The Role of Artificial Intelligence in Integrated Marketing Communications: An Evaluation of Pharmaceutical Retail Firms in Nairobi County, Kenya
DOI:
https://doi.org/10.47604/ejbsm.3729Keywords:
Artificial Intelligence, Integrated Marketing Communication, Pharmaceutical Retail, IMC IntegrationAbstract
Purpose: This study examined the role of AI in enhancing IMC among pharmaceutical retail firms in Nairobi City County, Kenya. This is informed by how Artificial Intelligence (AI) is increasingly reshaping pharmaceutical marketing by enabling data driven decision making, personalization, and multichannel communication integration globally but empirical evidence on its role in Integrated Marketing Communication (IMC) within pharmaceutical retail contexts in Kenya remains limited.
Methodology: A mixed-method design was adopted, combining survey data from 261 usable responses (89.7% response rate) drawn from 291 sampled pharmacies with systematic analysis of peer-reviewed literature, industry reports, and policy and regulatory frameworks. Descriptive, correlation, and regression analyses were used alongside thematic analysis of qualitative data.
Findings: Findings indicate moderate but growing AI adoption, with automation and mobile-based tools being the most widely implemented, while predictive analytics and personalization remain less developed. IMC practices were found to be mobile-driven but partially fragmented, with promotional integration lagging behind other dimensions. Correlation results show strong positive relationships between AI and IMC dimensions (r = 0.42–0.73), while regression analysis confirms that AI significantly predicts IMC performance (R² = 0.55–0.66). Qualitative findings further reveal that AI enhances communication efficiency and consistency but is constrained by system fragmentation, limited data maturity, and strict pharmaceutical regulatory frameworks. Overall AI is a critical enabler of IMC in pharmaceutical retail firms; however, its impact is moderated by organizational and regulatory constraints.
Unique Contribution to Theory, Practice and Policy: The study contributes to theory by proposing a transitional AI–IMC maturity model, where AI is operational and fully strategic in driving integrated communication systems and by extending IMC, Technology Acceptance Model (TAM), and Customer Relationship Management (CRM) frameworks through the integration of AI as a structural enabler. Practically, it highlights the need for system integration, investment in data capabilities, and regulatory alignment. Policy implications emphasize balanced regulatory frameworks that support innovation while ensuring ethical pharmaceutical communication.
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References
Alice, O., & Ebuka, N. (2024). Artificial intelligence adoption and customer engagement in African emerging markets. Journal of African Digital Transformation, 6(2), 45–62.
Angalia, J. (2017). Integrated marketing communication practices and organizational performance: Evidence from the beverage industry in Kenya. African Journal of Business Management, 11(4), 98–110.
Bansal, P. (2026). Artificial intelligence in pharmaceutical marketing: Enhancing targeting and personalization. International Journal of Pharmaceutical Marketing, 14(1), 22–38.
Chaffey, D., & Ellis-Chadwick, F. (2022). Digital marketing: Strategy, implementation and practice (8th ed.). Pearson.
Chatterjee, S., Rana, N. P., & Dwivedi, Y. K. (2023). Artificial intelligence and customer relationship management: Enhancing multichannel engagement in healthcare retail. Industrial Marketing Management, 112, 45–58. https://doi.org/10.xxxx/xxxx
Deloitte. (2024). AI in healthcare and marketing transformation report. Deloitte Insights.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2023). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 69, 102456.
Godday, S. (2019). Marketing strategies and organizational performance in Nigerian consumer goods firms. Journal of African Marketing Studies, 5(3), 77–91.
GSMA. (2024). The mobile economy: Africa 2024 report. GSMA Intelligence.
Jain, R., & Kumar, S. (2024). Artificial intelligence in healthcare marketing: Opportunities and challenges. Journal of Health Informatics, 10(1), 15–30.
Kenya AI. (2024). Artificial intelligence policy and innovation framework for Kenya. Government of Kenya.
Kenya Ministry of ICT. (2019). Digital economy blueprint: Powering Kenya’s transformation. Government of Kenya.
Kliatchko, J. (2020). Revisiting the IMC construct: A revised definition and framework. Journal of Marketing Communications, 26(1), 1–20.
Kliatchko, J., & Schultz, D. (2022). Integrated marketing communications: The evolution of IMC in the digital age. Journal of Advertising Research, 62(3), 245–260.
Kumar, V., & Anand, A. (2025). Artificial intelligence in pharmaceutical marketing: Adoption, benefits, and challenges. Journal of Marketing Analytics, 13(2), 88–104.
Lacave, C. (2024). Artificial intelligence and healthcare transformation in Kenya. East African Health Journal, 18(2), 33–47.
McKinsey Global Institute. (2021). The state of AI in 2021: Global survey results. McKinsey & Company.
OECD. (2023). Artificial intelligence in healthcare systems: Opportunities and challenges for SMEs. OECD Publishing.
Okok, R., Deya, J., & Rotich, G. (2023). Marketing capabilities and firm performance in Kenya’s healthcare sector. Journal of African Business Research, 9(2), 112–129.
Onyango, P. (2020). Technology adoption and organizational performance in Kenya’s service sector. African Journal of Management, 6(1), 55–70.
Payne, A., & Frow, P. (2005). A strategic framework for customer relationship management. Journal of Marketing, 69(4), 167–176.
Payne, A., Frow, P., & Eggert, A. (2021). The evolution of CRM: Customer engagement in the digital era. European Journal of Marketing, 55(3), 657–679.
Pharmacy and Poisons Board (PPB). (2023). Guidelines for pharmaceutical marketing and advertising in Kenya. Government of Kenya.
Pharmacy and Poisons Board (PPB). (2024). Kenya pharmaceutical sector annual report. Government of Kenya.
SAP Africa. (2024). Digital transformation and AI adoption in Africa’s SMEs. SAP SE.
Schultz, D. E., & Schultz, H. F. (2004). IMC: The next generation. McGraw-Hill.
Silcox, C., et al. (2024). Artificial intelligence adoption in African healthcare systems: Trends and barriers. Health Policy and Technology, 13(1), 100–115.
Tira, J., & Kihara, P. (2025). Artificial intelligence adoption and healthcare performance in Nairobi. Kenya Journal of Health Systems, 12(1), 19–34.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2022). Unified theory of acceptance and use of technology: A synthesis and future directions. MIS Quarterly, 46(1), 1–42.
Wanjiku, M. (2025). Integrated marketing communication and firm performance in pharmaceutical retail firms in Nairobi. Journal of Business and Health Marketing, 7(1), 44–60.
Wanjiku, M., & Maina, P. (2025). Customer retention challenges in Kenya’s pharmaceutical retail sector. African Journal of Pharmaceutical Management, 8(2), 77–93.
World Health Organization. (2023). Ethical marketing practices in healthcare systems. WHO Press.
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Copyright (c) 2026 Winnie Njeru, Jesse Kang’ethe Mukuria
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