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Articles de revues sur le sujet « AI Capacity Building »

Auteur : Grafiati

Publié le 7 juin 2025

Mis à jour le 2 août 2025

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1

Ramingwong, Sakgasem, Apichat Sopadang, Tanyanuparb Anantana, Runchana Sinthavalai, and Salinee Santiteerakul. "Industrial research and development capacity building." Revista Amazonia Investiga 13, no. 81 (2024): 9–23. http://dx.doi.org/10.34069/ai/2024.81.09.1.

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Thailand faces significant challenges in aligning academic research with industrial needs and fostering robust R&D capabilities within businesses. The Industrial Research and Development Capacity Building (IRDCap) initiative was implemented to address these issues and enhance Thailand's innovation ecosystem. The program employs a dual approach: Train-the-Trainer (TTT) to develop academic expertise, and IRDCap Consulting to provide tailored support to businesses. It utilizes a comprehensive framework for developing R&D blueprints and roadmaps, supported by a central digital platform for

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Jamil, Khalid, Wen Zhang, Aliya Anwar, and Sohaib Mustafa. "Exploring the Influence of AI Adoption and Technological Readiness on Sustainable Performance in Pakistani Export Sector Manufacturing Small and Medium-Sized Enterprises." Sustainability 17, no. 8 (2025): 3599. https://doi.org/10.3390/su17083599.

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This study examines the impact of technological integration on sustainable performance in Pakistani manufacturing SMEs from the export sector, focusing on the mediating role of employee capacity building and the moderating role of organizational learning, drawing on dynamic capabilities theory. Data were collected from manufacturing SMEs in Pakistan via a structured questionnaire, and structural equation modeling (SEM) was employed using Smart-PLS (4.1) for analysis. The results reveal that both AI adoption and technological readiness significantly enhance employee capacity building, which, in

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Pedersen, Maja, Suzanne (Christopher) Held, and Blakely Brown. "Building Capacity to Increase Health Promotion Funding to American Indian Communities." Health Promotion Practice 17, no. 6 (2016): 907–14. http://dx.doi.org/10.1177/1524839915622195.

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Foundations and government agencies have historically played a critical role in supporting community-based health promotion programs. Increased access to health promotion funding may help address significant health issues existing within American Indian (AI) communities, such as childhood obesity, type 2 diabetes, and cardiovascular disease. Understanding the capacity of AI communities to successfully apply for and receive funding may serve to increase resources for health promotion efforts within AI communities in Montana. This exploratory qualitative study completed 17 semistructured intervi

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Gryshchenko, Iryna, Yurii Bondar, Svitlana Serohina, Irina Bodrova, and Olha Stohova. "Building the capacity of territorial communities by revealing their latent potential." Revista Amazonia Investiga 11, no. 53 (2022): 45–58. http://dx.doi.org/10.34069/ai/2022.53.05.5.

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Decentralization is a common component of public finance development and reform strategies through efficiency, better governance and accountability. It has become particularly important for the local governments to recognize and test policies and practices that promote building the capacity of local communities by revealing their latent potential. The aim of the article was to identify and describe the current state of the decentralization process in Ukraine and in the EU, the problems and achievements of local communities. Observation and comparison were the leading methodological tools. The

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Huang, Huakun, Dingrong Dai, Longtao Guo, Sihui Xue, and Huijun Wu. "AI and Big Data-Empowered Low-Carbon Buildings: Challenges and Prospects." Sustainability 15, no. 16 (2023): 12332. http://dx.doi.org/10.3390/su151612332.

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Reducing carbon emissions from buildings is crucial to achieving global carbon neutrality targets. However, the building sector faces various challenges, such as low accuracy in forecasting, lacking effective methods of measurements and accounting in terms of energy consumption and emission reduction. Fortunately, relevant studies demonstrate that artificial intelligence (AI) and big data technologies could significantly increase the accuracy of building energy consumption prediction. The results can be used for building operation management to achieve emission reduction goals. For this, in th

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Alemipasand, Somayeh, and Elham Farahani. "Capacity Building for the Implementation of Artificial Intelligence in Public Organizations." Journal of Technology in Entrepreneurship and Strategic Management 3, no. 5 (2024): 15–36. https://doi.org/10.61838/kman.jtesm.3.5.2.

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In recent years, artificial intelligence (AI) has emerged as a remarkable phenomenon, creating a massive transformation globally and becoming a necessary condition for the development and progress of both private and public organizations. The successful implementation of any project requires capacity building, which involves identifying needs, challenges, capabilities, and strengthening systems along the path to development. Accordingly, the aim of this research is to identify the necessary capacities for the implementation of AI in public organizations and to propose a comprehensive model for

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Altinay, Zehra, Fahriye Altinay, Ramesh Chander Sharma, et al. "Capacity Building for Student Teachers in Learning, Teaching Artificial Intelligence for Quality of Education." Societies 14, no. 8 (2024): 148. http://dx.doi.org/10.3390/soc14080148.

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The future of education relies on the integration of information technologies, emphasizing the importance of equity and inclusiveness for quality education. Teacher education programs are essential for fostering qualified educators for the future. Integrating AI in education is crucial to ensure inclusivity and comprehensive services for all. This study aims to evaluate student teachers’ perceptions of using AI in learning and teaching, and to provide suggestions for enhancing sustainable education through information technologies. A qualitative research design was adopted to gather perception

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Johnson, Mark William, Martie Van Tongeren, and Hua (Kim) Wei. "O-040 TOWARDS AN AI-INFORMED CAPACITY-BUILDING FRAMEWORK FOR OCCUPATIONAL HEALTH." Occupational Medicine 74, Supplement_1 (2024): 0. http://dx.doi.org/10.1093/occmed/kqae023.0517.

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Abstract The speed of development and variety of potential applications of Artificial Intelligence (AI) technology represents significant intellectual and practical challenges to practitioners and researchers in the field of health and safety at work. While these challenges are likely to dominate research agendas in the coming years, knowledge and expertise about the technology among practitioners in the field of occupational health is currently limited. The challenge is to raise capacity within the occupational health sector so as to establish a coherent and defensible approach to judgment an

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Soomro, Manzoor Hussain, and Mirza Abdul Aleem Baig. "AI for Sustainable Development in the Belt and Road Countries - Need for Capacity Building." Journal of Sustainable Development 17, no. 5 (2024): 43. http://dx.doi.org/10.5539/jsd.v17n5p43.

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All United Nations member countries are striving to achieve the Sustainable Development Goals (SDGs), with information and communication technologies (ICTs) playing a crucial role in accelerating the progress. However, there is a significant disparity in technological capacities between the least developed, developing, and developed nations. Leading countries maintain dominance in these technologies, creating a digital divide that redefines richness and poverty. The Belt and Road Initiative (BRI), launched by China in 2013, offers a beacon of hope for developing nations. Over the past decade,

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IRORITERAYE-ADJEKPOVU, Janice Imizuokena, and Emmanuel Ikechuku Abamba. "The Exploring AI capacity building programs in Nigerian higher education institutions: A study of curriculum design, faculty competence, and student engagement." GPH-International Journal of Educational Research 8, no. 4 (2025): 35–49. https://doi.org/10.5281/zenodo.15356893.

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Artificial Intelligence (AI) is transforming education globally, necessitating the integration of AI capacity-building programs in higher education institutions. This study explored the state of AI capacity building programs in Nigerian higher education institutions, focusing on curriculum design, faculty competence, and student engagement. A descriptive survey research design was adopted, and data were collected using a structured four-point Likert scale questionnaire. The population of the study comprised 79,668 staff from federal and state universities in Nigeria. the sample size for the st

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Kwaku Ofori. "Leveraging technology to improve capacity-building initiatives in microfinance institutions." International Journal of Science and Research Archive 6, no. 2 (2022): 320–24. http://dx.doi.org/10.30574/ijsra.2022.6.2.0086.

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Capacity building is crucial for the long-term sustainability and success of microfinance institutions (MFIs), particularly in developing economies where financial inclusion plays a vital role. This paper explores how leveraging modern technologies, such as digital platforms, mobile applications, artificial intelligence (AI), and big data, can enhance the capacity-building initiatives of MFIs. These technologies enable better training, operational efficiency, and client outreach, ultimately leading to improved performance in financial inclusion efforts

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Mensah, George Benneh, Maad M. Mijwil, and Mostafa Abotaleb. "Assessing Ghana's Cybersecurity Act 2020: AI Training and Medical Negligence Cases." Journal of Integrated Engineering and Applied Sciences 3, no. 1 (2025): 175–82. https://doi.org/10.5281/zenodo.14964892.

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This study delves into how Ghana’s Cybersecurity Act addresses training provisions and support for investigating cases of AI negligence, drawing from sections of the Act’s legal cases and academic literature. A legal assessment of Act 1038 concerning capacity building, protection of infrastructure liability gaps considering emerging AI threats and disputes related to negligence based on documented cases was carried out. The analysis reveals that Act 1038 does not explicitly mention risks associated with AI systems in capacity building or designating infrastructure. It suggests the

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Z. Allam, Sammar. "ARTIFICIAL INTELLIGENCEINTERVENTION TO URBAN BUILDING RENEWABLE ENERGY MODELING INTERVENTION FOR ROBUST FLEXIBLE COMMUNITIES." International Journal of Advanced Research 9, no. 03 (2021): 314–21. http://dx.doi.org/10.21474/ijar01/12586.

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This research coveys a comparative analysis between Urban Building energy model (UBEM) generated by scholar, researchers, and professional in academia and industry while highlighting the reliable main components to manifest a successful and reliable UBEM technologies. Nevertheless, it consolidates distributed generation on building blocks rather than a whole district relying on renewable energy sources. It guides engineers through energy system model simulation on Openmodelica platform to feed green sustained communities. Moreover, energy use-pattern is mapped and analyzed by internet of thing

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Septeanny, Putrisia, Brigita Meylianti Sulungbudi, and Franciskus Antonius Alijoyo. "Charting the course: embracing challenges and anticipating future trends in building AI capacity for marketing excellence in emerging markets." AMAR (Andalas Management Review) 8, no. 2 (2024): 44–64. https://doi.org/10.25077/amar.8.2.44-64.2024.

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The marketing landscape is undergoing a profound transformation with the emergence of artificial intelligence as a game-changer in driving innovation and customer engagement. Businesses are strategically integrating AI-powered solutions into their marketing decision-making to gain a competitive edge. Marketers are increasingly recognizing the immense potential of AI in enhancing their ability to identify competitors, understand customer preferences, and uncover valuable insights. The application of AI in marketing spans intelligent content generation, predictive analytics, personalized custome

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Hardianto, Toto, Mustafa Mustafa, Yakub Suleman, Muh Nurul Aiman Mubarak, and Feby Triadi. "Digital Transformation in Public Administration: Challanges and Opportunities in the Age of AI and Big Data." Pinisi Business Administration Review 7, no. 1 (2025): 49. https://doi.org/10.26858/pbar.v7i1.71546.

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The rapid evolution of digital technologies is reshaping the landscape of public administration worldwide. This paper examines the integration of Artificial Intelligence (AI) and Big Data into public sector processes, analyzing their potential to enhance operational efficiency, transparency, and citizen engagement. Through a mixed-methods approach, combining literature review, surveys, and interviews with government officials and technology experts. Key issues include data security, digital inequality, and algorithmic bias. The paper concludes by recommending policy frameworks, capacity-buildi

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Sendak, Mark, Meg Young, Jee Young Kim, et al. "Building models, building capacity: A review of participatory machine learning for HIV prevention." PLOS Global Public Health 5, no. 6 (2025): e0003862. https://doi.org/10.1371/journal.pgph.0003862.

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A growing number of researchers and practitioners are embracing a “participatory turn” in machine learning (ML) to improve model development, prevent harm, and provide communities more influence over systems that impact them. In this paper, we explore the intersection of participatory practices in healthcare and the emerging focus on responsible AI with a focus on human immunodeficiency virus (HIV) care. We review the historical context of participation in HIV treatment and prevention, emphasizing how patient activism has shaped practices in this field. We then review participatory ML in HIV p

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Yusuf, S., M.A. Ibrahim, and M.A. Adepoju. "Leveraging on Artificial Intelligence for Effective Provision of Security Services in Nigerian Universities: Potential Benefits and Challenges." Zamfara International Journal of Education 4, no. 3 (2024): 215–27. https://doi.org/10.5281/zenodo.14259116.

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Security challenges in Nigerian universities have become a growing concern, with increasing incidents of theft, violence, and unauthorized access, endangering both students and staff. Traditional security systems, often limited by human capacity and outdated technology, are proving inadequate to meet the complex and evolving threats faced by these institutions. This study explores how the integration of Artificial Intelligence (AI) and Internet of Things (IoT) sensors can transform security services in Nigerian universities. AI systems, when combined with IoT sensors, offer enhanced capabiliti

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Wiranti, Dyah Ayu. "BUILDING ADMINISTRATIVE CAPACITY: TACKLING DOMESTIC VIOLENCE AMIDST THE COVID-19 PANDEMIC." Jurnal Politik Pemerintahan Dharma Praja 16, no. 2 (2023): 215–28. http://dx.doi.org/10.33701/jppdp.v16i2.3570.

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The implementation of Covid-19 mitigation policies has hindered the effective functioning of public services. During the Covid-19 pandemic, domestic violence cases remained hidden due to victims' limited access to reporting channels, despite the government's efforts in establishing P2TP2A and SEJIWA psychological services. The persistently high incidence of domestic violence prompted Farazmand (2009) to advocate for increasing the state's administrative capacity to confront unforeseen challenges. This article examines Indonesia's approach to addressing domestic violence during the pandemic thr

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Hieu, Hua Hong, and Le Thanh Thao. "Trust Dynamics of Vietnamese EFL Teachers towards AI-Driven Educational Tools." Journal of Management World 2024, no. 4 (2024): 254–63. https://doi.org/10.53935/jomw.v2024i4.372.

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With the proliferation of Artificial Intelligence (AI) in educational realms, understanding trust dynamics is paramount, especially within diverse cultural contexts. This qualitative study delved into the perspectives of nine Vietnamese EFL teachers from two higher educational institutions, aiming to uncover the challenges and considerations in building trust towards AI-driven educational tools. Utilizing semi-structured interviews, the research was anchored on two theoretical frameworks: the Technology Acceptance Model and the Sociocultural Theory. Four predominant themes surfaced: the trust

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Mădălina-Ioana, Ivanov, Ghercă Ana-Maria, and Gafencu Larisa-Nicoleta. "Artificial Intelligence and Sustainable Development: Reducing Food Waste, Building Resilient Organisations, and Enhancing Public Financial Administration." BRAIN. Broad Research in Artificial Intelligence and Neuroscience 16, no. 1 (2025): 243–60. https://doi.org/10.5281/zenodo.15043785.

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This paper explores the transformative impact of Artificial Intelligence (AI) across three critical areas: food waste reduction, organisational resilience, and public financial administration. By utilising AI technologies like machine learning, predictive analytics, and real-time monitoring, the study highlights how AI can address inefficiencies, enhance systemic resilience, and support global sustainability goals, including the United Nations SDGs. In food waste reduction, AI improves demand forecasting, inventory management, and supply chain optimisation, reducing surplus and spoilage. Examp

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Frimpong, Victor. "Artificial Intelligence Investment in Resource-Constrained African Economies: Financial, Strategic, and Ethical Trade-Offs with Broader Implications." World 6, no. 2 (2025): 70. https://doi.org/10.3390/world6020070.

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This paper argues that investing in artificial intelligence (AI) in developing economies involves significant trade-offs requiring ethical, financial, and geopolitical scrutiny. While AI is increasingly seen as a vehicle for technological leapfrogging, such ambitions often mask structural constraints, including weak infrastructure, limited institutional capacity, and external dependency. Using the economic theory of opportunity cost—extended through the political economy and digital governance perspectives—this study critically examines AI policy strategies in Ghana, Kenya, and Rwanda. A quali

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Zhang, Wei, and Dzintra Ilisko. "AI-driven innovation in educational management: A multi-case study of Chinese higher education institutions." Edelweiss Applied Science and Technology 9, no. 4 (2025): 2109–28. https://doi.org/10.55214/25768484.v9i4.6498.

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This study examines the implementation and impacts of AI-driven innovations in Chinese higher education management, focusing on how technological readiness and organizational learning capacity affect implementation outcomes. A multi-case analysis of 35 higher education institutions in the Yangtze River Delta region utilizes data from 847 survey responses from administrators, faculty, and students. Results reveal an asymmetry between technological readiness (β = 0.341, p < 0.01) and organizational learning capacity (β = 0.254, p < 0.01) on implementation success. Threshold effects were id

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POPESCU-ZORICA, Alexandra. "BUILDING INTERNAL INNOVATION CAPACITY IN LARGE ENTERPRISES: A STRATEGIC IMPERATIVE." Business Excellence and Management 15, no. 1 (2025): 85–96. https://doi.org/10.24818/beman/2025.15.1-06.

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This paper explores the necessity for large enterprises to develop robust internal innovation capabilities as a strategic imperative for sustaining long-term competitiveness. While 83% of global companies prioritize innovation, only 3% demonstrate high innovation readiness, highlighting a gap between ambition and execution. The study employs a literature review and case study analysis to examine the structural and cultural barriers that hinder corporate innovation, including risk aversion, hierarchical decision-making, and a focus on operational efficiency over exploration. The research furthe

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Boatemaa, Rebecca, Solomon Ossom Asare, Stephen Cosmos Akabadin, Victor Agyabeng, and Alfred Addy. "The role of AI in Enhancing Disease Surveillance and Outbreak Response in Developing Countries." Ghana Journal of Nursing and Midwifery 1, no. 4 (2024): 16–29. http://dx.doi.org/10.69600/gjnmid.2024.v01.i04.16-29.

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This paper examines the potential of AI in enhancing disease surveillance and outbreak response in developing countries. Through a comprehensive literature review, the study assesses the current state of AI applications, identifies challenges and opportunities, and proposes an implementation framework. Findings reveal that AI technologies offer significant advantages in speed, accuracy, and predictive capabilities for disease surveillance. However, challenges such as data quality issues, infrastructure limitations, and ethical concerns persist. The study proposes a framework emphasizing robust

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Yurt, Eyup, and Ismail Kasarci. "A Questionnaire of Artificial Intelligence Use Motives: A Contribution to Investigating the Connection between AI and Motivation." International Journal of Technology in Education 7, no. 2 (2024): 308–25. http://dx.doi.org/10.46328/ijte.725.

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This study introduces the Questionnaire of AI Use Motives (QAIUM), an instrument designed to measure motivation levels in individuals using artificial intelligence (AI) applications. Building on a theoretical framework that emphasizes motivation over dispositions and defines motivation as expectancy/value, the QAIUM aims to fill a research gap in understanding the motivational factors that govern AI application use. Previous studies have often overlooked this human aspect, focusing instead on technological facets while failing to provide a robust theoretical foundation for measuring motivation

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Otu, Offiong Duke. "Capacity Building of the Nigerian Armed Forces and Security Challenges." International Journal of Trend in Scientific Research and Development 4, no. 1 (2019): 402–8. https://doi.org/10.5281/zenodo.3605888.

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July 2019 marks the eleventh year since the Boko Haram insurgency in Nigeria gained international recognition. A series of riots which lasted between 25th July and 30th July 2009 and smeared four North eastern Nigerian states Bauchi, Kano, Yobe and Borno, sequel to the death of Mohammed Yusuf, metamorphosed into a gangrenous cancer eating deep into the social order and security of Nigeria. This conflict is believed to have claimed over one hundred thousand lives and led to the displacement of over 2.3 million people from their homes in the northern eastern region of Nigeria, and other nations

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Ivanov, Mădălina-Ioana, Ana-Maria Ghercă, and Larisa-Nicoleta Gafencu. "Artificial Intelligence and Sustainable Development: Reducing Food Waste, Building Resilient Organisations, and Enhancing Public Financial Administration." BRAIN. Broad Research in Artificial Intelligence and Neuroscience 16, no. 1 (2025): 243. https://doi.org/10.70594/brain/16.1/18.

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<span id="docs-internal-guid-b53b44f5-7fff-fc2a-362b-39927553c58d"><span>This paper explores the transformative impact of Artificial Intelligence (AI) across three critical areas: food waste reduction, organisational resilience, and public financial administration. By utilising AI technologies like machine learning, predictive analytics, and real-time monitoring, the study highlights how AI can address inefficiencies, enhance systemic resilience, and support global sustainability goals, including the United Nations SDGs. In food waste reduction, AI improves demand forecasting, inve

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Mwangi Chege, Stanley. "The Adoption of Generative AI in Kenya: A Critical Analysis of Opportunities, Challenges, and Strategic Imperatives." International Journal of Innovation and Economic Development 10, no. 2 (2024): 46–57. https://doi.org/10.18775/ijied.1849-7551-7020.2015.102.2003.

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Artificial intelligence (AI), especially generative AI, is progressively transforming industries on a global scale, creating new opportunities while introducing notable challenges for organizations and IT decision-makers. This research investigates the adoption of generative AI within Kenya, providing a detailed examination of its advantages, implementation barriers, and strategic actions needed for effective integration. By synthesizing recent research and industry data, this paper explains how generative AI can fuel innovation, increase productivity, and foster economic growth in Kenya. It a

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FAWEHINMI, Felix John, Folasade Bolanle SIYANBADE, and Felix Ayodele OMONIYI. "Leveraging Artificial Intelligence to Enhance Mathematics Learning: Bridging Skill Gaps and Fostering Economic Growth in Nigeria." International Journal of Research and Innovation in Applied Science X, no. IV (2025): 876–87. https://doi.org/10.51584/ijrias.2025.10040073.

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Artificial Intelligence (AI) has emerged as a transformative technology in mathematics education in Nigeria. Studies have shown that AI tools can improve student performance and learning outcomes, but implementation requires addressing teacher preparedness and curriculum integration. This research surveyed 520 respondents from secondary and tertiary institutions in Ondo, representing Nigeria's ethnic groups. The results show that AI integration enhances mathematics performance compared with traditional methods, effectively addressing individual learning needs. Success depends on digital infras

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Chernbumroong, Sainatee, Suchada Phunsathitwong, Pongsawat Premphet, Sakgasem Ramingwong, and Jutamat Jintana. "Development of a strategic roadmap for plasma technology in Thailand: The hub of talents initiative." Revista Amazonia Investiga 13, no. 84 (2024): 9–27. https://doi.org/10.34069/ai/2024.84.12.1.

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This paper presents the development process and results of a strategic roadmap for plasma technology in Thailand, as part of the Hub of Talents for Plasma Technology initiative. Through a comprehensive methodology including literature review, expert interviews, workshops, and stakeholder consultations, a 5-year roadmap was created to guide research, development, and application of plasma technology in the country. The roadmap identifies six priority areas: research and development in plasma science and technology, industrial applications, upskilling existing talent, capacity building for new t

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Gutierrez, Kurt Lenard T., and Paulene Miriel L. Viacrusis. "Bridging the Gap or Widening the Divide: A Call for Capacity-Building in Artificial Intelligence for Healthcare in the Philippines." Journal of Medicine, University of Santo Tomas 7, no. 2 (2023): 1325–34. http://dx.doi.org/10.35460/2546-1621.2023-0081.

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The emerging field of generative artificial intelligence (GAI) and some of its well-known technologies: ChatGPT, Google Bard and Claude, have gained substantial popularity due to their enormous potential in healthcare applications, as seen in medically fine-tuned models such as Med-PaLM and ChatDoctor. While these advancements are impressive, the dependence of AI development on data volume and quality raises questions about the generalizability of these models. Regions with lower medical research output risk bias and misrepresentation in AI-generated content, especially when used to assist cli

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Margetts, Helen. "Rethinking AI for Good Governance." Daedalus 151, no. 2 (2022): 360–71. http://dx.doi.org/10.1162/daed_a_01922.

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Abstract This essay examines what AI can dofor government, specifically through three generic tools at the heart of governance: detection, prediction, and data-driven decision-making. Public sector functions, such as resource allocation and the protection of rights, are more normatively loaded than those of firms, and AI poses greater ethical challenges than earlier generations of digital technology, threatening transparency, fairness, and accountability. The essay discusses how AI might be developed specifically for government, with a public digital ethos to protect these values. Three moves

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Margetts, Helen. "Rethinking AI for Good Governance." Daedalus 151, no. 2 (2022): 360–71. http://dx.doi.org/10.1162/daed_a_01922.

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Abstract This essay examines what AI can dofor government, specifically through three generic tools at the heart of governance: detection, prediction, and data-driven decision-making. Public sector functions, such as resource allocation and the protection of rights, are more normatively loaded than those of firms, and AI poses greater ethical challenges than earlier generations of digital technology, threatening transparency, fairness, and accountability. The essay discusses how AI might be developed specifically for government, with a public digital ethos to protect these values. Three moves

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Chen, Xiaoyu. "Level of Acceptance and Behavioral Intention on the Use of Artificial Intelligence in Internal Audit Procedure." International Journal of Global Economics and Management 7, no. 3 (2025): 287–92. https://doi.org/10.62051/ijgem.v7n3.32.

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The integration of Artificial Intelligence (AI) into internal auditing is reshaping conventional audit methodologies by enhancing precision, efficiency, and analytical capacity. Despite its growing relevance, the degree to which internal auditors accept and intend to adopt AI technologies remains insufficiently examined. This study investigated the level of acceptance and behavioral intention among accounting professionals toward AI adoption in auditing, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Utilizing a descriptive-correlational research design, da

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PIA WULANDARI, MAULINA, VAN BIMANTORO WACHID, SITI DAHLIA SITI DAHLIA, SAMANTHA BELLA PURI BAHESA, and KADEK GOPALA WISWA SAI WISWADARA ARISTA. "Digital Public Relations in Indonesia in the Age of AI and Big Data: Theoretical and Practical Insights from a Five-Dimensional Framework." Jurnal Komunikasi: Malaysian Journal of Communication 41, no. 2 (2025): 405–27. https://doi.org/10.17576/jkmjc-2025-4102-23.

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The rapid development of digital technology and artificial intelligence (AI) has significantly influenced public relations practices. This study examines how digital public relations (DPR) dimensions interact to shape DPR practices in Indonesia across public, private, and non-governmental sectors. The study aims to identify structural and practical gaps in digital PR implementation and propose a model to enhance strategic communication effectiveness. A descriptive qualitative approach was employed, using focus group discussions (FGDs) with communication professionals and digital media experts.

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Adel, Mohammed Ahmed Abou, Moustafa Mohamed Abouelnour, Mohammad Issa Alhourani, and Asmaa A. Awad. "Towards Intelligent Universities Enhanced with Artificial Intelligence (AI)." Journal of Infrastructure, Policy and Development 9, no. 1 (2025): 10412. https://doi.org/10.24294/jipd10412.

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This paper presents a comprehensive and integrated paradigm for intelligent universities using artificial intelligence (AI) to transform management systems and teaching, thus complementing sustainable development objectives. Through a systematic examination of top worldwide universities’ AI applications, this study reveals key achievements, obstacles, and strategies for successfully implementing AI-driven intelligent universities. Every case study focuses on a particular AI-driven project, including the adaptive learning systems at MIT, the AI teaching assistant Jill Watson at Georgia Tech, an

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Zhang, Jingwen, Yoo Jung Oh, Patrick Lange, Zhou Yu, and Yoshimi Fukuoka. "Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint." Journal of Medical Internet Research 22, no. 9 (2020): e22845. http://dx.doi.org/10.2196/22845.

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Background Chatbots empowered by artificial intelligence (AI) can increasingly engage in natural conversations and build relationships with users. Applying AI chatbots to lifestyle modification programs is one of the promising areas to develop cost-effective and feasible behavior interventions to promote physical activity and a healthy diet. Objective The purposes of this perspective paper are to present a brief literature review of chatbot use in promoting physical activity and a healthy diet, describe the AI chatbot behavior change model our research team developed based on extensive interdi

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Bansal, Saurabh, and Dr Neelesh Jain. "A Comprehensive Study Assessing the Transformative Role of Artificial Intelligence in India\'s Governance Policy Framework." International Journal for Research in Applied Science and Engineering Technology 11, no. 7 (2023): 1748–56. http://dx.doi.org/10.22214/ijraset.2023.54973.

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Abstract: Artificial Intelligence (AI) has gained significant prominence worldwide, and India is actively embracing its potential for transforming various sectors. This paper comprehensively studies the intersection between artificial intelligence and Indian government policies. It explores the opportunities, challenges, and implications of AI implementation in the Indian context, and discusses the evolving role of the Indian government in harnessing AI technologies. The paper addresses the challenges and risks associated with AI implementation in India, including ethical considerations, socio

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Brunetto, Yvonne, Tom Dick, Matthew Xerri, and Ashley Cully. "Building capacity in the healthcare sector: A strengths-based approach for increasing employees' well-being and organisational resilience." Journal of Management & Organization 26, no. 3 (2019): 309–23. http://dx.doi.org/10.1017/jmo.2019.53.

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AbstractThis study uses Appreciative Inquiry (AI) as a lens for informing the process for building on employees' existing wellbeing within one Australian organisation, using the ‘discovery, dreaming, designing, and achieving destiny’ process. Using POSH as a theoretical framework, we worked with a large Not-For-Profit healthcare organisation as part of the ‘discovery’ phase to identify elements of what was positive, flourishing, and life-giving in the practices of their employees. During the ‘dreaming’ process, employees' wellbeing was identified as a strength. During the ‘designing’ phase, a

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John Akwetey Boafo, Maud Avevor, and Noble Osei Poku Danzerl. "AI-powered credit risk assessment in development finance: Opportunities and ethical challenges in emerging markets." World Journal of Advanced Research and Reviews 26, no. 3 (2025): 068–74. https://doi.org/10.30574/wjarr.2025.26.3.2119.

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This discussion paper critically reviews the use of artificial intelligence (AI) in credit risk assessment in development finance institutions (DFIs) in emerging markets. The main goal is to assess the opportunities and ethical challenges of AI driven models for financial inclusion. Using secondary data synthesis, case studies and global policy frameworks, the paper examines how machine learning and alternative data sources can improve predictive accuracy, increase credit access and improve DFI operations. It also points out systemic risks such as algorithmic bias, data privacy violation, lack

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Kayusi, Fredrick, Srinivas Kasulla, S. J. Malik, et al. "Ensuring AI Algorithm Fairness in Healthcare Decision-Making." Africa Journal For Regulatory Affairs (AJFRA) 2024, no. 11 (2024): 77–90. https://doi.org/10.62839/AJFRA.v01.v01.77-90.

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<strong>Abstract:</strong> This paper provides a comprehensive analysis of artificial intelligence (AI) implementation in Ghana's healthcare system, synthesizing findings from recent Ghanaian studies. It examines legal and regulatory frameworks, ethical considerations, bias and fairness, transparency and accountability, interdisciplinary approaches, patient rights and data protection, healthcare access and equity, and implementation and oversight. The analysis reveals both significant opportunities for AI to improve healthcare delivery in Ghana and substantial challenges in ensuring its ethica

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Cordeiro-Costas, Moisés, Daniel Villanueva, Pablo Eguía-Oller, Miguel Martínez-Comesaña, and Sérgio Ramos. "Load Forecasting with Machine Learning and Deep Learning Methods." Applied Sciences 13, no. 13 (2023): 7933. http://dx.doi.org/10.3390/app13137933.

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Characterizing the electric energy curve can improve the energy efficiency of existing buildings without any structural change and is the basis for controlling and optimizing building performance. Artificial Intelligence (AI) techniques show much potential due to their accuracy and malleability in the field of pattern recognition, and using these models it is possible to adjust the building services in real time. Thus, the objective of this paper is to determine the AI technique that best forecasts electrical loads. The suggested techniques are random forest (RF), support vector regression (SV

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Müller, Robert, and Nour El Din Sharaf. "Combining AI and Machine Learning with Building Data Modeling to Detect and Locate Defects in Railway Infrastructure." International Academic Journal of Science and Engineering 11, no. 3 (2024): 27–30. https://doi.org/10.71086/iajse/v11i3/iajse1157.

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Owing to the elevated need for the railway system nowadays, the velocity and capacity of locomotives are inclined to rise. The impact of the harsh climate is concurrently worsening. This leads to degrading railway infrastructures (RI), resulting in flaws. Deficiencies may impact customer satisfaction and the operational security of the RI. Early detection of faults in RI helps mitigate operational risks, save maintenance costs, and enhance resource handling efficiency. This study integrated Artificial Intelligence (AI) and machine learning (ML) with building data modeling (BDM) to identify and

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Mazumder, Rajib, and Muhammad Anwar Hossain. "AI Hub: Idea to Innovative Service - An AI Service Hub for the Citizens of Bangladesh to Accelerate the Implementation of Smart Bangladesh." International Journal of Scientific Research and Management (IJSRM) 12, no. 05 (2024): 1217–33. http://dx.doi.org/10.18535/ijsrm/v12i05.ec07.

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In the contemporary digital era, the integration of Artificial Intelligence (AI) has become imperative for nations striving towards comprehensive development. Bangladesh, with its ambitious vision of achieving a Smart Bangladesh, stands at the forefront of leveraging AI technologies to enhance governance, improve public services, and foster economic growth. Recognizing the pivotal role of AI in this journey, the concept of an AI Service Hub emerges as a transformative initiative to empower citizens and expedite the realization of a technologically advanced society. The AI Service Hub serves as

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Han Zengfu, Kong Jiankun, Wang Zhiguo, et al. "AI-based network topology optimization system." ITU Journal on Future and Evolving Technologies 2, no. 4 (2021): 81–90. http://dx.doi.org/10.52953/yxtb5085.

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Existing network topology planning does not fully consider the increasing network traffic and problem of uneven link capacity utilization, resulting in lower resource utilization and unnecessary investments in network construction. The AI-based network topology optimization system introduced in this paper builds a Long Short-Term Memory (LSTM) model for time series traffic forecasting, which uses NetworkX, a Python library, for graph analysis, dynamically optimizes the network topology by edge deletion or addition based on traffic over nodes, and ensures network load balancing when node traffi

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Rathoure, Ashok K., and Ajay Kumar Rathaur. "AI and IoT in biodiversity assessment." Journal of Aquaculture & Marine Biology 13, no. 3 (2024): 108–15. http://dx.doi.org/10.15406/jamb.2024.13.00404.

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The integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies has revolutionized biodiversity assessment practices in recent years. This comprehensive review explores the various applications of AI and IoT in biodiversity assessment, highlighting their contributions to data collection, analysis, and conservation efforts. The synergy between AI algorithms and IoT sensors enables real-time monitoring of species diversity, habitat health, and environmental changes, thereby enhancing our understanding of ecosystem dynamics and supporting effective conservation strategie

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Hanif, Asif. "Global Health and the Role of Artificial Intelligence." Pioneer Journal of Biostatistics and Medical Research 2, no. 4 (2025): 1–2. https://doi.org/10.61171/v02.04.4.

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Artificial intelligence (AI) is revolutionizing global health by providing novel solutions to enduring concerns. AI has shown significant promise in enhancing diagnosis and treatment accuracy, as well as in advancing healthcare delivery in low- and middle-income countries (LMICs). Technologies such as machine learning and natural language processing are now used across several medical professions, improving results and diminishing inequities. However, challenges like as ethical quandaries, insufficient infrastructure and data related biases should be addressed to provide impartial access. By p

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Eche Samuel Okem, Emmanuel Adikwu Ukpoju, Abayomi B. David, and Joy Otibhor Olurin. "ADVANCING INFRASTRUCTURE IN DEVELOPING NATIONS: A SYNTHESIS OF AI INTEGRATION STRATEGIES FOR SMART PAVEMENT ENGINEERING." Engineering Science & Technology Journal 4, no. 6 (2023): 533–54. http://dx.doi.org/10.51594/estj.v4i6.679.

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This research focuses on the transformational potential of artificial intelligence (AI) towards the field of pavement engineering, particularly considering underdeveloped nations. This exploratory study aims to shed light on the complex effects AI has on pavement engineering and management processes, as well as various strategic, policy, and ethical perspectives underpinning its implementation. By using a systematic process, the study builds on information from academic papers, case studies, and industry research to create more enriching knowledge on this topic. Through a robust study, it is s

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Dr. Abdul Qayyum, Zeshan Rafique, Syed Shehr Wa Ali Shah, Shahbaz Ahmad, and Zulqarnain Haider. "Artificial Intelligence (AI)-Driven Curriculum Development in Early Childhood Education: Educators' Insights, Barriers, and Policy Pathways." Research Journal of Psychology 3, no. 1 (2025): 713–33. https://doi.org/10.59075/rjs.v3i1.102.

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The integration of Artificial Intelligence (AI) in early childhood education (ECE) has gained global attention for its potential to enhance personalized learning and inclusivity. However, challenges such as teacher preparedness, infrastructure limitations, and ethical concerns hinder its effective implementation, particularly in developing contexts. This study explores the perceptions of educators regarding AI-driven curriculum development in ECE, identifies challenges and opportunities, and assesses the effectiveness of AI-based learning models. A qualitative research approach was used, invol

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Kayusi, Fredrick, Srinivas Kasulla, S. J. Malik, et al. "Advancing Algorithmic Justice: A Systematic Review of Fair Decision-Making Protocols in Healthcare AI." Africa Journal For Law and Development Research (AJFLDR) 2024, no. 11 (2024): 39–52. https://doi.org/10.62839/AJFLDR.v01.v01.39-52.

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<strong>Abstract:</strong> This paper provides a comprehensive analysis of artificial intelligence (AI) implementation in Ghana’s healthcare system, synthesizing findings from recent Ghanaian studies. It examines legal and regulatory frameworks, ethical considerations, bias and fairness, transparency and accountability, interdisciplinary approaches, patient rights and data protection, healthcare access and equity, and implementation and oversight. The analysis reveals both significant opportunities for AI to improve healthcare delivery in Ghana and substantial challenges in ensuring its

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