Campus Location
Dallas Campus (Online)
Date of Award
11-2025
Document Type
Dissertation
Department
Organizational Leadership
Degree Name
Doctor of Education
Committee Chair or Primary Advisor
Melissa Atkinson
Second Committee Member or Secondary Advisor
Suzanne Barker
Third Committee Member or Committee Reader
Sonerka Mouton
Abstract
This dissertation explored the experiences of multilingual employees with AI-powered language learning tools in financial and technology firms across the United States. As multilingual communication becomes increasingly vital in the workplace, the integration of artificial intelligence (AI) offers promising support in language acquisition and cross-cultural collaboration. The purpose of this basic qualitative study was to explore how AI-powered language learning tools influence the acquisition and retention of foreign languages of employees within financial and technology firms, how these tools strengthen professional identity and interpersonal communication, and how code-switching facilitated by AI impacts user experience and workplace engagement. Drawing from the theoretical frameworks of situated cognition and constructivism, the study employed semistructured interviews, online observations, and field notes. Eight participants were interviewed who worked in financial and technology firms. Multilingual employees were selected through purposive sampling. Interviews were transcribed and hand-coded using process coding to identify emergent themes across participant experiences. Findings revealed that daily structured engagement with AI tools such as ChatGPT, Duolingo, DeepL, and Google Translate enhanced vocabulary retention, reduced cognitive strain in multilingual interactions, and reinforced user credibility in professional settings. These results provide insight into the evolving role of AI in language learning and offer guidance for implementation in multilingual workplaces.
Keywords: situated cognition, constructivism, language acquisition, AI-powered learning, multilingual workplace, code-switching, professional identity, bilingual cogniti
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Baskar, Iswariya, "Effectiveness of AI-Powered Language Learning Tools in the Workplace" (2025). Digital Commons @ ACU, Electronic Theses and Dissertations. Paper 959.
https://digitalcommons.acu.edu/etd/959