Trust in AI translation: Reception and adoption among Jordanian business professionals
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Abstract
Artificial intelligence (AI) has become increasingly integrated into multilingual professional communication, particularly in translation. This study examines the perceptions, adoption patterns, and future intentions of 2,500 business professionals across various sectors in Jordan regarding AI-powered translation tools. Data were collected using a 28-item questionnaire covering seven dimensions: trust in human versus AI translators, perceived AI accuracy and reliability, adoption and frequency of use, perceived usefulness, organizational policy and support, ethical concerns, and future adoption intentions. The findings revealed a significant negative correlation between perceived AI accuracy and reliability and comparative trust in human translators (r = −.339, p < .001), alongside a positive correlation with future adoption intentions (r = .453, p < .001). Organizational policy and support were negatively associated with ethical concerns (r = −.411, p < .001). No significant differences in perceived AI accuracy and reliability were found based on formal AI training (p = .057). However, AI translation adoption varied significantly across sectors, with higher adoption in Technology and Marketing/Advertising than in Legal Services and Healthcare/Pharmaceuticals. Larger organizations also reported stronger institutional policy and support. Overall, the findings suggest that growing reliance on AI translation does not eliminate the need for human linguistic expertise, particularly in sensitive professional contexts. The study highlights the importance of organizational support and ethical governance in promoting the responsible integration of AI translation into professional practice.
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Afroogh, S., Akbari, A., Malone, E., Kargar, M., & Alambeigi, H. (2024). Trust in AI: progress, challenges, and future directions. Humanities and Social Sciences Communications, 11(1), 1568.
Al-Billeh, T., Khashashneh, T., Alhendi, N. I., Al-Shabatat, M., & Al-Billeh, G. (2026). The Role of Artificial Intelligence in Constitutional Adjudication: Comparative Insights from General Judicial Practice. Access to Justice in Eastern Europe, 9(3), 377–421.
Al-Jarf, R. (2025). Translation of English and Arabic “sleep” terms and formulaic expressions by Artificial Intelligence: A comparison of Copilot and DeepSeek. International Journal of Linguistics, Literature and Translation, 8(11), 95-108.
Al Khaldi, I., Khawaldeh, A. M., Alhusban, F. M., Altarawneh, S. M. D., & Al-Wreikat, E. I. (2025). Arbitration in cyber security disputes: Sci-fi or future reality? Brazilian Journal of Law & International Relations/Relações Internacionais no Mundo, 4(50), 1-17.
AlAfnan, M. A. (2025). Artificial intelligence and language: Bridging Arabic and English with technology. Journal of Ecohumanism, 4(1), 240-256.
Almubasher, Z. M., Abu-Rahme, M. O., Abu-Mallouh, R., Al-Hawawsheh, S. H., Obeid, M. A., Dabash, A. t. M. K., & AL-Salman, A. M. (2026). Language teachers’ perspectives on artificial intelligence in education: administrative and pedagogical standards in Jordan. Research Journal in Advanced Humanities, 7(2), 1-15.
Asrifan, A., Nursyam, N., & Aini, N. (2025). Lifelong Learning as a Lever for Translator Career Longevity: Strategies and Applications. In Cutting-Edge Approaches in Translator Education and Pedagogy (pp. 93-120): IGI Global Scientific Publishing.
Boluwatife, O. S. (2025). The Impact of AI on the Translation Industry.
Bowker, L. (2020). Translation technology and ethics. In The Routledge handbook of translation and ethics (pp. 262-278): Routledge.
Burgos, D., Branch, J. W., Tlili, A., Stracke, C. M., & de la Higuera, C. (2024). Artificial Intellience, Digital Transformation, and Education, as a Combined Contribution to Society. In Radical Solutions for Artificial Intelligence and Digital Transformation in Education: Utilising Disruptive Technology for a Better Society (pp. 3-13): Springer.
Castilho, S., Moorkens, J., Gaspari, F., Calixto, I., Tinsley, J., & Way, A. (2017). Is neural machine translation the new state of the art?
Clark, D. (2020). Artificial intelligence for learning: How to use AI to support employee development: Kogan Page Publishers.
Cronin, I. (2024). Understanding generative AI business applications. Apress eBooks.
Drugan, J. (2013). Quality in professional translation: Assessment and improvement (Vol. 9): A&C Black.
Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information systems frontiers, 24(5), 1709-1734.
Hadla, L. S., Hailat, T. M., & Al-Kabi, M. N. (2014). Evaluating Arabic to English machine translation. International Journal of Advanced Computer Science and Applications, 5(11).
Hammouri, D. M. (2025). The role of artificial intelligence in generating Arabic neologisms: A study of gaming localization. Research Journal in Advanced Humanities, 6(4), 1-15.
Hariri, W. (2023). Unlocking the potential of ChatGPT: A comprehensive exploration of its applications, advantages, limitations, and future directions in natural language processing. arXiv preprint arXiv:2304.02017.
Jiménez-Crespo, M. A. (2013). Translation and web localization: Routledge.
Jiménez-Crespo, M. A. (2025). Human-centered AI and the future of translation technologies: What professionals think about control and autonomy in the AI era. Information, 16(5), 387.
Johnsen, M. (2025). Developing AI Applications With Large Language Models: Maria Johnsen.
Kaggwa, S., Eleogu, T. F., Okonkwo, F., Farayola, O. A., Uwaoma, P. U., & Akinoso, A. (2024). AI in decision making: transforming business strategies. International Journal of Research and Scientific Innovation, 10(12), 423-444.
Khurana, D., Koli, A., Khatter, K., & Singh, S. (2023). Natural language processing: state of the art, current trends and challenges. Multimedia tools and applications, 82(3), 3713-3744.
Koehn, P. (2010). Statistical machine translation (Vol. 11): Cambridge University Press Cambridge.
Kumar, A., & Nagar, D. K. (2024). AI-based language translation and interpretation services: Improving accessibility for visually impaired students. In As the editors of Transforming Learning: The Power of Educational (pp. 178).
Leslie, D. (2019). Understanding artificial intelligence ethics and safety. arXiv preprint arXiv:1906.05684.
Liedtke, C. A. (2025). Artificial Intelligence for Strategic Improvement.
Megdadi, S., Almahasees, Z., Al-Harahsheh, A., Al Rousan, R., Al-Taher, M. A., & Husienat, I. (2026). Translating food idioms across the English-Arabic language divide: A com-parative study of human translators, ChatGPT, and Gemini. Research Journal in Advanced Humanities, 7(2), 1-15.
Mihalache, I. (2020). Human and non-human crossover: Translators partnering with digital tools. In When translation goes digital: Case studies and critical reflections (pp. 19-43): Springer.
Mohamed, Y. A., Khanan, A., Bashir, M., Mohamed, A. H. H., Adiel, M. A., & Elsadig, M. A. (2024). The impact of artificial intelligence on language translation: a review. IEEE access, 12, 25553-25579.
Moniz, H., & Escartín, C. P. (2023). Towards Responsible Machine Translation. Ethical and Legal Considerations in Machine Translation. Cham: Springer.
Murire, O. T. (2024). Artificial intelligence and its role in shaping organizational work practices and culture. Administrative Sciences, 14(12), 316.
Mustapha, R., & Malkan, S. N. A. (2025). Maqasid al-shariah in the AI era: Balancing innovation and Islamic ethical principles. International Journal of Islamic Theology & Civilization (E-ISSN-3009-1551), 3(3), 1-21.
Mutashar, M. K. (2024). Navigating Ethics in AI-Driven Translation for a Human-Centric Future: Menavigasi Etika dalam Penerjemahan Berbasis AI untuk Masa Depan yang Berpusat pada Manusia. Academia Open, 9(2), 10.21070/acopen. 21079.22024. 29407-21010.21070/acopen. 21079.22024. 29407.
Nurminen, M., & Koponen, M. (2020). Machine translation and fair access to information. Translation Spaces, 9(1), 150-169.
Orbán, F., & Stefkovics, Á. (2025). Trust in artificial intelligence: a survey experiment to assess trust in algorithmic decision-making. AI & SOCIETY, 40(6), 4955-4969.
Owolabi, O. S., Uche, P. C., Adeniken, N. T., Ihejirika, C., Islam, R. B., Chhetri, B. J. T., & Jung, B. (2024). Ethical implication of artificial intelligence (AI) adoption in financial decision making. Computer and Information Science, 17(1), 1-49.
Rajagopal, N. K., Qureshi, N. I., Durga, S., Ramirez Asis, E. H., Huerta Soto, R. M., Gupta, S. K., & Deepak, S. (2022). Future of business culture: An artificial intelligence‐driven digital framework for organization decision‐making process. Complexity, 2022(1), 7796507.
Rezaei, M., Pironti, M., & Quaglia, R. (2025). AI in knowledge sharing, which ethical challenges are raised in decision-making processes for organisations? Management Decision, 63(10), 3369-3388.
Rivas Ginel, M. I., & Moorkens, J. (2025). Translators’ trust and distrust in the times of GenAI. Translation Studies, 18(2), 283-299.
Rukba, R. A., Awaisheh, S., Al-Hobabseh, W., Al-Khalaileh, L., Hmaidan, R., Althunibat, A., . . . Abdelrahman, A. (2025). Balancing efficiency and ethics in public administration: The role of artificial intelligence in administrative law of the Middle East. Research Journal in Advanced Humanities, 6(4), 1-15.
Saba, D., Sahli, Y., & Hadidi, A. (2020). The role of artificial intelligence in company’s decision making. In Enabling AI Applications in Data Science (pp. 287-314): Springer.
Tahmasbi, N., Rastegari, E., & Truong, M. (2025). A conceptual model of trust in generative AI systems.
Torfi, A., Shirvani, R. A., Keneshloo, Y., Tavaf, N., & Fox, E. A. (2020). Natural language processing advancements by deep learning: A survey. arXiv preprint arXiv:2003.01200.
Van der Meer, J. (2020). Translation technology–past, present and future. The Bloomsbury companion to language industry studies, 1, 285-310.
Zaki, M. Z., & Ahmed, U. (2024). Bridging linguistic divides: The impact of AI-powered translation systems on communication equity and inclusion. Journal of translation and language studies, 5(2), 20–30