Relevant bibliographies by topics / Keywords: Artificial Intelligence adoption

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Keywords: Artificial Intelligence adoption'

Author: Grafiati
Published: 7 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Keywords: Artificial Intelligence adoption"

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Kuzembayeva, N., Sh Nurgazy, A. Kaliyeva, and D. Khalizhan. "IMPACT OF ARTIFICIAL INTELLIGENCE ON ORGANIZATIONAL PERFORMANCE." Farabi Journal of Social Sciences 11, no. 1 (2025): 22–28. https://doi.org/10.26577/fjss20251113.

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This research explores how faculty training and development initiatives influence organizational performance within Kazakhstan's higher education institutions. It further examines the mediating effect of AI adoption on this relationship. A structured questionnaire was used as the primary method for data collection, with responses gathered from a sample of 218 employees working in higher education institutions across Kazakhstan. The results indicate that AI adoption serves as an intermediary factor between training and development practices and organizational performance, confirming the propose
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Ahmed Arafa, Mostafa, and Karim Hamda Farhat. "The Integration of Artificial Intelligence in Physicians' Daily Practice for Diagnosis, Prediction, And Disease Management in the Arab World." International Journal of Research and Review 11, no. 10 (2024): 550–54. http://dx.doi.org/10.52403/ijrr.20241049.

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Artificial intelligence (AI) is developing rapidly. Integrating AI into healthcare practices in the Arab world will transform diagnosis, prediction, and disease management. Today, countries such as Saudi Arabia and the United Arab Emirates (UAE) are at the forefront of AI adoption in healthcare, supported by strategic frameworks such as Saudi Arabia's Vision 2030 and the UAE National Artificial Intelligence Strategy 2031. However, adopting AI in daily healthcare practice on a large scale faces many obstacles that need to be overcome. Keywords: Artificial intelligence, AI, healthcare practice,
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Akhileshwari,, Asamani. "Navigating the Connections Among ‘Financial Inclusion’, Digital Lending Adoption, and Financial Literacy in India: The Mediating Role of Artificial Intelligence." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48940.

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Abstract: With an eye towards "Artificial Intelligence (AI)," this paper looks at the relationship between "digital lending adoption," "digital financial literacy," and "financial inclusion" in India. Based on earlier studies showing the critical need of "digital financial literacy" in advancing "financial inclusion," the article underlines the significance of financial technology solutions enhanced by artificial intelligence as a primary facilitator. The findings show that by streamlining complex financial duties and tackling financial literacy gaps, artificial intelligence helps low-income p
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Kalava, Sudheer Peddineni. "Best AI Framework Guide: Build Production-Ready Agents That Work." International Scientific Journal of Engineering and Management 03, no. 12 (2024): 1–9. https://doi.org/10.55041/isjem02191.

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Artificial Intelligence (AI) frameworks serve as the foundation for building scalable, production-ready AI agents that enable automation, decision-making, and intelligent interactions. This paper explores the architecture, core components, and best practices for selecting, deploying, and optimizing AI agent frameworks. Additionally, it addresses security considerations, compliance standards, performance enhancements, and real-world integration strategies for enterprise adoption. Keywords Artificial Intelligence, AI Agents, Automation, Scalability, Security, Optimization, Enterprise AI
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Olaoye, Ayoola Azeez. "Artificial Intelligence and Enhancing Accounting Practices in Selected African Countries." Jurnal Akuntansi 17, no. 1 (2025): 36–50. https://doi.org/10.28932/jam.v17i1.10729.

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Purpose – As the firms in Africa strive to modernize and compete globally, Artificial Intelligence adoption becomes imperative for the transformation of their accounting practices, particularly in Nigeria, South Africa, and Kenya. The aim of this study is therefore to examine the role of AI in improving accounting processes and operational efficiency in selected multinational companies in three under-studied countries. Design/methodology/approach – The study used a quantitative research design through questionnaires distributed to Chief Financial Officers/Accountants in 30 multinational firms
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Kamardina, Y. V., S. O. Polyarush-Safronenko, and Yu V. Vyshnevska. "HUMAN RIGHTS IN THE ERA OF ARTIFICIAL INTELLIGENCE." Vìsnik Marìupolʹsʹkogo deržavnogo unìversitetu. Serìâ: Pravo 14, no. 27 (2024): 71–78. http://dx.doi.org/10.34079/2226-3047-2023-14-27-71-78.

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The article examines topical issues of international legal regulation of the status of artificial intelligence and compliance with international human rights standards. Starting with the evolution of the formation and development of artificial intelligence, the article draws attention to the importance of the legal relationship with international law. The article emphasises the importance of recent legal developments, in particular, the adoption by the Council of Europe of the first Convention for the Protection of Human Rights and Democracy with regard to Artificial Intelligence in 2024. In a
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PANĂ-MICU, Florentina. "ARTIFICIAL INTELLIGENCE IN THE PUBLIC SECTOR- CHALLENGES, OPPORTUNITIES AND BEST PRACTICES." Journal of Public Administration, Finance and Law 32 (2024): 393–99. http://dx.doi.org/10.47743/jopafl-2024-32-29.

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Artificial Intelligence (AI) is increasingly influencing the functioning of public institutions, offering innovative solutions to enhance governance, public service delivery, and operational efficiency. This article aims to explore best practices in the use of AI for public service delivery and identify the main advantages of using artificial intelligence in the public sector. Additionally, it examines how Romania is aligning itself in the process of integrating AI technologies through the adoption of the National Strategy on Artificial Intelligence 2024-2027. Therefore, the purpose of this re
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Panwar, Shreya. "Perception of Artificial Intelligence towards the Development of Human Resources Management Practices." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 11 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26995.

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This research paper explores the perception of artificial intelligence (AI) and its impact on the development of human resources management (HRM) practices in organizations. As artificial intelligence continues to advance rapidly, its potential to transform various aspects of HRM is becoming increasingly evident. This study examines how HR professionals and employees perceive their perception of artificial intelligence, its potential benefits, challenges, and ethical implications for HRM practices. The paper also delves into the readiness of organizations to adopt AI-driven HRM solutions and t
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AMITABH KUMAR. "Artificial Intelligence in Education: Revolutionizing Teaching and Learning." Journal of Asian Primary Education (JoAPE) 1, no. 1 (2024): 64–68. https://doi.org/10.59966/joape.v1i1.1207.

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Artificial Intelligence (AI) is transforming education by enhancing personalized learning, automating routine tasks, and improving both student engagement and teaching effectiveness. However, challenges such as inadequate teacher training, infrastructural limitations, and data privacy concerns hinder AI's widespread adoption in educational settings. This paper presents findings from a survey of 150 educators and classroom observations, highlighting the impact of AI on teaching and learning. Results show significant improvements in student engagement, academic performance, and a reduction in te
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J I, SHYAMSUNDAR. "UNDERSTANDING STUDENT PREFERENCES AND FACTORS INFLUENCING THE ADOPTION OF AI TOOLS IN ACADEMIC ENVIRONMENTS." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 01 (2024): 1–6. http://dx.doi.org/10.55041/ijsrem28204.

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The research article explores the factors influencing student's preferences towards the usage of Artificial Intelligence (AI) tools in their academics. The study employs exploratory research methods, beginning with an online questionnaire distributed to university students, aiming to identify key attributes or variables affecting the preference for AI tools in academic work. The data collected is used to perform statistical analysis, employing factor analysis to reduce the 25 attributes. The results reveal that the attributes are reduced to 5 factors such as 'Easiness and convenience,' 'Intere
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Dissertations / Theses on the topic "Keywords: Artificial Intelligence adoption"

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Nguyen, Quynh. "Three Essays on Artificial Intelligence Adoption and Use." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1538732/.

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Artificial intelligence (AI) is quickly transforming business operations and society, as AI capabilities are incorporated into applications ranging from mobile personal assistants to self-driving cars. The potentially disruptive nature of AI calls for an extensive investigation into all aspects of AI-human interactions at individual, group, organizational and market levels. However, there is paucity of academic information systems (IS) research in this area that goes beyond the development and testing of specific narrow AI capabilities. AI represents an important opportunity for organizationa
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Kim, Jee Won. "How speciesism affects artificial intelligence (AI) adoption intent." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/228673/1/Jee%20Won_Kim_Thesis.pdf.

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As there have been concerns about the excessive advancement of artificial intelligence (AI) surpassing humans, exploring reactions to AI as challenging human superiority is meaningful. By examining how the hierarchical and discriminative views on animals (speciesism) affects the views on non-living AI, this thesis has significant and novel contributions to AI adoption literature and AI product marketing.
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Damerji, Hassan. "Technology Readiness Impact on Artificial Intelligence Technology Adoption by Accounting Students." Thesis, University of La Verne, 2020. http://pqdtopen.proquest.com/#viewpdf?dispub=27547476.

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Artificial Intelligence (AI) is the way forward in accounting and auditing. The purpose of this study was to examine the relationship between accounting students’ level of technology readiness (TR) and AI technology adoption (TA). This quantitative study examined the independent variables of TR, perceived ease of use (PEOU), and perceived usefulness (PU) and the dependent variable of TA. Moreover, the present study examined the mediating effect of PEOU and PU on the relationship between TR and TA. The present study was related to individual accounting students’ perceptions of TR and TA. Studen
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Rao, Tarun. "Factors critical to the organisational adoption of artificial intelligence : a South African perspective." Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/64917.

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The purpose of this research is to understand the factors critical to the organisation level adoption of Artificial Intelligence (AI) based technologies in a South African context. Considering the emerging nature of AI based technologies and the relative immaturity of extant academic studies at the intersection of AI and the business context, the current study finds salience in its propensity to support senior management in the considerations that they must make when tackling the AI based adoption decision. Considering the relative immaturity of extant studies an exploratory qualitative approa
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Regona, Massimo. "Opportunities and adoption constraints of artificial intelligence in the construction industry: A scoping study." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/232514/1/Massimo_Regona_Thesis.pdf.

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This MPhil thesis provides an overview of AI technologies and the key opportunities and challenges these technologies bring to the construction industry. The first study was a literature review that identified and explored the theoretical foundations underpinning AI technologies that are currently being used in construction, specifically in the design, planning and construction stages. Secondly, the study used social media analytics to explore AI technology adoption, prospects and constraints in the Australian construction industry. Finally, a sentiment analysis established the opportunities,
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Kang, Johan, and Sebastian Westskytte. "Diffusion of Cybersecurity Technology - Next Generation, Powered by Artificial Intelligence." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-246027.

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The cyber world is growing as more information is converted from analogue to digital form. While convenience has been the main driver for this change little effort has been made on securing the data. Data breaches are growing in number and each breach is growing in severity. Combined with regulatory pressure organizations are starting to realize the importance of security. The increased threat level is also driving the security market for more potent solutions and artificial intelligence (AI) have in recent years been implemented to enhance the capabilities of security technologies.  The thesi
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Ineza, Kayihura Didier. "Adoption of Artificial Intelligence in Commercial Real Estate : Data Challenges, Transparency and Implications for Property Valuations." Thesis, KTH, Fastigheter och byggande, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-298074.

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Investment decision in the property market is closely connected to property valuation. Thus, accuracy of valuation results and deep analysis of the market is essential. Artificial Intelligence (AI) models have been successfully adopted in different fields and markets. However, the real estate market is typically lagged in time to adapt to these changes. Swedish commercial property market arrangements are characterized by increasing confidentiality of certain data types. As a consequence, the adoption of the AI valuation models in the Swedish commercial property market is slowed down.  This stu
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Zhu, Ying. "PREFERENCES: OPTIMIZATION, IMPORTANCE LEARNING AND STRATEGIC BEHAVIORS." UKnowledge, 2016. http://uknowledge.uky.edu/cs_etds/46.

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Preferences are fundamental to decision making and play an important role in artificial intelligence. Our research focuses on three group of problems based on the preference formalism Answer Set Optimization (ASO): preference aggregation problems such as computing optimal (near optimal) solutions, strategic behaviors in preference representation, and learning ranks (weights) for preferences. In the first group of problems, of interest are optimal outcomes, that is, outcomes that are optimal with respect to the preorder defined by the preference rules. In this work, we consider computational pr
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Zaoui, Amina. "Impact de l'adoption de l'Intelligence Artificielle sur la performance organisationnelle dans le secteur aéronautique : une étude quantitative et qualitative sur les facteurs déterminants et les obstacles." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2025. http://www.theses.fr/2025TLSEP021.

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Le secteur aéronautique a manifesté un intérêt croissant pour l’Intelligence Artificielle (IA) ces dernières années, reconnaissant son potentiel à transformer les opérations, améliorer l’efficacité et optimiser les performances. Cependant, l’adoption de l’IA dans ce domaine s’accompagne de défis spécifiques, nécessitant une compréhension approfondie de ses implications sur la performance organisationnelle.Cette thèse examine l’impact de l’IA sur la performance dans le secteur aéronautique à travers une approche structurée. Tout d’abord, une analyse bibliométrique a été réalisée pour explorer l
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Savola, Tommi, Tyko Tuohimaa, and Sebastian Berg. "AI-Enhanced Marketing Management – Factors Influencing Adoption in SMEs." Thesis, Högskolan i Jönköping, Internationella Handelshögskolan, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-39908.

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Recent developments and hype around artificial intelligence (AI) have arisen as result of two main factors: increase in computational power and data. Although marketing is considered as one of the main business applications within AI today, there is a lack of literature combining the disciplines. Marketing management tools, which utilise AI in supporting decision making are referred to as knowledge-driven marketing management support systems (MMSS). These systems provide besides quantitative analysis, further qualitative facets into marketing management. Despite the willingness of many SMEs to
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Books on the topic "Keywords: Artificial Intelligence adoption"

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Varlamov, Oleg. Fundamentals of creating MIVAR expert systems. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1513119.

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Methodological and applied issues of the basics of creating knowledge bases and expert systems of logical artificial intelligence are considered. The software package "MIV Expert Systems Designer" (KESMI) Wi!Mi RAZUMATOR" (version 2.1), which is a convenient tool for the development of intelligent information systems. Examples of creating mivar expert systems and several laboratory works are given. The reader, having studied this tutorial, will be able to independently create expert systems based on KESMI. 
 The textbook in the field of training "Computer Science and Computer Engineering"
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Varlamov, Oleg. Mivar databases and rules. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.

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The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in th
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Poot, Matthijs, and Daniel Samaan. Rethinking production processes with AI and avoiding the innovator’s dilemma. ILO, 2024. http://dx.doi.org/10.54394/blss4423.

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This brief explores the challenges traditional companies face in fully harnessing the transformative potential of Artificial Intelligence (AI). Drawing parallels with historical shifts like the assembly line, the brief argues that AI adoption requires a holistic rethinking of work processes rather than incremental improvements. It highlights the multi-modal capabilities of Generative AI (GenAI) and underscores the need for further research to better understand its impact on productivity and business operations.
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Sood, Kiran, Pallavi Tyagi, Naveen Chilamkurti, Simon Grima, and B. Balamurugan. Adoption and Effect of Artificial Intelligence on Human Resources Management. Emerald Publishing Limited, 2023.

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Sood, Kiran, Pallavi Tyagi, Naveen Chilamkurti, Simon Grima, and B. Balamurugan. Adoption and Effect of Artificial Intelligence on Human Resources Management. Emerald Publishing Limited, 2023.

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Sood, Kiran, Pallavi Tyagi, Naveen Chilamkurti, Simon Grima, and B. Balamurugan. Adoption and Effect of Artificial Intelligence on Human Resources Management. Emerald Publishing Limited, 2023.

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Sood, Kiran, Pallavi Tyagi, Naveen Chilamkurti, Simon Grima, and B. Balamurugan. Adoption and Effect of Artificial Intelligence on Human Resources Management. Emerald Publishing Limited, 2023.

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Sood, Kiran, Pallavi Tyagi, Naveen Chilamkurti, Simon Grima, and B. Balamurugan. Adoption and Effect of Artificial Intelligence on Human Resources Management. Emerald Publishing Limited, 2023.

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Sood, Kiran, Pallavi Tyagi, Naveen Chilamkurti, Simon Grima, and B. Balamurugan. Adoption and Effect of Artificial Intelligence on Human Resources Management. Emerald Publishing Limited, 2023.

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Mohan Kumar, Dr S. Artificial Intelligence: Foundations, Applications, and the Generative Future. Magestic Technology Solutions (P) Ltd, Chennai, Tamil Nadu, India, 2025. https://doi.org/10.47716/978-93-92090-63-9.

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Artificial Intelligence (AI) is no longer confined to laboratories and theoretical models; it is now a driving force behind the digital transformation of society. Artificial Intelligence: Foundations, Applications, and the Generative Future provides an in-depth journey through AI’s essential principles, its wide-ranging applications, and the revolutionary impact of generative technologies. The book methodically builds knowledge from classical AI concepts like intelligent agents, search strategies, and knowledge representation, to advanced learning models including neural networks and machine l
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Book chapters on the topic "Keywords: Artificial Intelligence adoption"

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Singler, Beth. "Adoption." In Religion and Artificial Intelligence. Routledge, 2024. http://dx.doi.org/10.4324/9781003256113-3.

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Wiesmüller, Sabine, Nele Fischer, Wenzel Mehnert, and Sabine Ammon. "Responsible AI Adoption Through Private-Sector Governance." In Responsible Artificial Intelligence. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-09245-9_5.

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Ünver, H. Akın, and Arhan S. Ertan. "Politics of Artificial Intelligence Adoption." In Democratic Frontiers. Routledge, 2022. http://dx.doi.org/10.4324/9781003173427-5.

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Hu, Shengwei, Bicheng Li, Kongjie Lin, Rui Wang, and Kai Liu. "Text Sentiment Transfer Methods by Using Sentence Keywords." In Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55789-8_4.

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Shin, Dong-Guk, and Lung-Yung Chu. "Establishing logical connectivity between query keywords and database contents." In Advances in Artificial Intelligence. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64575-6_39.

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Viani, Natalia, Rashmi Patel, Robert Stewart, and Sumithra Velupillai. "Generating Positive Psychosis Symptom Keywords from Electronic Health Records." In Artificial Intelligence in Medicine. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21642-9_38.

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Pilon, Ricardo V. "Applied Psychology and AI Adoption." In Artificial Intelligence in Commercial Aviation. Routledge, 2023. http://dx.doi.org/10.4324/9781003018810-30.

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Smit, Danie, Sunet Eybers, and Jarod Smith. "A Data Analytics Organisation’s Perspective on Trust and AI Adoption." In Artificial Intelligence Research. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95070-5_4.

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Colla, Davide, Enrico Mensa, and Daniele P. Radicioni. "Semantic Measures for Keywords Extraction." In AI*IA 2017 Advances in Artificial Intelligence. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70169-1_10.

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Ventura, João, and Joaquim Silva. "Automatic Extraction of Explicit and Implicit Keywords to Build Document Descriptors." In Progress in Artificial Intelligence. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40669-0_42.

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Conference papers on the topic "Keywords: Artificial Intelligence adoption"

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Gui, Anderes, Imanuela Tuhenay, Nadine Shakira Rahma, Yuliana Lisanti, Veronica, and Siti Rohaida Mohamed Zainal. "Artificial Intelligence Readiness and Adoption in Auditing." In 2024 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM). IEEE, 2024. https://doi.org/10.1109/cenim64038.2024.10882695.

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Adediran, Anthonia Oluwatosin, Samuel-Soma M. Ajibade, Muhammed Basheer Jasser, et al. "Artificial Intelligence Adoption in Housing: A Bibliometric Analysis." In 2025 21st IEEE International Colloquium on Signal Processing & Its Applications (CSPA). IEEE, 2025. https://doi.org/10.1109/cspa64953.2025.10933225.

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Bhushan, Sushant, and Sarvottam Dixit. "Explainable AI for Shaping Adoption of Artificial Intelligence." In 2024 Asian Conference on Intelligent Technologies (ACOIT). IEEE, 2024. https://doi.org/10.1109/acoit62457.2024.10939416.

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Khanna, Aseem, and Anuradha Bhusri. "Navigating AI Adoption – An “AI Verse” Framework for Enterprises." In 2025 IEEE Conference on Artificial Intelligence (CAI). IEEE, 2025. https://doi.org/10.1109/cai64502.2025.00279.

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Gruenbichler, Rudolf, Lianna Wijaya, Cheng Kin Meng, Katharina Greimel, Tiurida Lily Anita, and Sylvia Samuel. "Artificial Intelligence Adoption Among Accountants: Empirical Study in Austria." In 2024 International Conference on Information Management and Technology (ICIMTech). IEEE, 2024. https://doi.org/10.1109/icimtech63123.2024.10780935.

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Abad, Arif, Mohd Abdul Muqeet Maaz, Mohd Salman Shamsi, and Shahzaib Tariq. "Artificial Intelligence and Agriculture: Unveiling Adoption Patterns Through UTAUT2." In 2024 1st International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI). IEEE, 2024. https://doi.org/10.1109/icscai61790.2024.10866698.

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Mitra, Arijit, A. Seetharaman, and K. Maddulety. "Adoption of Artificial Intelligence Enabling Value Creation in Business." In 2024 4th International Conference on Robotics, Automation and Artificial Intelligence (RAAI). IEEE, 2024. https://doi.org/10.1109/raai64504.2024.10949520.

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Liew, Kongmeng, Xiaoli Wu, and Zhouqing Zhang. "Trust, Support, and Adoption Intentions Towards Generative AI are Context Dependent." In 2025 IEEE Conference on Artificial Intelligence (CAI). IEEE, 2025. https://doi.org/10.1109/cai64502.2025.00051.

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Avitia-Carlos, Patricia, Francisco Gárate Vergara, and José Antonio Ramírez Díaz. "EDUCATIONAL ARTIFICIAL INTELLIGENCE (AIED) ADOPTION POLICIES IN HIGHER EDUCATION INSTITUTIONS." In 19th International Technology, Education and Development Conference. IATED, 2025. https://doi.org/10.21125/inted.2025.1608.

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Barton, Richard, P. W. C. Prasad, Indra Seher, and Amr Elchouemi. "Artificial Intelligence (AI) in Cybersecurity and Inhibitors to AI Adoption." In 2024 International Conference on Intelligent Education and Intelligent Research (IEIR). IEEE, 2024. https://doi.org/10.1109/ieir62538.2024.10959777.

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Reports on the topic "Keywords: Artificial Intelligence adoption"

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Pasupuleti, Murali Krishna. Securing AI-driven Infrastructure: Advanced Cybersecurity Frameworks for Cloud and Edge Computing Environments. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv225.

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Abstract: The rapid adoption of artificial intelligence (AI) in cloud and edge computing environments has transformed industries by enabling large-scale automation, real-time analytics, and intelligent decision-making. However, the increasing reliance on AI-powered infrastructures introduces significant cybersecurity challenges, including adversarial attacks, data privacy risks, and vulnerabilities in AI model supply chains. This research explores advanced cybersecurity frameworks tailored to protect AI-driven cloud and edge computing environments. It investigates AI-specific security threats,
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Pasupuleti, Murali Krishna. Decentralized Creativity: AI-Infused Blockchain for Secure and Transparent Digital Innovation. National Education Services, 2025. https://doi.org/10.62311/nesx/rrvi125.

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Abstract The convergence of artificial intelligence (AI) and blockchain technology is transforming the creative economy by enabling secure, transparent, and decentralized innovation in digital content creation, intellectual property management, and monetization. Traditional creative industries are often constrained by centralized platforms, opaque copyright enforcement, and unfair revenue distribution, which limit the autonomy and financial benefits of creators. By leveraging blockchain’s immutable ledger, smart contracts, and non-fungible tokens (NFTs), digital assets can be authenticated, to
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Pasupuleti, Murali Krishna. Neural Computation and Learning Theory: Expressivity, Dynamics, and Biologically Inspired AI. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv425.

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Abstract: Neural computation and learning theory provide the foundational principles for understanding how artificial and biological neural networks encode, process, and learn from data. This research explores expressivity, computational dynamics, and biologically inspired AI, focusing on theoretical expressivity limits, infinite-width neural networks, recurrent and spiking neural networks, attractor models, and synaptic plasticity. The study investigates mathematical models of function approximation, kernel methods, dynamical systems, and stability properties to assess the generalization capa
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King, Wayne. Barriers to Adoption of Artificial Intelligence in Metal Additive Manufacturing. SAE International, 2025. https://doi.org/10.4271/epr2025001.

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<div class="section abstract"><div class="htmlview paragraph">Artificial intelligence (AI) is poised to significantly impact metal additive manufacturing (AM). Understanding how one might use AI in AM is challenging because AM experts are not AI experts, nor the other way around. This document introduces AI in AM and guides researchers in accessing relevant literature. It also discusses the hype surrounding AI in AM, the rush to publish peer-reviewed papers that use AI in AM, and the resulting uneven quality of the literature. Conclusions regarding the application of AI in both lar
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Vargas, Fernando, and Arturo Muente. Artificial Intelligence Framework for the Inter-American Development Group. Inter-American Development Bank, 2025. https://doi.org/10.18235/0013377.

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Artificial intelligence (AI) has the potential to become a transformative general-purpose technology, reshaping economic, social, and institutional frameworks globally. The Inter-American Development Bank Group (IDBG) recognizes the urgency of fostering AI adoption in Latin America and the Caribbean to catalyze productivity, inclusion, and sustainable development. This document provides a high-level strategic framework to guide IDBGs interventions in advancing AI adoption and responsible use across the region. The document reviews key challenges facing the three dimensions of AI institutions a
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Haddad, Ibrahim. Artificial Intelligence and Data in Open Source. The Linux Foundation, 2022. https://doi.org/10.70828/zaow8899.

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Artificial intelligence (AI) is no different from any other technology domain where OSS dominates. As with other industries, OSS adoption in the AI field has increased the use of open source in products and services, contributions to existing projects, the creation of projects fostering collaboration, and the development of new technologies. Artificial Intelligence and Data in Open Source reviews critical challenges in the open source AI ecosystem, discusses common characteristics across AI and data projects, and presents the role of the LF AI & Data Foundation in empowering innovators and
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Hunt, Jennifer, Iain Cockburn, and James Bessen. Is Distance from Innovation a Barrier to the Adoption of Artificial Intelligence? National Bureau of Economic Research, 2024. http://dx.doi.org/10.3386/w33022.

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Chernavskikh, Vladislav. Nuclear Weapons and Artificial Intelligence: Technological Promises and Practical Realities. Stockholm International Peace Research Institute, 2024. http://dx.doi.org/10.55163/vbqx6088.

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Recent advances in the capabilities of artificial intelligence (AI) have increased state interest in leveraging AI for military purposes. Military integration of advanced AI by nuclear-armed states has the potential to have an impact on elements of their nuclear deterrence architecture such as missile early-warning systems, intelligence, surveillance and reconnaissance (ISR) and nuclear command, control and communications (NC3), as well as related conventional systems. At the same time, a number of technological and logistical factors can potentially limit or slow the adoption of AI in the nuc
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Kong, Byeongjo, Zhigang Li, Sara Ratner, Erik Hemberg, and A. K. M. Shamsul Haque. Artificial Intelligence for Education in Bangladesh: Insights from the First Small-Scale Artificial Intelligence Needs Assessment and Training for Primary Education Teachers. Asian Development Bank, 2024. https://doi.org/10.22617/wps240575-2.

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Bangladesh, with one of the largest education systems in the world, has started to lay the foundation for reskilling its youth in preparation for an automated world of work. The country has thus looked to using artificial intelligence (AI) in the education sector, recognizing its promise to transform the teaching–learning landscape while acknowledging the challenges inherent in its adoption. This paper presents results of an AI needs assessment survey and training workshop conducted among primary education teachers from 2023 to 2024, to gather opinions on pedagogies that could benefit from AI-
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Agarwal, Vivek, Cody Walker, Koushik Araseethota Manjunatha, Torrey Mortenson, Nancy Lybeck, and Andrei Gribok. Technical Basis for Advanced Artificial Intelligence and Machine Learning Adoption in Nuclear Power Plants. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1889877.

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