Relevant bibliographies by topics / AI readiness

Contents

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

Academic literature on the topic 'AI readiness'

Author: Grafiati
Published: 19 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "AI readiness"

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Machynska, Nataliia, Nataliya Yaremchuk, Vira Korniat, Yuliia Derkach, Nelya Sirant, and Svitlana Lozynska. "Research of readiness of pedagogical workers for innovations." Revista Amazonia Investiga 11, no. 51 (2022): 50–60. http://dx.doi.org/10.34069/ai/2022.51.03.5.

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The purpose is empirical research of the interdependence of variables and construction of the factor structure of the readiness of pedagogical workers for innovation. Research methods: theoretical analysis and generalization, valid test methods with standardized questionnaires, factor analysis. The structure of readiness of pedagogical workers for innovative pedagogical activity has been determined using ANOVA factor analysis with Varimax rotation. The most significant interdependencies of variables and researched relationships were established at the statistically significant level (p ≤ .01;
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Alnasib, Badiah N. M. "Factors Affecting Faculty Members’ Readiness to Integrate Artificial Intelligence into Their Teaching Practices: A Study from the Saudi Higher Education Context." International Journal of Learning, Teaching and Educational Research 22, no. 8 (2023): 465–91. http://dx.doi.org/10.26803/ijlter.22.8.24.

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Artificial intelligence (AI) has been around for about three decades. However, use of AI in pedagogy on a large scale and examination of its impact on teaching practices in higher education are under-researched topics. This study examined the readiness of 465 faculty members at King Faisal University in Saudi Arabia to integrate AI into their teaching practices as well as the factors influencing that readiness. A 46-item online survey was used to collect data. The results show that the respondents demonstrated an average readiness to integrate AI into their teaching (M = 3.40, SD = 0.841). Sta
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Budiraharjo, Muhammad Husein, Alva Hendi Muhammad, and Kusnawi. "MSME AI Readiness Analysis Using The AIRI Framework." Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) 9, no. 2 (2024): 33–44. http://dx.doi.org/10.20527/jtiulm.v9i2.307.

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AI is expected to become one of the key technologies supporting the development of MSMEs, which represent a major pillar of Indonesia's economy. Successful adoption and implementation of AI require the right strategies, one of which stems from an analysis of a company’s AI readiness. In this study, an AI readiness analysis was conducted using the AIRI framework on six MSMEs from various business sectors. The results of the analysis provided the AI readiness levels of each MSME, along with comparisons to similar industries and to industries of comparable business scale (MSME). The analysis also
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Shonhe, Liah, and Mavis Kolobe. "Glimpse into Botswana’s AI Readiness Landscape." JeDEM - eJournal of eDemocracy and Open Government 15, no. 2 (2023): 37–67. http://dx.doi.org/10.29379/jedem.v15i2.812.

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This study seeks to provide insights into Botswana’s AI readiness landscape. It was achieved by analysing secondary data from the Oxford Insights 2022- Government AI Readiness Index (AIRI). According to the AIRI, Botswana is in position 98, out of 181 countries surveyed. The major drawbacks to successful AI adoption were; a lack of AI strategy, limited capacity to support change, an immature technology sector incapable of supporting innovation, inadequate skills to support AI development, insufficient technological infrastructure to support AI, insufficient data to train AI models, and there a
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Dai, Yun, Ching-Sing Chai, Pei-Yi Lin, Morris Siu-Yung Jong, Yanmei Guo, and Jianjun Qin. "Promoting Students’ Well-Being by Developing Their Readiness for the Artificial Intelligence Age." Sustainability 12, no. 16 (2020): 6597. http://dx.doi.org/10.3390/su12166597.

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This study developed and validated an instrument to measure students’ readiness to learn about artificial intelligence (AI). The designed survey questionnaire was administrated in a school district in Beijing after an AI course was developed and implemented. The collected data and analytical results provided insights regarding the self-reported perceptions of primary students’ AI readiness and enabled the identification of factors that may influence this parameter. The results indicated that AI literacy was not predictive of AI readiness. The influences of AI literacy were mediated by the stud
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Chuyen, Nguyen Thi Hong, and Nguyen The Vinh. "How teachers’ AI readiness affects AI integration: insights from modeling analysis." International Journal of Evaluation and Research in Education (IJERE) 14, no. 2 (2025): 1496. https://doi.org/10.11591/ijere.v14i2.28242.

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<span lang="EN-US">This study examined the dynamic relationships among professional development and training, resources and accessibility, attitudes and perceptions, pedagogical knowledge and expertise, teachers’ artificial intelligence (AI) readiness, and the integration of AI in teaching practices. The study employed a non-random purposive approach and utilized the structural equation modeling (SEM) method. Five hypotheses were meticulously formulated and subsequently subjected to empirical scrutiny, involving a cohort of 224 participants. Data were collected via Google Form and subjec
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Xuan, Pang Yi, Mohamed Ismath Fathima Fahumida, Muhammad Imran Al Nazir Hussain, et al. "Readiness Towards Artificial Intelligence Among Undergraduate Medical Students in Malaysia." Education in Medicine Journal 15, no. 2 (2023): 49–60. http://dx.doi.org/10.21315/eimj2023.15.2.4.

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Artificial intelligence (AI) technology is growing at a fast pace and permeates many aspects of people’s daily lives. Medical students’ inclination towards AI in the medical field increases the probability of successful AI adoption and its value in the medical field. This study was conducted to evaluate medical AI readiness among undergraduate medical students. A cross-sectional study was conducted from March 2022 to April 2022 in a private medical institution in Malaysia. A non-probability purposive sampling method was used to enroll students and a questionnaire was distributed online via Goo
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Manrique, Paul Christian J., and Noel R. Palomares. "EMBRACING THE FUTURE: EXPLORING TEACHERS PERSPECTIVE AND READINESS FOR INTEGRATING ARTIFICIAL INTELLIGENCE (AI) IN MATHEMATICS CLASSROOM IN SELECTED PUBLIC AND PRIVATE SENIOR HIGH SCHOOL." Ignatian International Journal for Multidisciplinary Research 2, no. 5 (2024): 2654–75. https://doi.org/10.5281/zenodo.11393926.

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The study investigated the readiness and perspective of senior high school mathematics teachers in integrating Artificial Intelligence (AI) in their classrooms. It aimed to examine the relationship between teacher demographics, AI familiarity, perspectives, and readiness for AI adoption, identify challenges and barriers, explore potential benefits, and propose interventions. A descriptive-correlational design was employed, involving 37 senior high school mathematics teachers from Quezon City and Marinduque. Data was collected through a survey questionnaire and analyzed using descriptive and in
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Tsumarieva, Natalia, Maksym Hryshchenko, Stanislav Merdov, Volodymyr Hospodarenko, and Dmytro Kyslenko. "The model of training law enforcement officers’ readiness for professional self-fulfillment." Revista Amazonia Investiga 12, no. 63 (2023): 277–88. http://dx.doi.org/10.34069/ai/2023.63.03.26.

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The aim of the study was to determine an effective model of training law enforcement officers’ readiness for professional self-fulfillment taking into account the level of their professional training and the demands of society. The research involved the methods of questionnaire survey, expert evaluations and interviews with the use of focus groups. The obtained data were analysed using the methods of mathematical statistics. According to the results of the factor analysis, motivation, support, ability to manage time, recognition of success and relaxation have the greatest impact on readiness f
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Alshorman, Sameera. "THE READINESS TO USE AI IN TEACHING SCIENCE: SCIENCE TEACHERS' PERSPECTIVE." Journal of Baltic Science Education 23, no. 3 (2024): 432–48. http://dx.doi.org/10.33225/jbse/24.23.432.

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This study aimed to assess the readiness of Jordanian science teachers for integrating Artificial Intelligence (AI) in science education, focusing on their perceptions, challenges, and training needs. A quantitative survey methodology was employed, using a 35-item questionnaire distributed to 136 science teachers in urban Jordan. The questionnaire, developed and refined through expert peer review and a pilot study, encompassed demographics, attitudes towards AI, perceived benefits and challenges of AI in science teaching, self-efficacy in using AI, and behavioural intentions regarding its use.
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Dissertations / Theses on the topic "AI readiness"

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Göransson, Johanna, and Sofi Glas. "AI-READINESS : En kvalitativ fallstudie i skogsindustrin." Thesis, Umeå universitet, Institutionen för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-183674.

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Organizations in all industries have reached a transition point because of the rapid development of digital technology. Digitalization and AI has therefore become the driving force for transformation within today's organizations to remain competitive in the digital era. The forest industry is no exception. However, digital transformation through AI within organizations is synonymous with high complexity and the forestry industry faces unique challenges to overcome because of the industry's traditional approach and the corporate culture that comes with it. This approach creates challenges for t
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Ek, Lina, and Sanna Ström. "Organizational AI Readiness : Evaluating Employee Attitudes and Management Responses." Thesis, Jönköping University, Internationella Handelshögskolan, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53412.

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Background - As a result of the latest advances in artificial intelligence (AI), the world ofbusiness is facing a major transformation where basic organizational principlesare redefined initiating a new era. It is predicted that AI in the coming decadeswill make a significant imprint and organizations aiming to stay at the forefrontcannot afford not to change. AI adoption can bring great benefits to organizationswhere a crucial factor is to establish AI readiness. However, as in any change,different perceptions are raised among employees which can either hinder orfoster organizational AI readi
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Krantz, Oscar. "Beredskap för AI implementering : En fallstudie om beredskapsfaktorer för AI implementeringar på svenska IT-företag." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19939.

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Titel: Beredskap för AI implementering: En fallstudie om beredskapsfaktorer för AI implementeringar på svenska IT-företag Forskningsfråga: Vilka beredskapsfaktorer krävs för implementering av AI på svenska IT-företag? Syfte: Undersöka vilka beredskapsfaktorer svenska IT-företag behöver för att skapa en lyckad AI implementering. Genomförande: Studien genomfördes som en fallstudie. En litteraturstudie utfördes för att sammanfatta tillgänglig och relevant vetenskaplig forskning inom området och fungerade som forskningsöversikt till studien. Datainsamlingen bestod av åtta semistrukturerade intervj
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Stenberg, Louise, and Svante Nilsson. "Factors influencing readiness of adopting AI : A qualitative study of how the TOE framework applies to AI adoption in governmental authorities." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279583.

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Artificial intelligence is increasing in interest and it is creating value to many organizations world-wide. Due to the potential, governmental authorities in Sweden who work with large volumes of text documents are interested in natural language processing models, which is a sub field of AI and have started to incorporate it to their organizations. This study explores and discusses factors that are influential for governmental authorities when adopting AI and highlights ethical aspects which are of importance for the adoption process. This is explored through a literature review which lead to
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Pajany, Peroumal. "AI Transformative Influence: Extending the TRAM to Management Student's AI’s Machine Learning Adoption." Franklin University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=frank1623093426530669.

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Umurerwa, Janviere, and Maja Lesjak. "AI IMPLEMENTATION AND USAGE : A qualitative study of managerial challenges in implementation and use of AI solutions from the researchers’ perspective." Thesis, Umeå universitet, Institutionen för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-187810.

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Artificial intelligence (AI) technologies are developing rapidly and cause radical changes in organizations, companies, society, and individual levels. Managers are facing new challenges that they might not be prepared for. In this work, we seek to explore managerial challenges experienced while implementing and using AI technologies from the researchers’ perspective. Moreover, we explore how appropriate ethical deliberations should be applied when using big data concerning AI and the meaning of understanding or defining it. We describe qualitative research, the triangulation that includes rel
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Books on the topic "AI readiness"

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Turi, Abeba N., and Paulos Teckle, eds. Tech Transformation and AI Readiness. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-73639-1.

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Sciberras, Marvic, and Alexiei Dingli. Investigating AI Readiness in the Maltese Public Administration. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19900-4.

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1935-, Engelmore Robert, ed. Readings from AI magazine: Volumes 1-5. American Association for Artificial Intelligence, 1988.

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1946-, Yang Jwing-Ming, ed. Tai chi secrets of the ancient masters: Selected readings with commentary. YMAA Publication Center, 1999.

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AI Tools for Military Readiness. RAND Corporation, 2021. http://dx.doi.org/10.7249/rra449-1.

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Léveillé, Jasmin, and Peter Schirmer. AI Tools for Military Readiness. RAND Corporation, The, 2021.

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Sciberras, Marvic, and Alexei Dingli. Investigating AI Readiness in the Maltese Public Administration. Springer International Publishing AG, 2023.

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Investigating AI Readiness in the Maltese Public Administration. Springer International Publishing AG, 2024.

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Futures of Artificial Intelligence Through Technology Readiness Levels: AI Technologies Generality Capabilities Technology Readiness TRLs. Independently Published, 2021.

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Carlebach, Ezri. AI Readiness: A Collaborative Design Toolkit for Professional Services Firms. Oxford Brookes University, 2021.

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Book chapters on the topic "AI readiness"

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Sciberras, Marvic, and Alexiei Dingli. "AI-Readiness." In Investigating AI Readiness in the Maltese Public Administration. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19900-4_5.

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Dobrin, Seth. "AI Readiness." In AI iQ for a Human-Focused Future. CRC Press, 2024. http://dx.doi.org/10.1201/9781003486725-9.

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Dobrin, Seth. "Data Readiness." In AI iQ for a Human-Focused Future. CRC Press, 2024. http://dx.doi.org/10.1201/9781003486725-8.

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Dobrin, Seth. "Infrastructure Readiness." In AI iQ for a Human-Focused Future. CRC Press, 2024. http://dx.doi.org/10.1201/9781003486725-7.

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Dobrin, Seth. "Compliance Readiness." In AI iQ for a Human-Focused Future. CRC Press, 2024. http://dx.doi.org/10.1201/9781003486725-11.

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Dobrin, Seth. "Assessing Your Readiness." In AI iQ for a Human-Focused Future. CRC Press, 2024. http://dx.doi.org/10.1201/9781003486725-12.

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Dobrin, Seth. "Generative Artificial Intelligence Readiness." In AI iQ for a Human-Focused Future. CRC Press, 2024. http://dx.doi.org/10.1201/9781003486725-10.

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Sciberras, Marvic, and Alexiei Dingli. "AI Adoption." In Investigating AI Readiness in the Maltese Public Administration. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19900-4_4.

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Schmitz, Anna, Rebekka Görge, Elena Haedecke, Marion Borowski, Adrian Seeliger, and Maximilian Poretschkin. "Towards Formalising AI Readiness of Standards." In Information Technology and Law Series. T.M.C. Asser Press, 2024. https://doi.org/10.1007/978-94-6265-639-0_10.

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AbstractStandards and specifications (henceforth standards) greatly simplify our everyday lives and the economy in many areas. By establishing quality benchmarks and promoting interoperability, they form a key pillar for international trade and competition. As artificial intelligence (AI) emerges as one of the key technologies of the future, two fundamental questions arise regarding standards: (i) What new standards must be developed specifically for AI? (ii) What modifications to existing standards are necessary to fully leverage the potential of AI? The first question is being addressed acti
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Horvat, Djerdj, and Heidi Heimberger. "AI Readiness: An Integrated Socio-technical Framework." In Proceedings of the 11th International Conference on Production Research – Americas. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36121-0_69.

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Conference papers on the topic "AI readiness"

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Salman, Husain, Muhammad Aliif, Roliana Ibrahim, and Jamilah Mahmood. "Technology Readiness for Generative AI Among Academic Researchers." In 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT). IEEE, 2024. https://doi.org/10.1109/3ict64318.2024.10824523.

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Zine, Mohamed, Fouzi Harrou, Mohamed Terbeche, and Ying Sun. "Enhancing E-Learning Readiness Assessment Using XGBoost: An Explainable AI Approach." In 2024 International Conference of the African Federation of Operational Research Societies (AFROS). IEEE, 2024. https://doi.org/10.1109/afros62115.2024.11037023.

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Kochkina, Nataliia, Iryna Andriushchenko, and Gianluca Gatto. "Strategic AI Adoption: Economic Impact, Case Studies from Handy.ai, and Industry Readiness." In 2024 IEEE International Conference on Artificial Intelligence & Green Energy (ICAIGE). IEEE, 2024. https://doi.org/10.1109/icaige62696.2024.10776631.

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Bandara, R. B. M. T., and Ruwan Wickramarachchi. "Developing an AI Readiness Model for Software Project Management: A Thematic Analysis." In 2025 5th International Conference on Advanced Research in Computing (ICARC). IEEE, 2025. https://doi.org/10.1109/icarc64760.2025.10962923.

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Alnajjar, Mohammed, Khalid Alnajjar, and Mika Hämäläinen. "Threefold model for AI Readiness: A Case Study with Finnish Healthcare SMEs." In Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities. Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.nlp4dh-1.41.

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Madibo, Carol Thato, Rene Van Eck, and Fhatuwani Vivian Mapande. "Readiness for Adoption Model of AI-based chatbots in Academic Institutions: A Review." In 2024 4th International Multidisciplinary Information Technology and Engineering Conference (IMITEC). IEEE, 2024. https://doi.org/10.1109/imitec60221.2024.10850987.

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Kunekar, Pankaj, Om Thigale, Mansi Waghmode, Shreyash Telsang, Pranoti Shinde, and Manthan Thakare. "AI-Driven Alumni Networking Platform for Enhanced Student-Alumni Engagement and Career Readiness." In 2025 International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI). IEEE, 2025. https://doi.org/10.1109/icmsci62561.2025.10894387.

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Azemi, Asad. "Navigating the Dual Edges of AI in Engineering Education: Opportunities, Challenges, and Societal Readiness." In 2024 IEEE Frontiers in Education Conference (FIE). IEEE, 2024. https://doi.org/10.1109/fie61694.2024.10893083.

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Ghazal, Mohammed, Taimur Hassan, Jawad Yousaf, et al. "Diabetic Retinopathy Detection and Grading AI for Mobile and Hand-held Devices: A Readiness Survey." In 2024 11th International Conference on Future Internet of Things and Cloud (FiCloud). IEEE, 2024. http://dx.doi.org/10.1109/ficloud62933.2024.00044.

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Ngulube, Beatrice. "FINAL YEAR PRESERVICE ECONOMICS TEACHERS’ ARTIFICIAL INTELLIGENCE (AI) READINESS: A CASE OF A UNIVERSITY OF TECHNOLOGY IN SOUTH AFRICA." In 17th International Conference on Education and New Learning Technologies. IATED, 2025. https://doi.org/10.21125/edulearn.2025.1511.

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Reports on the topic "AI readiness"

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Quimba, Francis Mark, Neil Irwin Moreno, and Alliah Mae Salazar. Readiness for AI Adoption of Philippine Business and Industry: The Government's Role in Fostering Innovation- and AI-Driven Industrial Development. Philippine Institute for Development Studies, 2024. https://doi.org/10.62986/dp2024.35.

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This paper examines the current state of artificial intelligence (AI) adoption in Philippine businesses and industries, analyzing the barriers to adoption and evaluating the government's role in fostering AI-driven industrial development. Through an analysis of various AI readiness indices and case studies, the research finds that while basic digital infrastructure is widespread, with 90.8 percent of establishments having computers and 81 percent having internet access, advanced technology adoption remains limited. Only 14.9 percent of firms use AI technologies, with adoption concentrated in u
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Konaev, Margarita, Husanjot Chahal, Ryan Fedsiuk, Tina Huang, and Ilya Rahkovsky. U.S. Military Investments in Autonomy and AI: A Strategic Assessment. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20190044.

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This brief examines how the Pentagon’s investments in autonomy and AI may affect its military capabilities and strategic interests. It proposes that DOD invest in improving its understanding of trust in human-machine teams and leverage existing AI technologies to enhance military readiness and endurance. In the long term, investments in reliable, trustworthy, and resilient AI systems are critical for ensuring sustained military, technological, and strategic advantages.
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Tjondronegoro, Dr Dian Wirawan. Navigating AI risks for sustainable productivity and resilience. Asian Productivity Organization, 2025. https://doi.org/10.61145/occa6400.

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In Navigating AI Risks for Sustainable Productivity and Resilience, Dr. Dian Wirawan Tjondronegoro presents a structured framework for integrating artificial intelligence (AI) into organizations while mitigating associated risks. The report outlines three interdependent frameworks—EPIC (Education, Partnership, Infrastructure, Community), TOAST (Trustworthy, Optimised, Adaptable, Socio-Technological), and RAIIF (Responsible AI Implementation Framework)—which collectively support AI readiness, responsible governance, and continuous adaptation. Emphasizing the socio-technical nature of AI, the pu
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Readiness assessment methodology. A tool of the Recommendation on the Ethics of Artificial Intelligence. UNESCO, 2023. http://dx.doi.org/10.54678/yhaa4429.

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The Readiness assessment methodology (RAM) is a macro level instrument that will help countries understand where they stand on the scale of preparedness to implement AI ethically and responsibly for all their citizens, in so doing highlighting what institutional and regulatory changes are needed. The outputs of the RAM will help UNESCO tailor the capacity building efforts to the needs of specific countries. Capacity here refers to the ability to assess AI systems in line with the Recommendation, the presence of requisite and appropriate human capital, and infrastructure, policies, and regulati
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Ethical impact assessment. A tool of the Recommendation on the Ethics of Artificial Intelligence. UNESCO, 2023. http://dx.doi.org/10.54678/ytsa7796.

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The Recommendation on the Ethics of AI provides a framework to ensure that AI developments align with the promotion and protection of human rights and human dignity, environmental sustainability, fairness, inclusion and gender equality. It underscores that these goals and principles should inform technological developments in an ex-ante manner. To support effective implementation, UNESCO developed two instruments, the Readiness Assessment Methodology (RAM) and the Ethical Impact Assessment (EIA). The EIA is proposed to procurers of AI systems, as this is one of the main channels in which algor
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