Digital Technologies Research and Applications

Article

AI‑Driven Customer Positioning and Perception: Strategies, Challenges and Insights

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https://doi.org/10.54963/dtra.v4i2.1231
Burra, R., Wu, T., Chang, K., & Huang, C. (2025). AI‑Driven Customer Positioning and Perception: Strategies, Challenges and Insights. Digital Technologies Research and Applications, 4(2), 96–108. https://doi.org/10.54963/dtra.v4i2.1231
Volume 4 Issue 2: September 2025
Copyright (c) 2025 Rajitha Burra, Tai‑Ying Wu, Kirk Chang, Chin‑Fei Huang
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Authors

  • Rajitha Burra

    Royal Docks School of Business and Law, University of East London, London E16 2RD, UK
  • Tai‑Ying Wu

    Graduate Institute of Science Education and Environmental Education, National Kaohsiung Normal University, Kaohsiung 82444, Taiwan
  • Kirk Chang

    Royal Docks School of Business and Law, University of East London, London E16 2RD, UK
  • Chin‑Fei Huang

    Graduate Institute of Science Education and Environmental Education, National Kaohsiung Normal University, Kaohsiung 82444, Taiwan

Received: 13 May 2025; Revised: 25 June 2025; Accepted: 30 June 2025; Published: 23 July 2025

The current research aims to investigate the transformative impact of artificial intelligence (AI) on marketing. AI‑driven marketing strategies are widely utilized in practice but their influence on customers is not always clear, leaving a glaring knowledge gap. Drawing on the Technology Acceptance Model, the current research analyses how AI‑driven marketing strategies influence customer positioning and perception, with a particular emphasis on customer trust, engagement, and relevant ethical considerations. To maximize the ecological validity of data mining and analysis, we collect multi‑layered data from renowned academic platforms, industry reports and consultancy records, in line with the institutional ethical guidelines. Research findings are meaningful in three ways. To begin with, while AI‑driven marketing strategies offer promising tools for enhancing customer engagement, they also raise severe concerns related to transparency and ethics, such as threats surrounding data privacy, fairness, as well as the opacity of AI algorithms in implementation. Next, by comparing AI‑driven and non‑AI‑driven marketing strategies, we can uncover the conditions under which AI promotes trust and improves the customer experience. Finally, research findings have advanced knowledge by providing evidence‑based insights into the mechanisms through which AI affects customer perception. Overall, new research discoveries have benefited both entrepreneurs and marketing professionals, providing sensible insights to policy making (e.g., AI‑driven marketing strategies) and ethical practices (e.g., ethical standards and procedures in marketing). Research limitation and suggestions for future research are discussed.

Keywords:

AI‑Driven Customer Perception Customer Positioning Marketing Strategies Technology Acceptance Model

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