Keywords:
Trust in AI
Perceived service quality
User satisfaction
Chabots
Virtual Assistants
Emerging Economies

  • Abstract

    Artificial intelligence (AI) is rapidly transforming customer service through automation, scalability, and data-driven personalization, yet its effectiveness depends on how customers perceive automated interactions, particularly in fragile, low-regulation contexts such as Somalia. This study aimed to provide the first empirical evidence on Somali customers’ perceptions of AI-enabled customer service and to test how trust in AI and perceived service quality shape user satisfaction and, in turn, recommendation readiness, while accounting for digital literacy. Using a positivist, descriptive cross-sectional design, primary data were collected via a bilingual (Somali/English) online questionnaire from 353 adult customers in Mogadishu, Hargeisa, Garowe, and Kismayo who had interacted with AI-based customer support in telecommunications and mobile banking within the prior six months (86.9% response rate). Constructs were measured with culturally adapted multi-item Likert scales (Cronbach’s α = 0.81–0.92); hypotheses were tested using correlations, multiple regression, and structural equation modeling with bootstrapped mediation and moderation. Customers reported moderate trust (M = 3.12), service quality (M = 3.20), satisfaction (M = 3.27), and recommendation readiness (M = 3.30). Transparency was the weakest trust facet (M = 2.87), alongside low confidence in protection against unauthorized data access (M = 2.78), whereas efficiency was the strongest perceived service-quality benefit (M = 3.61) and system availability was comparatively higher (M = 3.34). Service quality predicted satisfaction more strongly (β = 0.45, p < 0.001) than trust (β = 0.31, p < 0.001), and satisfaction predicted recommendation readiness (β = 0.58, p < 0.001). Satisfaction partially mediated effects of trust and service quality on recommendation readiness (indirect β = 0.18 and 0.26, respectively; model fit: CFI = 0.94, RMSEA = 0.062), and digital literacy strengthened the satisfaction-to-recommendation link (interaction β = 0.12, p < 0.01). Overall, Somali customers exhibit pragmatic acceptance of AI for efficiency gains but remain constrained by transparency, privacy-security concerns, and a persistent preference for relational human service, implying that trust-sensitive transparency, privacy-by-design, culturally calibrated personalization, and hybrid human–AI escalation pathways are critical for sustainable AI deployment in fragile economies.

  • References

    1. Antczak, J., Kabus, J., Miciuła, I., Lenort, R., Brzozowska, A., Wolniak, R., & Kana, R. (2025). Artificial Intelligence in business management - SWOT analysis. Procedia Computer Science, 270, 4410–4420. https://doi.org/10.1016/j.procs.2025.09.566
    2. Ashfaq, M., Makkar, M., Hoang, A. P., Dang-Pham, D., Do, M. H. T., & Nguyen, A. T. V. (2025). Exploring customer stickiness during “smart” experiences: a study on AI chatbot affinity in online customer services. Journal of Research in Interactive Marketing. https://doi.org/10.1108/JRIM-09-2024-0452
    3. Ayala, N. F., Rodrigues da Silva, J., Cannarozzo Tinoco, M. A., Saccani, N., & Frank, A. G. (2025). Artificial Intelligence capabilities in Digital Servitization: Identifying digital opportunities for different service types. International Journal of Production Economics, 284. https://doi.org/10.1016/j.ijpe.2025.109604
    4. Bhattacharyya, S. S. (2025). Study of adoption of artificial intelligence technology-driven natural large language model-based chatbots by firms for customer service interaction. Journal of Science and Technology Policy Management, 16(8), 1367–1379. https://doi.org/10.1108/JSTPM-11-2023-0201
    5. Bigliardi, B., Bottani, E., Dolci, V., Monferdini, L., & Pini, B. (2025). Artificial intelligence in consumer preferences: Implications for health and well-being. Procedia Computer Science, 253, 2869–2878. https://doi.org/10.1016/j.procs.2025.02.011
    6. Buhalis, D., & Moldavska, I. (2022). Voice assistants in hospitality: using artificial intelligence for customer service. Journal of Hospitality and Tourism Technology, 13(3), 386–403. https://doi.org/10.1108/JHTT-03-2021-0104
    7. Cao, L., Sarkar, S., Ramesh, B., Mohan, K., & Park, E. H. (2024). Shift of ambidexterity modes: An empirical investigation of the impact of artificial intelligence in customer service. International Journal of Information Management, 76. https://doi.org/10.1016/j.ijinfomgt.2024.102773
    8. Chang, Y., Wang, H., & Guo, Z. (2025). Artificial intelligence in live streaming: How can virtual streamers bring more sales? Journal of Retailing and Consumer Services, 84. https://doi.org/10.1016/j.jretconser.2025.104247
    9. Chau, H. K. L., Ngo, T. T. A., Bui, C. T., & Tran, N. P. N. (2025). Human-AI interaction in E-Commerce: The impact of AI-powered customer service on user experience and decision-making. Computers in Human Behavior Reports, 19. https://doi.org/10.1016/j.chbr.2025.100725
    10. Chotisarn, N., & Phuthong, T. (2025). Impact of artificial intelligence-enabled service attributes on customer satisfaction and loyalty in chain hotels: Evidence from coastal tourism destinations in western Thailand. Social Sciences and Humanities Open, 11. https://doi.org/10.1016/j.ssaho.2025.101306
    11. Dai, Y., Huang, Z., He, W., Khan, N., & Yang, Y. (2024). Emotional dialogue generation model of electronic commerce intelligent customer service based on topic expansion. Engineering Applications of Artificial Intelligence, 138. https://doi.org/10.1016/j.engappai.2024.109429
    12. Du, J., Popp, N., & Shapiro, S. L. (2025). Enhancing sport sales training through technology: an examination of artificial intelligence as a tool for evaluating and training sales agents. International Journal of Sports Marketing and Sponsorship, 26(4), 768–785. https://doi.org/10.1108/IJSMS-09-2024-0263
    13. Ferraro, C., Demsar, V., Sands, S., Restrepo, M., & Campbell, C. (2024). The paradoxes of generative AI-enabled customer service: A guide for managers. Business Horizons, 67(5), 549–559. https://doi.org/10.1016/j.bushor.2024.04.013
    14. Gao, J., Opute, A. P., Jawad, C., & Zhan, M. (2025). The influence of artificial intelligence chatbot problem solving on customers’ continued usage intention in e-commerce platforms: an expectation-confirmation model approach. Journal of Business Research, 200. https://doi.org/10.1016/j.jbusres.2025.115661
    15. Graham, G., Nisar, T. M., Prabhakar, G., Meriton, R., & Malik, S. (2025). Chatbots in customer service within banking and finance: Do chatbots herald the start of an AI revolution in the corporate world? Computers in Human Behavior, 165. https://doi.org/10.1016/j.chb.2025.108570
    16. Guo, Y., Chen, Y., & Singh, S. K. (2025). Cross-border platforms’ coupling of artificial intelligence adoption and strategic agility for upgraded ESMEs’ global value chains: international marketing capability perspectives. International Marketing Review. https://doi.org/10.1108/IMR-10-2024-0418
    17. Hari, H., Sharma, A., Verma, S., & Chaturvedi, R. (2025). Exploring ethical frontiers of artificial intelligence in marketing. Journal of Responsible Technology, 21. https://doi.org/10.1016/j.jrt.2024.100103
    18. Ikhsan, R. B., Fernando, Y., Prabowo, H., Yuniarty, Gui, A., & Kuncoro, E. A. (2025). An empirical study on the use of artificial intelligence in the banking sector of Indonesia by extending the TAM model and the moderating effect of perceived trust. Digital Business, 5(1). https://doi.org/10.1016/j.digbus.2024.100103
    19. Jang, I., Kim, J., & Park, I. (2025). When AI takes your call: Investigating the impact of conversational styles on customer service agents’ affective delivery. Telematics and Informatics, 99. https://doi.org/10.1016/j.tele.2025.102277
    20. Ku, E. C. S. (2025). Increasing customer service competencies of airports: virtual integration competence, warmth and intimacy of artificial intelligence services. Business Process Management Journal, 31(4), 1392–1413. https://doi.org/10.1108/BPMJ-12-2023-0948
    21. Lee, D. H., & Gottlieb, U. (2025). Back to the future via human-centered artificial intelligence. Asia Pacific Journal of Marketing and Logistics. https://doi.org/10.1108/APJML-02-2025-0284
    22. Leocádio, D., Guedes, L., Oliveira, J., Reis, J., & Melão, N. (2024). Customer Service with AI-Powered Human-Robot Collaboration (HRC): A Literature Review. Procedia Computer Science, 232, 1222–1232. https://doi.org/10.1016/j.procs.2024.01.120
    23. Li, R., & Zhong, Q. (2024). On the Application of Generative Artificial Intelligence ChatGPT in Digital Trade. Procedia Computer Science, 247(C), 112–120. https://doi.org/10.1016/j.procs.2024.10.014
    24. Lian, J. W., & Li, C. W. (2025). Using a two-stage method to understand the critical factors influencing customers’ intention to switch from traditional to artificial intelligence based banking services: A perspective based on the push–pull–mooring model. Computers in Human Behavior, 168. https://doi.org/10.1016/j.chb.2025.108645
    25. Meng, H., Xiao, Q., & Na, Y. (2025). Warmhearted cues: A study of the impact of social mindfulness on trust repair by intelligent customer service in service recovery. International Journal of Hospitality Management, 128. https://doi.org/10.1016/j.ijhm.2025.104131
    26. Molina, M. D., Thorson, E., Huddleston, P., & de Bruin, J. (2025). Customers’ perceptions of AI designers: the role of cognitive heuristics and customization. Journal of Consumer Marketing, 1–15. https://doi.org/10.1108/JCM-02-2025-7595
    27. Ngo, T. T. A., Phan, T. Y. N., Nguyen, T. K., Le, N. B. T., Nguyen, N. T. A., & Le, T. T. D. (2025). Understanding continuance intention toward the use of AI chatbots in customer service among generation Z in Vietnam. Acta Psychologica, 259. https://doi.org/10.1016/j.actpsy.2025.105468
    28. Niros, A., Niros, M. I., Baltas, G., Giovanis, A., & Painesis, G. (2025). Chatbot marketing efforts in the era of artificial intelligence: The moderating role of individualism. International Marketing Review, 42(4), 788–816. https://doi.org/10.1108/IMR-10-2024-0443
    29. Northey, G., Hunter, V., Mulcahy, R., Choong, K., & Mehmet, M. (2022). Man vs machine: how artificial intelligence in banking influences consumer belief in financial advice. International Journal of Bank Marketing, 40(6), 1182–1199. https://doi.org/10.1108/IJBM-09-2021-0439
    30. Rahi, S., Ngah, A. H., Alnasr, F., Alghizzawi, M., Rasheed, R., & Rashid, A. (2025). Unlocking the precursors of customer service experience using artificial intelligence-driven chatbot: calibration of gratification theory and expectation confirmation model. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-10-2024-0551
    31. Ratner, S., Revinova, S., Balashova, S., & Ersoy, A. B. (2025). Artificial intelligence and consumer loyalty in e-commerce. Procedia Computer Science, 253, 435–444. https://doi.org/10.1016/j.procs.2025.01.105
    32. Ren, G., Chen, Y., & Yang, M. (2024). Customer perception, integration behavior, and loyalty of internet of things enterprises. Technology in Society, 78. https://doi.org/10.1016/j.techsoc.2024.102600
    33. Shin, H., Ryu, J., & Jo, Y. (2025). Navigating artificial intelligence adoption in hospitality and tourism: managerial insights, workforce transformation, and a future research agenda. International Journal of Hospitality Management, 128. https://doi.org/10.1016/j.ijhm.2025.104187
    34. Shuqair, S., Pinto, D. C., Lancelot Miltgen, C., & Viglia, G. (2024). When powerful artificial intelligence backfires. International Journal of Hospitality Management, 120. https://doi.org/10.1016/j.ijhm.2024.103778
    35. Song, M., Xing, X., Duan, Y., Cohen, J., & Mou, J. (2022). Will artificial intelligence replace human customer service? The impact of communication quality and privacy risks on adoption intention. Journal of Retailing and Consumer Services, 66. https://doi.org/10.1016/j.jretconser.2021.102900
    36. Swan, E. L., Peltier, J. W., & Dahl, A. J. (2024). Artificial intelligence in healthcare: the value co-creation process and influence of other digital health transformations. Journal of Research in Interactive Marketing, 18(1), 109–126. https://doi.org/10.1108/JRIM-09-2022-0293
    37. Tan, K. L., Yeap, P. F., Cheong, K. C. K., & Loganathan, S. R. (2025). Crafting an organizational strategy for the new era: a qualitative study of artificial intelligence transformation in a homegrown Singaporean hotel chain. Business Process Management Journal, 31(8), 104–123. https://doi.org/10.1108/BPMJ-11-2024-1086
    38. Tian, J., Lin, H., Tourky, M., & Cheng, B. (2025). The impact of AI service failure on human employee behavior and customer service performance. International Journal of Contemporary Hospitality Management, 37(7), 2264–2286. https://doi.org/10.1108/IJCHM-08-2024-1209
    39. Vafaei-Zadeh, A., Nikbin, D., Wong, S. L., & Hanifah, H. (2025). Investigating factors influencing AI customer service adoption: an integrated model of stimulus–organism–response (SOR) and task-technology fit (TTF) theory. Asia Pacific Journal of Marketing and Logistics, 37(6), 1465–1502. https://doi.org/10.1108/APJML-05-2024-0570
    40. Yao, A., Jia, F., Jiang, L., Shi, Z., & Wei, Q. (2026). Artificial intelligence customer service adoption strategy in platform supply chain: Strategic interactions and consumer automation aversion. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2025.12.032
    41. Yu, J., Zhan, X., & Bojja, G. R. (2025). Exploring artificial intelligence for sustainable business development: a review. Data Science and Management. https://doi.org/10.1016/j.dsm.2025.10.001
    42. Zhang, J., Wang, X., Lu, J., Liu, L., & Feng, Y. (2024). The impact of emotional expression by artificial intelligence recommendation chatbots on perceived humanness and social interactivity. Decision Support Systems, 187. https://doi.org/10.1016/j.dss.2024.114347
    43. Zhang, J., Zheng, C. G., Yang, J., & Usama, M. (2022). Research on an Interactive Question Answering System of Artificial Intelligence Customer Service Based on word2Vec. International Journal of E-Collaboration, 18(2). https://doi.org/10.4018/IJeC.304040
    44. Zhu, H., Vigren, O., & Söderberg, I. L. (2024). Implementing artificial intelligence empowered financial advisory services: A literature review and critical research agenda. Journal of Business Research, 174. https://doi.org/10.1016/j.jbusres.2023.114494
    45. Zimmermann, R., Mora, D., Cirqueira, D., Helfert, M., Bezbradica, M., Werth, D., Weitzl, W. J., Riedl, R., & Auinger, A. (2023). Enhancing brick-and-mortar store shopping experience with an augmented reality shopping assistant application using personalized recommendations and explainable artificial intelligence. Journal of Research in Interactive Marketing, 17(2), 273–298. https://doi.org/10.1108/JRIM-09-2021-0237
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to cite

Rage, A. (2026). Customer Perceptions of Artificial Intelligence in Enhancing Customer Service: Empirical Evidence from Somalia. Multidisciplinary Reviews, (| Accepted Articles). Retrieved from https://malque.pub/ojs/index.php/mr/article/view/17940
  • Article viewed - 25