Exploring the Impact of Artificial Intelligence on Customer Experience Personalization and Marketing Strategy Optimization in Digital Marketing: An Empirical Analysis.

Daniel  Owusu-Mensah; Philip Adu Sarfo; Gideon Appiah  Kusi

doi:10.51903/jmi.v4i2.242

Authors

Daniel Owusu-Mensah The Katz School of Science and Health at Yeshiva University, New York, NY 10016, United States https://orcid.org/0000-0002-6145-3105
Philip Adu Sarfo School of Management, Zhengzhou University, Zhengzhou, China https://orcid.org/0000-0002-4082-4341
Gideon Appiah Kusi School of Business and Justice Studies, Utica University, Utica NY, 13502, U.S.A https://orcid.org/0000-0002-0406-8358

DOI:

https://doi.org/10.51903/jmi.v4i2.242

Keywords:

Artificial Intelligence (AI), Customer Experience Personalization, Digital Marketing, Ethical and Privacy Concerns, Marketing Strategy Optimization

Abstract

This study explores the transformative role of Artificial Intelligence (AI) in enhancing customer experience personalization (CEP) and optimizing marketing strategies (MSO) within digital marketing environments. Grounded in the Technology Acceptance Model (TAM), the research incorporates ethical and privacy concerns (EC) as moderating factors influencing AI adoption and its effectiveness. Using survey data from marketing professionals across diverse industries, the study employs Structural Equation Modeling (SEM) to analyze complex relationships among AI use, CEP, MSO, and marketing outcomes. The findings reveal that AI significantly improves customer engagement and marketing performance by enabling tailored interactions, data-driven segmentation, and campaign optimization. Moreover, ethical and privacy concerns positively moderate these effects, underscoring the necessity of responsible AI practices in sustaining consumer trust and regulatory compliance. By offering empirical insights into the interplay between AI, personalization, strategy, and ethics, this study contributes to both theoretical development and practical guidance for businesses navigating digital transformation. The research highlights AI’s strategic potential in creating sustainable competitive advantage while advocating for ethical safeguards in technology-driven marketing.

References

Adu Sarfo, P., Zhang, J., Nyantakyi, G., Lassey, F. A., Bruce, E., & Amankwah, O. (2024). Influence of Green Human Resource Management on firm’s environmental performance: Green Employee Empowerment as a mediating factor. Plos one, 19(4), e0293957. https://doi.org/10.1371/journal.pone.0293957

Appiah, A., Zhang, J., Mintah, C., Ofori, E. K., Sarfo, P. A., Alemu, T., Abbas, S., & Jia, H. (2025). Knowledge as the Engine: Transforming Healthcare Delivery Through Information and Communications Technology Applying a Sustainable Development Framework. Sustainable Development. https://doi.org/10.1002/sd.3457

Arun Kumar, B. (2021). AI-based digital marketing strategies—a review. Inventive Computation and Information Technologies: Proceedings of ICICIT 2020, 957-969. https://doi.org/10.1007/978-981-33-4305-4_70

Bhuiyan, M. S. (2024). The role of AI-Enhanced personalization in customer experiences. Journal of Computer Science and Technology Studies, 6(1), 162-169. https://doi.org/10.32996/jcsts.2024.6.1.17

Binns, R. (2018). Algorithmic accountability and public reason. Philosophy & technology, 31(4), 543-556. https://doi.org/10.1007/s13347-017-0263-5

Bruce, E., Shurong, Z., Amoah, J., Egala, S. B., Sarfo, P. A., Baidoo, B. E., Darko, D. A., Ailing, L., & Yongxing, Y. (2025). Examining the impact of social media usage on start-ups performance: Mediating role of brand image. Plos one, 20(5), e0320133. https://doi.org/10.1371/journal.pone.0320133

Chauhan, S., & Thapliyal, S. (2025). Role of AI Tools in Evaluating Brand Performance. In Strategic Brand Management in the Age of AI and Disruption (pp. 53-80). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9461-8.ch003

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024). Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. Asia Pacific Journal of Management, 41(2), 745-783. https://doi.org/10.1007/s10490-023-09871-y

Clark, L. A., & Watson, D. (2019). Constructing validity: New developments in creating objective measuring instruments. Psychological assessment, 31(12), 1412. https://doi.org/10.1037/pas0000626

Daqar, M. A. A., & Smoudy, A. K. (2019). The role of artificial intelligence on enhancing customer experience. International Review of Management and Marketing, 9(4), 22. https://doi.org/10.32479/irmm.8166

Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42. https://doi.org/10.1007/s11747-019-00696-0

Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129, 961-974. https://doi.org/10.1016/j.jbusres.2020.08.024

Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. https://doi.org/10.1016/j.rmal.2022.100027

Hair Jr, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101-110. https://doi.org/10.1016/j.jbusres.2019.11.069

Hassan, A. (2021). The usage of artificial intelligence in digital marketing: A review. Applications of Artificial Intelligence in Business, Education and Healthcare, 357-383. https://doi.org/10.1007/978-3-030-72080-3_20

Immadisetty, A. (2025). Dynamic Pricing Strategies in Retail: Leveraging Real-Time Data Analytics for Competitive Advantage. Journal of Recent Trends in Computer Science and Engineering, 13(1), 53-65. https://doi.org/10.70589/JRTCSE.2025.13.1.8

Kacar, M. (2023). Application of AI in customer experience management. In Marketing and Sales Automation: Basics, Implementation, and Applications (pp. 409-430). Springer. https://doi.org/10.1007/978-3-031-20040-3_26

Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford publications. https://doi.org/10.15353/cgjsc.v1i1.3787

Konda, R. (2025). AI-driven customer support: Transforming user experience and operational efficiency. International Journal on Science and Technology, 16(1). https://doi.org/10.71097/ijsat.v16.i1.2600

Kopalle, P. K., Gangwar, M., Kaplan, A., Ramachandran, D., Reinartz, W., & Rindfleisch, A. (2022). Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities. International Journal of Research in Marketing, 39(2), 522-540. https://doi.org/10.1016/j.ijresmar.2021.11.002

Kumar, D., & Suthar, N. (2024). Ethical and legal challenges of AI in marketing: an exploration of solutions. Journal of Information, Communication and Ethics in Society, 22(1), 124-144. https://doi.org/10.1108/JICES-05-2023-0068

Kumar, V., Ashraf, A. R., & Nadeem, W. (2024). AI-powered marketing: What, where, and how? International Journal of Information Management, 77, 102783. https://doi.org/10.1016/j.ijinfomgt.2024.102783

Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM computing surveys (CSUR), 54(6), 1-35. https://doi.org/10.1145/3457607

Paschen, J., Wilson, M., & Ferreira, J. J. (2020). Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel. Business Horizons, 63(3), 403-414. https://doi.org/10.1016/j.bushor.2020.01.003

Peruchini, M., da Silva, G. M., & Teixeira, J. M. (2024). Between artificial intelligence and customer experience: a literature review on the intersection. Discover Artificial Intelligence, 4(1), 4. https://doi.org/10.1007/s44163-024-00105-8

Phudech, P. (2024). AI and smart customer services: Revolutionizing the customer experience. Journal of Social Science and Multidisciplinary Research (JSSMR), 1(3), 1-20.

Rust, R. T. (2020). The future of marketing. International Journal of Research in Marketing, 37(1), 15-26. https://doi.org/10.1016/j.ijresmar.2019.08.002

Shanmugam, G., Rajendran, D., Thanarajan, T., Murugaraj, S. S., & Rajendran, S. (2023). Artificial Intelligence as a Catalyst in Digital Marketing: Enhancing Profitability and Market Potential. Ingénierie des Systèmes d'Information, 28(6). https://doi.org/10.18280/isi.280620

Siva Shankar, S., Hung, B. T., Chakrabarti, P., Chakrabarti, T., & Parasa, G. (2024). A novel optimization based deep learning with artificial intelligence approach to detect intrusion attack in network system. Education and Information Technologies, 29(4), 3859-3883. https://doi.org/10.1007/s10639-023-11885-4

Song, J., Munyinda, M., & Adu Sarfo, P. (2025). Examining the impact of risk management practices on sustainable project performance in the construction industry: the role of stakeholder engagement. Frontiers in Built Environment, 11, 1575827. https://doi.org/10.3389/fbuil.2025.1575827

Subhashree, M. S. (2023). AI in marketing: The transformation of customer engagement strategies. Journal of the Asiatic Society of Mumbai, XCVI (34). https://doi.org/10.38124/ijisrt/25jun260

Tasnim, K., Abdullah, M. S., Karim, M. Z., & Hasan, R. (2025). AI-Driven Innovation, Privacy Issues, and Gaining Consumer Trust: The Future of Digital Marketing. Business & Social Sciences, 3(1), 1-7. https://doi.org/10.25163/business.3110212

Vashishth, T. K., Sharma, K. K., Kumar, B., Chaudhary, S., & Panwar, R. (2024). Enhancing customer experience through AI-enabled content personalization in e-commerce marketing. Advances in digital marketing in the era of artificial intelligence, 7-32. https://doi.org/10.1201/9781003450443‑2

Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002. https://doi.org/10.1016/j.jjimei.2020.100002

Voigt, P., & Von dem Bussche, A. (2017). The eu general data protection regulation (gdpr). A practical guide, 1st ed., Cham: Springer International Publishing, 10(3152676), 10-5555. https://doi.org/10.1007/978-3-319-57959-7

Wen, L., Lin, W., & Guo, M. (2022). Study on optimization of marketing communication strategies in the era of artificial intelligence. Mobile Information Systems, 2022(1), 1604184. https://doi.org/10.1155/2022/1604184

Wilson, G., Johnson, O., & Brown, W. (2024). The Impact of Artificial Intelligence on Digital Marketing Strategies. Journal of Digital Marketing, 15(3), 112-128. https://doi.org/10.20944/preprints202408.0276.v1

Wilson, M. (2023). Constructing measures: An item response modeling approach. Routledge. https://doi.org/10.4324/9781003286929

Wong, L.-W., Tan, G. W.-H., Ooi, K.-B., & Dwivedi, Y. (2024). The role of institutional and self in the formation of trust in artificial intelligence technologies. Internet Research, 34(2), 343-370. https://doi.org/10.1108/INTR-07-2021-0446