Relevant bibliographies by topics / AI Talent

Contents

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

Academic literature on the topic 'AI Talent'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "AI Talent"

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Cai, Can. "Training Mode of Innovative Accounting Talents in Colleges Using Artificial Intelligence." Mobile Information Systems 2022 (July 19, 2022): 1–11. http://dx.doi.org/10.1155/2022/6516658.

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With the rise of big data revolution, a new generation of artificial intelligence (AI) is gaining momentum and the AI era will come strongly. However, the accounting profession is also showing a booming trend in colleges and universities, which, as the main base of higher education talent training, also undertake a considerable part of the task of training accounting talents. As traditional accounting is gradually replaced, finance professionals are being forced to gradually change to management talents. In the information era, how to realize the transformation of talent cultivation mode of fi
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Alam, Mohammad Sarwar, Kazi Sirajum Munira, Md Sahidur Rahman, Md Aftab Uddin, and Ayesha Akter. "Artificial Intelligence (AI) for Talent Acquisition." International Journal of Human Capital and Information Technology Professionals 13, no. 1 (2024): 1–18. http://dx.doi.org/10.4018/ijhcitp.303950.

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The present study's aim is to investigate the intention to use and actual use of a artificial intelligence (AI) for talent acquisition in Bangladesh. The authors used deductive reasoning approach in a positive paradigm. The study finally collected 243 responses through self-administered questionnaire and used the PLS-based structural equation modeling to analyze the data. The findings of this study revealed that each of the predictors is significantly associated with the intention to use and actual use of AI for recruiting talents, excepting the influence of facilitation conditions on actual u
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Aruna, Dr Chittineni. "Revolutionizing Talent Scouting with AI and Blockchain." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43025.

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Identifying and nurturing emerging talent requires effective scouting mechanisms, yet traditional methods suffer from significant limitations such as subjective evaluations, lack of transparency, and ineffective progress monitoring. These challenges hinder the fair and efficient identification of high-potential individuals, particularly in fields like artificial intelligence, blockchain, and other cutting-edge technologies. This study presents a novel platform that leverages AI analytics and Blockchain tokenization to overcome the constraints of conventional talent identification and investmen
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He, Ling, and Hashima Binti Hamid. "The suitability of skilled talent training in higher vocational colleges based on AI and 5G network connection in the context of educational transformation and upgrading." Journal of Infrastructure, Policy and Development 8, no. 12 (2024): 6964. http://dx.doi.org/10.24294/jipd.v8i12.6964.

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The development of artificial intelligence (AI) and 5G network technology has changed the production and lifestyle of people. AI also has promoted the transformation of talent training mode under the integration of college industry and education. In the context of the current transformation of education, AI and 5G networks are increasingly used in the education industry. This paper optimizes and upgrades the training mode of skilled talents in higher vocational colleges by using its advanced methods and technologies of information display. This means is helpful to analyze and solve a series of
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Yang, Fang, Junde Chen, Xiaowei Ge, and Shuyu Jiang. "Exploring Innovative Pathways for Cultivating Brand Marketing Talent through Virtual Digital Humans." Contemporary Education and Teaching Research 6, no. 5 (2025): 178–83. https://doi.org/10.61360/bonicetr252018280505.

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The deep integration of AI technology with the virtual digital human industry is driving a transformative shift in brand marketing from “digitalization” to “intelligentization”. Based on emotional practice theory, the industry-education integration model, and AI technology applications, this paper explores the integration mechanism of virtual digital human technology in the educational ecosystem and its innovative value in cultivating brand marketing talents. Through a comprehensive education platform that integrates government, industry, academia, research, and application, and serves as a ta
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Bingbing, Chen, Zhang Lei, Li Menghan, and Hu Xinyu. "Research on "AI+X" Composite Non-heritage Exhibition Design Talents Cultivation." Journal of New Media and Economics 1, no. 5 (2024): 13–20. https://doi.org/10.62517/jnme.202410504.

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In April 2018, the Ministry of Education proposed that it would gradually promote the construction of a new model of "AI+X"composite professional training. the current situation of non-heritage protection and the development of AI technology, as well as the emergence of "AI+X" composite talent cultivation mode, have brought new opportunities and challenges for non-heritage exhibition design. This study aims to analyse the current situation of "AI+X" technology in non-heritage exhibition design, discuss the necessity of talent training, and propose corresponding training strategies to inject ne
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Pillai, Rajasshrie, and Brijesh Sivathanu. "Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations." Benchmarking: An International Journal 27, no. 9 (2020): 2599–629. http://dx.doi.org/10.1108/bij-04-2020-0186.

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PurposeHuman resource managers are adopting AI technology for conducting various tasks of human resource management, starting from manpower planning till employee exit. AI technology is prominently used for talent acquisition in organizations. This research investigates the adoption of AI technology for talent acquisition.Design/methodology/approachThis study employs Technology-Organization-Environment (TOE) and Task-Technology-Fit (TTF) framework and proposes a model to explore the adoption of AI technology for talent acquisition. The survey was conducted among the 562 human resource managers
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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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Baratelli, Giulia, and Elanor Colleoni. "Does Artificial Intelligence (AI) Enabled Recruitment Improve Employer Branding?" International Journal of Business and Management 17, no. 2 (2022): 45. http://dx.doi.org/10.5539/ijbm.v17n2p45.

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Extant research over the last decades has stressed how artificial intelligence (AI) can be used to boost the recruitment process and to attract the best talents. Although AI is increasingly used for talent acquisition, with 36% of hiring processes expected to have a pre-screen through AI (Oracle, 2019) in the next two years, we have limited knowledge of how AI shapes talents’ perceptions about the organisation to which they are applying to. The goal of this research is to investigate if and how the usage of AI in the recruitment process improves employer attractiveness and employer b
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Hamid, Aditia Putra, Yanuar Zulardiansyah Arief, Brainvendra Widi Dionova, and Rosyid Ridlo Al-Hakim. "A Fuzzy Expert System for Talent Pool Management in Indonesia." A Fuzzy Expert System for Talent Pool Management in Indonesia 1, Vol. 1 No. 2 (2023): July 2023 (2024): 12. https://doi.org/10.59890/ijma.v1i2.73.

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Addressing the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) situation, one of the company's strategies is to design a talent management strategy program to identify talent needs based on the company's vision, mission, strategy, and values. Talent is the knowledge and abilities possessed by a person relevant to the company's needs, supporting the company's goals and strategies. The company has a system that designs and manages the talents of its employees to acquire and retain their employees, namely talent management (TM). Talent management is an organizational scheme that systema
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Dissertations / Theses on the topic "AI Talent"

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Paramita, Dhyana. "Digitalization in Talent Acquisition : A Case Study of AI in Recruitment." Thesis, Uppsala universitet, Institutionen för samhällsbyggnad och industriell teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-413081.

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The trend of changing technology has affected different sectors including human resources in the process of recruitment and selection. Different technology solutions offer various benefit for recruitment practices especially in terms of efficiency outcome while it seems to overlook the relationship outcomes. Whether or not to have a balance approach depends on how a firm views their own recruitment process. The purpose of this study is to understand firm’s orientation towards its approach in performing recruiting practices. The analysis and discussion is articulated through the phenomenon of A
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Weißenburger, Julius Eric. "Disruption in HR : the impact of Artificial Intelligence and machine learning innovation on recruiting." Master's thesis, 2020. http://hdl.handle.net/10400.14/31314.

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Talent is increasingly important for organizations which makes corporate recruitment a significant ongoing function. Recruiting top talent cannot occur where there are inefficiencies, high costs and lack of innovation. At the same time, artificial intelligence (AI) and machine learning (ML) are disrupting industries and different areas of business practice. This technology has the potential to create unprecedented value in recruiting functions also, by positively impacting efficiency, costs and employee fit. Despite rapid developments in the field of AI, academic literature on AI in recruitme
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Books on the topic "AI Talent"

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Nguyen, A. Tâm & tài, họ là ai?: People of devotion and talent. Nhà xuất bản Trẻ, 2013.

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Khang, Alex. AI-Oriented Competency Framework for Talent Management in the Digital Economy. CRC Press, 2024. http://dx.doi.org/10.1201/9781003440901.

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Cư, Nguynen Giao, ред. Ai mạnh nhrat. NXB Đà Nmang, 2004.

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Yamiqisi, De. Ai de jiao yu. Zhongguo shao nian er tong chu ban she, 2006.

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Tchya. Ai hát gizua rxung khuya. Đại Nam, 1987.

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Quroc, Minh. Ai mua hành tôi. 4th ed. NXB Kim Đsong, 2003.

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Nongfu, Zhang Muhua, Liu Ying ill, and Cai shi tu wen, eds. Ke ai de jing ling =. Jing ying chu ban she you xian gong si, 2004.

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ill, Sendak Maurice, ed. Qin ai de xiao li. Ge lin wen hua shi ye you xian gong si, 1995.

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Rocco, Emilia Di. Chaucer: Guida ai Canterbury tales. Carocci, 2003.

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Kim, Yong-nan. Nae ai ege kajang tŭllyŏ chugopʻŭn 100-kaji iyagi. Sesang Modŭn Chʻaek, 2000.

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Book chapters on the topic "AI Talent"

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Sharma, Rohan. "AI Talent Strategy." In AI and the Boardroom. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0796-1_15.

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Kamal, Yusuf, Amitabh Roy, Saifuddin Ahmad, and Raj Kumar Mishra. "AI in Talent Acquisition." In AI and Innovation in HRM. Routledge, 2025. https://doi.org/10.4324/9781003522157-16.

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Rogers, Bob. "HR and Talent Management." In Demystifying AI for the Enterprise. Productivity Press, 2021. http://dx.doi.org/10.4324/9781351032940-4.

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Weinstein, Emily, and Jeffrey Stoff. "China's quest for AI talent." In Chinese Power and Artificial Intelligence. Routledge, 2022. http://dx.doi.org/10.4324/9781003212980-6.

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Himani Srihita, Rachoru, Gurunadham Goli, and M. Rajya Laxmi. "Artificial Intelligence in Talent Acquisition." In AI and Innovation in HRM. Routledge, 2025. https://doi.org/10.4324/9781003522157-4.

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Saxena, Parul, Vidhi Agrawal, and Indira P. Pradhan. "AI-Powered Talent Acquisition and Recruitment." In Human Resource Management and Artificial Intelligence. Routledge, 2025. https://doi.org/10.4324/9781003474265-2.

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Vashishth, Tarun Kumar, Vikas Sharma, Kewal Krishan Sharma, and Sachin Chaudhary. "Future-Proofing Talent Management." In AI-Oriented Competency Framework for Talent Management in the Digital Economy. CRC Press, 2024. http://dx.doi.org/10.1201/9781003440901-10.

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Knox, Jeremy. "‘Talent’ and the international flow of AI expertise." In AI and Education in China. Routledge, 2023. http://dx.doi.org/10.4324/9781003375135-6.

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Horn, Martin, Xiang Li, Lin Chen, and Sabin Kafle. "A Multi-talent Healthcare AI Bot Platform." In Explainable AI in Healthcare and Medicine. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53352-6_15.

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Bhattacharya, Subhajit. "AI in Talent Management for Business Excellence." In Industry 4.0 Technologies for Business Excellence. CRC Press, 2021. http://dx.doi.org/10.1201/9781003140474-15.

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Conference papers on the topic "AI Talent"

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Kadirov, Abdumalik, Yulduzkhon Shakirova, Gulshodakhon Ismoilova, and Nodirakhon Makhmudova. "AI in Human Resource Management: Reimagining Talent Acquisition, Development, and Retention." In 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS). IEEE, 2024. http://dx.doi.org/10.1109/ickecs61492.2024.10617231.

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V, Akshaya, Vejaysundaram R, and Santhosh H. "Talent Tracer – AI Driven Interview Preparation Engine for Job Seekers using LLMs." In 2025 11th International Conference on Communication and Signal Processing (ICCSP). IEEE, 2025. https://doi.org/10.1109/iccsp64183.2025.11088608.

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Kundu, Sankhadip, and Saravanan Palani. "Unlocking Talent: Exploring the Potential of AI and ML Algorithms in Recruitment Process." In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT). IEEE, 2024. http://dx.doi.org/10.1109/iceect61758.2024.10739192.

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Lutfiani, Ninda, Untung Rahardja, Sutarto Wijono, Kristoko Dwi Hartomo, and Hindriyanto Purnomo. "Unlocking the Potential of AI-Enabled Startup through Digital Talent in Higher Education." In 2024 3rd International Conference on Creative Communication and Innovative Technology (ICCIT). IEEE, 2024. http://dx.doi.org/10.1109/iccit62134.2024.10701142.

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Indoria, Devadutta, Barani Dakshinamoorthy, M. Karthik, Manish Sharma, S. Kaliappan, and G. Manikandan. "Transforming HR in Finance by Leveraging IoT and AI for Strategic Talent Management." In 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63760.2024.10910324.

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Gupta, Muskan, S. Ammani, Mohan Ranga Rao Dontineni, B. R. Kumar, Monika Gupta, and Siva Koteswara Rao Katta. "The Future of Hr Marketing Ai-Driven Approaches to Talent Acquisition and Management." In 2024 International Conference on Intelligent Computing and Emerging Communication Technologies (ICEC). IEEE, 2024. https://doi.org/10.1109/icec59683.2024.10837377.

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Bhavsar, Nisarg, Sachish Singla, Divyansh Sharma, Rwik Dey, and Subarno Maji. "SATYA: Smart AI-driven Talent Yield Analyzer for Resume Screening and Recommendation Evaluation." In 2024 4th International Conference on Robotics, Automation and Artificial Intelligence (RAAI). IEEE, 2024. https://doi.org/10.1109/raai64504.2024.10949555.

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Halim, Erwin, Azani Cempaka Sari, Irma Kartika Wairooy, Muhamad Keenan Ario, Said Achmad, and Devi Fitrianah. "Performance Variations in Digital Talent: Gender-Based Insights from STEM and AI Education Backgrounds." In 2024 International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA). IEEE, 2024. https://doi.org/10.1109/icicyta64807.2024.10913074.

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Lou, Huiru. "Research on AI-driven talent training system for cruise industry and its optimization path." In International Conference on Machine Vision and Deep Learning (MVDL 2025), edited by Chengzhong Xu and Dickson K. W. Chiu. SPIE, 2025. https://doi.org/10.1117/12.3071214.

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Rinata, Vidra, Marini Othman, and Rajermani Thinakaran. "An Assessment of The Talent Management Practices At Aceh Government: A Way Forward In Leveraging AI." In 2024 International Conference on Computing Innovation, Intelligence, Technologies and Education (CIITE). IEEE, 2024. https://doi.org/10.1109/ciite62244.2024.10987583.

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Reports on the topic "AI Talent"

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Aiken, Catherine, James Dunham, and Remco Zwetsloot. Career Preferences of AI Talent. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200012.

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The United States faces increased international competition for top talent in artificial intelligence, a critical component of the American AI advantage. CSET surveyed recent AI PhDs from U.S. universities, offering insights into the academic and career preferences of the AI workforce.
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Toney, Autumn, and Melissa Flagg. U.S. Demand for AI-Related Talent. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200027.

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The U.S. government and industry both see artificial intelligence as a pivotal technology for future growth and competitiveness. What skills will be needed to create, integrate, and deploy AI applications? This data brief analyzes market demand for AI-related jobs to determine their educational requirements, dominant sectors, and geographic distribution.
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Gehlhaus, Diana, and Santiago Mutis. The U.S. AI Workforce: Understanding the Supply of AI Talent. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200068.

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As the United States seeks to maintain a competitive edge in artificial intelligence, the strength of its AI workforce will be of paramount importance. In order to understand the current state of the domestic AI workforce, Diana Gehlhaus and Santiago Mutis define the AI workforce and offer a preliminary assessment of its size, composition, and key characteristics. Among their findings: The domestic supply of AI talent consisted of an estimated 14 million workers (or about 9% of total U.S. employment) as of 2018.
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Aiken, Catherine, James Dunham, and Remco Zwetsloot. Immigration Pathways and Plans of AI Talent. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200013.

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To better understand immigration paths of the AI workforce, CSET surveyed recent PhD graduates from top-ranking AI programs at U.S. universities. This data brief offers takeaways — namely, that AI PhDs find the United States an appealing destination for study and work, and those working in the country plan to stay.
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Cary, Dakota. China’s CyberAI Talent Pipeline. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/2020ca017.

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To what extent does China’s cultivation of talent in cybersecurity and AI matter in terms of competitiveness with other countries? Right now, it seems to have an edge: China’s 11 World-Class Cybersecurity Schools offer more classes on artificial intelligence and machine learning than do the 20 U.S. universities certified as Centers of Academic Excellence in Cyber Operations. This policy brief recommends tracking 13 research grants from the National Science Foundation that attempt to integrate AI into cybersecurity curricula.
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Langenkamp, Max, and Melissa Flagg. AI Hubs: Europe and CANZUK. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200061.

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U.S. policymakers need to understand the landscape of artificial intelligence talent and investment as AI becomes increasingly important to national and economic security. This knowledge is critical as leaders develop new alliances and work to curb China’s growing influence. As an initial effort, an earlier CSET report, “AI Hubs in the United States,” examined the domestic AI ecosystem by mapping where U.S. AI talent is produced, where it is concentrated, and where AI private equity funding goes. Given the global nature of the AI ecosystem and the importance of international talent flows, this
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Olander, Justin, and Melissa Flagg. AI Hubs in the United States. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200006.

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With the increasing importance of artificial intelligence and the competition for AI talent, it is essential to understand the U.S. domestic industrial AI landscape. A new CSET data brief maps where AI talent is produced, where it concentrates, and where AI equity funding goes. This mapping reveals distinct AI hubs emerging across the country, with different growth rates, investment levels, and potential access to talent.
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Zwetsloot, Remco. Keeping Top AI Talent in the United States. Center for Security and Emerging Technology, 2019. http://dx.doi.org/10.51593/20190007.

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Talent is core to U.S. competitiveness in artificial intelligence, and international graduate students are a large source of AI talent for the United States. Retaining them in this country as they transition into the workforce is key. Graduate student retention has historically been a core U.S. strength, but that strength is endangered by recent events.
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Goode, Kayla, Heeu Millie Kim, and Melissa Deng. Examining Singapore’s AI Progress. Center for Security and Emerging Technology, 2023. http://dx.doi.org/10.51593/2021ca014.

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Despite being a small city-state, Singapore’s star continues to rise as an artificial intelligence hub presenting significant opportunities for international collaboration. Initiatives such as fast-tracking patent approval, incentivizing private investment, and addressing talent shortfalls are making the country a rapidly growing global AI hub. Such initiatives offer potential models for those seeking to leverage the technology and opportunities for collaboration in AI education and talent exchanges, research and development, and governance. The United States and Singapore share similar goals
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Huang, Tina, and Zachary Arnold. Immigration Policy and the Global Competition for AI Talent. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20190024.

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Current immigration policies may undermine the historic strength of the United States in attracting and retaining international AI talent. This report examines the immigration policies of four U.S. economic competitor nations—the United Kingdom, Canada, France, and Australia—to offer best practices for ensuring future AI competitiveness.
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