, which constitutes the essence and backbone of all the other trends. To drive its efforts forward in each trend, Germany should overcome the respective challenges. Furthermore, due to the nove

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Huang, Huang. "Exploring the Future of AI: An In-Depth Analysis of the 2024 AI Index Report." Transactions on Computer Science and Intelligent Systems Research 7 (November 25, 2024): 564–68. https://doi.org/10.62051/acx9xa49.

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Artificial Intelligence (AI) has rapidly developed across multiple fields, for example, in the medical field, various diseases are prevented, diagnosed, and classified. In the financial field, the trend of some stocks is predicted. In the education field, teachers are assisted in teaching and grading homework. This paper provides a comprehensive analysis of the “2024 AI Index Report,” which offers a detailed account of the current state of AI, including technological advancements, public perceptions, geopolitical dynamics, and trends in responsible AI development. The paper aims to present a n

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Andrews, J. Christy. "THE FUTURE OF AI AND EMERGING TRENDS." International Scientific Journal of Engineering and Management 04, no. 03 (2025): 1–7. https://doi.org/10.55041/isjem02439.

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Artificial Intelligence (AI) is transforming industries and reshaping human-machine interactions at an unprecedented pace. From healthcare and finance to autonomous systems and creative fields, AI is driving innovation across multiple domains. This paper explores key emerging trends that will define the future of AI, including explainable AI (XAI) for greater transparency, the integration of quantum computing processing power, advancements in autonomous systems such as self-driving vehicles and drones, and the role of AI in content generation and creativity. Additionally, AI is playing a cruci

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Gau, Li-Shiue, Hsiu-Tan Chu, Duong Thuy Pham, and Chung-Hsing Huang. "Innovative Teaching of AI-Based Text Mining and ChatGPT Applications for Trend Recognition in Tourism and Hospitality." Tourism and Hospitality 5, no. 4 (2024): 1274–91. http://dx.doi.org/10.3390/tourhosp5040071.

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This research applies a model-based teaching approach aimed at scrutinizing trends in the leisure, tourism, hospitality, recreation, and sport (LTHRS) field by integrating artificial intelligence (AI) along with ChatGPT, project-based learning (PBL), systems thinking, and industrial analysis tools to foster trend recognition skills. The study employs a quasi-experimental design to compare the efficacy of two instructional approaches (exploratory vs. confirmatory) concerning AI literacy and learning outcomes. Notably, the exploratory group exhibits marked improvements in AI knowledge, while the

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Dr. Ravi Khatwal and Suman Shaktawat. "AI On Cyber Security for Future Trends." international journal of engineering technology and management sciences 9, no. 4 (2025): 77–81. https://doi.org/10.46647/ijetms.2025.v09i04.009.

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The infusion of Artificial Intelligence (AI) in cybersecurity has profoundly transformed the discipline, enhancing the detection, response, and mitigation of cyber attacks. This article explores the present and future state of AI-based cybersecurity, with a specific emphasis on the challenges and opportunities that come with these developments. Legacy security solutions are found to be insufficient against more advanced cyber attacks, motivating the integration of AI technologies with predictive modelling, anomaly detection, and automated reaction capabilities. Although generative AI provides

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George, Pavlidis. "AI trends in digital humanities research." Trends in Computer Science and Information Technology 7, no. 2 (2022): 026–34. http://dx.doi.org/10.17352/tcsit.000048.

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Recent advances in specialised equipment and computational methods had a significant impact in the Humanities and, particularly, cultural heritage and archaeology research. Nowadays, digital technology applications contribute in a daily basis to the recording, preservation, research and dissemination of cultural heritage. Digitisation is the defining practice that bridges science and technology with the Humanities, either in the tangible or in the intangible forms. The digital replicas support a wide range of studies and the opening of new horizons in the Humanities research. Furthermore, adva

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Djuric, Dragan, Vladan Devedzic, and Dragan Gasevic. "Adopting Software Engineering Trends in AI." IEEE Intelligent Systems 22, no. 1 (2007): 59–66. http://dx.doi.org/10.1109/mis.2007.2.

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LEE Kang Yoon, Jin-soo Kim, and Hye-rim Kim. "AI Platform Solution Service and Trends." Korea Journal of BigData 2, no. 2 (2017): 9–16. http://dx.doi.org/10.36498/kbigdt.2017.2.2.9.

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Pavlidis, George. "AI trends in digital humanities research." Trends in Computer Science and Technology 7, no. 2 (2022): 26–34. https://doi.org/10.17352/tcsit.000048.

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Recent advances in specialised equipment and computational methods had a significant impact in the Humanities and, particularly, cultural heritage and archaeology research. Nowadays, digital technology applications contribute in a daily basis to the recording, preservation, research and dissemination of cultural heritage. Digitisation is the defining practice that bridges science and technology with the Humanities, either in the tangible or in the intangible forms. The digital replicas support a wide range of studies and the opening of new horizons in the Humanities research. Furthermore, adva

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Kim, Hyun Ji, Se Young Yoon, and Hwa Jeong Seo. "Research Trends in Domestic and International AI chips." Korean Institute of Smart Media 13, no. 3 (2024): 36–44. http://dx.doi.org/10.30693/smj.2024.13.3.36.

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Recently, large-scale artificial intelligence (AI) such as ChatGPT have been developed, and as AI is used across various industrial fields, attention is focused on AI chips (semiconductors). AI chips refer to chips designed for calculations for AI algorithms, and many companies at domestic and abroad, such as NVIDIA, Tesla, and ETRI, are developing AI chips. In this paper, we survey research trends on nine types of AI chips. Currently, many attempts have been made to improve the computational performance of most AI chips, and semiconductors for specific purposes are also being designed. In ord

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Bai, Xinzhu, Wei Jiang, and Jiahao Xu. "Development Trends in AI-Based Financial Risk Monitoring Technologies." Journal of Economic Theory and Business Management 1, no. 2 (2024): 58–63. https://doi.org/10.5281/zenodo.10965494.

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In recent years, artificial intelligence (AI) technology has rapidly evolved and deeply integrated with the financial industry. It has been widely used in various scenarios such as intelligent customer service, credit scoring, robo-advisors, and risk management. Central banks and other financial regulatory authorities are also exploring the utilization of AI to strengthen economic monitoring, analysis, and forecasting. AI contributes to improving the efficiency of financial services, promoting inclusive finance, and enhancing regulatory effectiveness. However, it also introduces risks such as

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Wilson, Richard, and Olivia Bowles. "Artificial Intelligence and Trend Forecasting in the Fashion Industry: Ethical and Anticipated Ethical Issues." International Conference on AI Research 4, no. 1 (2024): 75–81. https://doi.org/10.34190/icair.4.1.3186.

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Trend forecasting within the fashion industry is aimed at predicting the of future popular styles, materials, colors, and all things related to the development of fashion. Trend forecasting is based on information collected about past, present, and projected future developments in the fashion world. AI, as it has been applied in other areas in society, is now being applied within the fashion industry. This analysis will focus on AI being applied to trend forecasting within the fashion industry. Using AI in trend forecasting brings a number of advantages for those in the fashion industry while

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Riliwan, Adekola Adebayo, Constance Obiuto Nwankwo, Kayode Olajiga Oladiran, and Clinton Festus-Ikhuoria Igberaese. "AI-enhanced manufacturing robotics: A review of applications and trends." World Journal of Advanced Research and Reviews 21, no. 3 (2024): 2060–72. https://doi.org/10.5281/zenodo.14173760.

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This review explores the transformative impact of artificial intelligence (AI) on manufacturing robotics, elucidating a comprehensive overview of applications and emerging trends within the realm of smart manufacturing. As industries increasingly embrace Industry 4.0 principles, the integration of AI into manufacturing robots has become pivotal for enhancing efficiency, flexibility, and adaptability. The synergy of AI and manufacturing robotics has resulted in a plethora of applications that redefine traditional manufacturing processes. Machine learning algorithms empower robots with predictiv

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Morales, Victor E., Jose Sanchez, Jonathan Escalera, Vivek Sharma, and Brooke E. Wheeler. "Artificial intelligence & aviation: Content analysis of research publications from 2013-2023." Journal of Management and Engineering Integration 17, no. 2 (2024): 100–106. http://dx.doi.org/10.62704/10057/28469.

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The aviation industry has explored the integration of artificial intelligence (AI) into its unique aspects but has not yet actively incorporated AI into the cockpit. This study aimed to identify trends in peer reviewed research publications that discuss AI and aviation from 2013 to 2023. Content analysis was used to identify the trend in annual AI and aviation publication counts over time. The study collected publication data from the Advanced Technologies & Aerospace Database (ATAD) using specific search terms, “AI and aviation,” “artificial intelligence and aviation,” “AI and aircraft,”

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Jaglan, Ritu. "EMERGING TRENDS IN AI: A CROSSROADS FOR HUMANITY." international journal of advanced research in computer science 16, no. 03 (2025): 152–55. https://doi.org/10.26483/ijarcs.v16i3.7287.

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The world of AI is changing exponentially. This paper explores the top AI trends shaping the future of technology, business, and everyday life. From ground breaking innovations to unexpected applications, these trends are redefining what AI can achieve; discover how advancements in generative AI, autonomous systems, and ethical AI frameworks are transforming industries worldwide. The paper also delves into the rise of hyper-personalization, AI-powered creativity, and the integration of AI into healthcare, education, and finance. The paper is trying to uncover the opportunities that these trend

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Xu, Yang, Yingchia Liu, Haosen Xu, and Hao Tan. "AI-Driven UX/UI Design: Empirical Research and Applications in FinTech." International Journal of Innovative Research in Computer Science and Technology 12, no. 4 (2024): 99–109. http://dx.doi.org/10.55524/ijircst.2024.12.4.16.

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This study explores the transformative impact of AI-driven UX/UI design in the FinTech sector, examining current practices, user preferences, and emerging trends. Through a mixed-methods approach, including surveys, interviews, and case studies, the research reveals significant adoption of AI technologies in FinTech UX/UI design, with 78% of surveyed companies implementing such solutions. Personalization emerges as a dominant trend, with 76% of FinTech apps utilizing AI for tailored user interfaces. The study demonstrates a strong correlation between AI-enhanced features and improved user enga

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Ryazanova, Svetlana V., Vladimir P. Mazaev, and Artem A. Komkov. "New trends for artificial intelligence development in medicine." CardioSomatics 12, no. 4 (2021): 227–33. http://dx.doi.org/10.17816/22217185.2021.4.201264.

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The article discusses the modern aspects of the use of artificial intelligence (AI) in medicine, the use of AI technologies in Russia and abroad. The article describes the limitations of the use of AI in various fields of medicine, discusses possible solutions, and develops electronic devices for remote and independent monitoring. The problems of information security and ethical issues of AI application are presented with the arguments of experts and expert organizations in AI issues, as well as the prospects for development and possible consequences of AI implementation. The possibilities of

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Ali, Dr Atif. "Artificial Intelligence Potential Trends in Military." Foundation University Journal of Engineering and Applied Sciences <br><i style="color:yellow;">(HEC Recognized Y Category , ISSN 2706-7351)</i> 2, no. 1 (2021): 20–30. http://dx.doi.org/10.33897/fujeas.v2i1.380.

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Artificial intelligence (AI) is trending in the military and safety-critical application sectors. Currently, the private sector is helping the government sector to implement new advanced techniques to bring a revolution for different government and public sector management. It also helps to provide sustainable accountability in the accounting field; at present, AI is bringing a revolution in concept building. It is bringing potential revolutions by using novel approaches in such directions. This paper is a novel approach in the same direction; our research aim of this paper is to emphasize the

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Achimugu, Dolapo, Chinaza Ukatu, and Arinze E. Anaege. "Sustainability in Financial Reporting: The Role of AI-Powered Predictive Analytics." American Journal of Multidisciplinary Research and Innovation 4, no. 3 (2025): 53–70. https://doi.org/10.54536/ajmri.v4i3.4551.

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Artificial Intelligence (AI) is revolutionizing sustainability reporting with greater accuracy, efficiency, and transparency in Environmental, Social, and Governance (ESG) disclosures. This paper uses a systematic literature review in line with PRISMA guidelines to explore how AI-based predictive analytics is improving sustainability-related financial reporting. Three research questions underpin this paper: (1) how AI-based predictive analytics is improving ESG reporting, (2) challenges and benefits in adopting AI, and (3) future trends in AI-based sustainability reporting. Research indicates

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Gumennykova, Tamara, Petro Ilchenko, Olena Bazyl, Alla Ilchenko, and Olena Vydrych. "Educational trends 2022: essence and innovation potential." Revista Amazonia Investiga 11, no. 55 (2022): 226–33. http://dx.doi.org/10.34069/ai/2022.55.07.24.

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The paper aims to analyze the educational trends of the year 2022 and determine whether they are relevant in the future, whether they are a response to the challenges of the present. Also, attention is paid to the method of SWOT-analysis, with the help of which the strengths and vulnerabilities of distance learning are identified. The results analyze the future of distance education, in particular, special attention is paid to the experience of implementing hybrid education as a likely promising direction of further learning. Another aspect is the introduction of STEM education, media educatio

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Gu, Jiasheng, Chongyang Gao, and Lili Wang. "The Evolution of Artificial Intelligence in Biomedicine: Bibliometric Analysis." JMIR AI 2 (December 19, 2023): e45770. http://dx.doi.org/10.2196/45770.

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Background The utilization of artificial intelligence (AI) technologies in the biomedical field has attracted increasing attention in recent decades. Studying how past AI technologies have found their way into medicine over time can help to predict which current (and future) AI technologies have the potential to be utilized in medicine in the coming years, thereby providing a helpful reference for future research directions. Objective The aim of this study was to predict the future trend of AI technologies used in different biomedical domains based on past trends of related technologies and bi

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Sakharuk, Iryna, Svitlana Batychenko, Olena Derii, Anton Kryzhevskyi, Alina Magomedova, and Oleksandra Pohorielova. "Main trends in development of migration policy in Ukraine." Revista Amazonia Investiga 9, no. 26 (2020): 372–82. http://dx.doi.org/10.34069/ai/2020.26.02.43.

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This Article is devoted to the interdisciplinary research of Migration Policy and determination of Main Trends of its realization in Ukraine at the current stage. The Basic Steps of Migration Policy-making have been defined. We have also identified that the efficiency of migration policy is determined by degree of consideration of the factors of political, economic, social and demographic origin, as well as by the trends of international labor migration. On the basis of the study results, the main trends of implementation of Migration Policy in Ukraine have been identified: lack of system of c

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Tyagi, Mukund, Dr Nikhil Sirohi, Dr Pallavi Tyagi, and Kajal Yadav. "Future Trends of B2C Marketing with Artificial Intelligence." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51309.

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Artificial Intelligence (AI) is fundamentally transforming business-to-consumer (B2C) marketing by enhancing the ability of brands to understand, engage, and retain customers. This paper investigates the emerging trends shaping the future of B2C marketing through the integration of advanced AI technologies. Key developments such as generative AI, conversational interfaces, emotion AI, and ethical personalization are enabling hyper-personalized content, real-time customer interactions, and deeper emotional engagement. These innovations are not only optimizing marketing strategies but also resha

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Kauffman, Marcos Eduardo, and Marcelo Negri Soares. "AI in legal services: new trends in AI-enabled legal services." Service Oriented Computing and Applications 14, no. 4 (2020): 223–26. http://dx.doi.org/10.1007/s11761-020-00305-x.

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Ms., R. Suma, and R. Moses Daniel Dr. "Trends Influencing Ai's Development During The Next Ten Years." Empirical Economics Letters 24, Special Issue 3 (2025): 204–10. https://doi.org/10.5281/zenodo.15230087.

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As we look ahead to the next decade, the development of artificial intelligence (AI) is poised to be shaped by several key trends. The study explores these trends and their potential impact on the future of AI. Advancements in deep learning and neural networks will continue to drive breakthroughs in AI capabilities, enabling more sophisticated and human-like interactions. The integration of AI with the Internet of Things (IoT) will facilitate the creation of smart environments, enhancing automation and efficiency across various sectors. The ethical and regulatory frameworks will play a crucial

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Sathya, P., N. Nirmala, and T. Priyadharshini. "The Future of AI: Emerging Trends and Innovations." ComFin Research 13, S1-i2 (2025): 207–12. https://doi.org/10.34293/commerce.v13is1-i2.8767.

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AI has the potential to completely transform a number of industries, including healthcare, banking, manufacturing, and education. Driven by developments in robotics, computer vision, deep learning, and natural language processing (NLP), artificial intelligence (AI) has enormous promise when combined with cutting-edge technologies like 5G, blockchain, and quantum computing. The significance of guaranteeing openness, equity, and responsibility in AI systems is highlighted by the emergence of explainable AI (XAI) and the growing emphasis on ethical AI frameworks. With a focus on data privacy, hum

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G. Popkova, Elena, and Miladin Stefanovic. "TRENDS OF THE AI ECONOMY IN RUSSIA." Journal of Trends and Challenges in Artificial Intelligence 1, no. 1 (2024): 1–14. http://dx.doi.org/10.61552/jai.2024.01.001.

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This paper is devoted to determining the trends of the AI economy in Russia. The method of trend analysis was used to find the dynamics of change in the values of the indicators of development of the AI economy in Russia. As a result, we revealed the specific features of its Russian model. The first feature is that in Russia, the key participant of the AI economy is the government, and the role of business, despite its being a secondary player, constantly grows. The second feature is that Russia successfully strengthens technological sovereignty in the sphere of the AI economy. The main conclu

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Alexandrov, Boris. "Trends of aquatic alien species invasions in Ukraine." Aquatic Invasions 2, no. 3 (2007): 215–42. http://dx.doi.org/10.3391/ai.2007.2.3.8.

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Deepak, Moolpani. "Artificial Intelligence and Data Science: Emerging Trends and Future Perspectives." International Journal of Advance and Applied Research S6, no. 22 (2025): 1170–72. https://doi.org/10.5281/zenodo.15542868.

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<em>Artificial Intelligence (AI) and Data Science have become pivotal in shaping the future of technology. These fields drive innovation, transforming industries through advanced analytics, automation, and intelligent decision-making. This paper explores emerging trends in AI and Data Science, their applications, challenges, and future perspectives. It discusses the impact of deep learning, natural language processing, generative AI, explainable AI, quantum AI, and ethical considerations, providing a comprehensive overview of the evolving landscape.</em> <em>Looking toward the future, AI and D

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Riliwan Adekola Adebayo, Nwankwo Constance Obiuto, Oladiran Kayode Olajiga, and Igberaese Clinton Festus-Ikhuoria. "AI-enhanced manufacturing robotics: A review of applications and trends." World Journal of Advanced Research and Reviews 21, no. 3 (2023): 2060–72. http://dx.doi.org/10.30574/wjarr.2024.21.3.0924.

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This review explores the transformative impact of artificial intelligence (AI) on manufacturing robotics, elucidating a comprehensive overview of applications and emerging trends within the realm of smart manufacturing. As industries increasingly embrace Industry 4.0 principles, the integration of AI into manufacturing robots has become pivotal for enhancing efficiency, flexibility, and adaptability. The synergy of AI and manufacturing robotics has resulted in a plethora of applications that redefine traditional manufacturing processes. Machine learning algorithms empower robots with predictiv

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Alok, Reddy Jakkula. "Future Trends in AI and E-commerce." Journal of Scientific and Engineering Research 8, no. 8 (2021): 190–93. https://doi.org/10.5281/zenodo.11490272.

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The integration of artificial intelligence (AI) into e-commerce is set to transform how retail operates and how customers experience shopping online. This paper aims to predict the significant changes and advancements that AI will bring to the e-commerce sector. We will explore how AI is expected to improve personalization, increase operational efficiency, and enhance decision-making processes within e-commerce businesses. The study will examine both current technological advancements and anticipated future developments, providing a comprehensive overview of how AI is expected to reshape the r

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Joshi, Satyadhar. "Agentic Generative AI and the Future U.S. Workforce: Advancing Innovation and National Competitiveness." International Journal of Research and Review 12, no. 2 (2025): 102–13. https://doi.org/10.52403/ijrr.20250212.

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This paper presents a systematic review of generative AI applications in workforce development and education. We categorize the literature into key themes and synthesize findings to highlight trends, challenges, and future directions. Expected outcomes include enhanced training efficiency, broader accessibility to high-quality learning resources, and reduced costs compared to traditional methods. The AI-driven approach ensures adaptability across industries, providing a scalable solution for continuous workforce upskilling. However, challenges such as data privacy, algorithmic bias, and user a

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Gîrbacia, Florin. "An Analysis of Research Trends for Using Artificial Intelligence in Cultural Heritage." Electronics 13, no. 18 (2024): 3738. http://dx.doi.org/10.3390/electronics13183738.

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Artificial intelligence (AI) techniques have been increasingly applied in assisting various cultural heritage (CH)-related tasks. The aim of this study is to examine the research trends and current applications of AI in this vast domain. After obtaining a dataset from the Web of Science and Scopus databases, a scientometric analysis of research publications from 2019 to 2023 related to the use of AI in CH was conducted. The trending topics based on the author’s keywords were identified by using the ScientoPy v2.1.3 software. Through this approach, five main topics were identified: classificati

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Nan Wang, Nan Wang, Suqi Li Nan Wang, Chenhui Wang Suqi Li, and Li Zhao Chenhui Wang. "Current Status and Emerging Trends of Generative Artificial Intelligence Technology: A Bibliometric Analysis." 網際網路技術學刊 25, no. 3 (2024): 477–85. http://dx.doi.org/10.53106/160792642024052503013.

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<>With the widespread application of ChatGPT (Chat Generative Pre-trained Transformer), its superordinate concept, generative artificial intelligence (Gen AI), has received increasing attention from researchers. The current study attempted to explore the current status and emerging trends of Gen AI technology research by visualizing the relevant published articles using the Biblioshiny tool. A total of 1,902 academic articles in the Web of Science (WOS) database published between 2014-2022 were analyzed. Annual publications, most productive journals and countries, co-authors, co-occurrin

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Dalal, Ruhi Dharmendra. "AI And Energy Demand: Trends, Impacts, And Solutions." Journal of Software Engineering and Simulation 11, no. 7 (2025): 01–08. https://doi.org/10.35629/3795-11070108.

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Artificial intelligence (AI) is transforming industries by automating processes, enabling real-time decisionmaking, and optimizing system performance. However, this rapid expansion—especially in generative AI models like GPT-4—has resulted in a sharp rise in global energy demand. AI systems rely on high-performance computing infrastructure that consumes significant electricity and water resources, contributing to greenhouse gas emissions and environmental stress. For example, training a single large AI model can use as much electricity as 120 U.S. homes consume in a year and emit hundreds of m

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Li, Chunlin. "Future Trends and Technological Innovations of Private AI Deployment." Science, Technology and Social Development Proceedings Series 1 (September 28, 2024): 1–14. http://dx.doi.org/10.70088/6fmynz86.

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As data protection laws like GDPR tighten, companies must ensure their AI systems comply with regulations, leading to widespread use of encryption, federated learning, and differential privacy to protect data. Privatized AI deployment will transform enterprise operations by integrating AI with core business processes, automating and enhancing efficiency and decision-making. For instance, manufacturing firms can use privatized AI for intelligent monitoring and predictive maintenance, reducing costs and improving quality. The market landscape will shift as companies reevaluate technology and ser

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Chittaro, Luca, and Angelo Montanari. "Trends in temporal representation and reasoning." Knowledge Engineering Review 11, no. 3 (1996): 281–88. http://dx.doi.org/10.1017/s026988890000792x.

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Time is one of the most relevant topics in AI. It plays a major role in several of AI research areas, ranging from logical foundations to applications of knowledge-based systems. Despite the ubiquity of time in AI, researchers tend to specialise and focus on time in particular contexts or applications, overlooking meaningful connections between different areas. In an attempt to promote crossfertilisation and reduce isolation, the Temporal Representation and Reasoning (TIME) workshop series was started in 1994. The third edition of the workshop was held on May 19–20 1996 in Key West, FL, with S

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Shabir, Achmad, Herwin Herwin, Asriadi Asriadi, Riana Nurhayati, Lantip Diat Prasojo, and Shakila Che Dahalan. "Integration of Artificial Intelligence in Virtual Reality-Based Learning." Data and Metadata 4 (March 19, 2025): 859. https://doi.org/10.56294/dm2025859.

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The integration of Artificial Intelligence (AI) and Virtual Reality (VR) in education presents a promising opportunity to create immersive and adaptive learning environments, but research on the integration of both is very rare for the case of elementary school education. Most studies only focus on the standalone study of one of the technologies. The research focuses on analyzing the impact and relationship between the integration of AI in VR learning environments over time, hence it will employ longitudinal data collection and time series analysis to understand trends and patterns. The resear

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