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Article published In: Digital Translation
Vol. 13:1 (2026) ► pp.29–59

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Transcreation and AI in global marketing

A comparative case study of two telecom websites

 | Independent Scholar
ORCiD logo with link | University of Granada
ORCiD logo with link | University of Granada
Published online: 17 October 2025
DOI logo with link
https://doi.org/10.1075/dt.25009.aul
Abstract
This study investigates transcreation in global marketing through a comparative case study of selected sections of Apple’s and Sunstech’s multilingual websites (English<>Spanish). Using the FACT framework, it evaluates content adaptation, cultural localization, and linguistic strategies. Apple employs a hybrid strategy, blending standardization and transcreation, maintaining structural consistency while adapting key visual and textual elements for cultural relevance. Sunstech, however, relies heavily on standardization, with translation deficiencies affecting its cultural and linguistic resonance. The study also explores AI’s role in transcreation, highlighting its efficiency in handling large volumes of content. However, AI-generated translations often lack cultural nuance and creative adaptation, requiring human intervention to ensure cultural and contextual appropriateness. Ultimately, the study advocates for a hybrid transcreation approach that combines technology with human creativity, enhancing global brand communication and positioning in increasingly diverse and competitive markets.
Article outline
  • 1.Introduction
  • 2.Theoretical framework
    • 2.1Transcreation in global marketing: Concept and relevance
    • 2.2Localization and transcreation: Complementary practices in marketing
    • 2.3AI in translation
  • 3.Methodology
    • 3.1Sample selection
    • 3.2Tools and analytical techniques
  • 4.Results and discussion
    • 4.1The case of Apple
      • 4.1.1Indicators with the highest values
      • 4.1.2Indicators with the lowest values
    • 4.2The case of Sunstech
      • 4.2.1Indicators with the highest values
      • 4.2.2Indicators with the lowest values
    • 4.3Application of AI in the Sunstech case study
  • 5.Conclusions
  • References
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