Generative AI and Customer Experience Management for Small and Medium-sized Enterprises (SMEs)
Article Sidebar
Main Article Content
Abstract
Deep understanding of customer behavior and needs is crucial for businesses to respond and deliver a good experience, which is important for their competitive capability. This research aims to study the benefits, challenges, and methods of assessing the impact of using Generative AI in small and medium-sized enterprises (SMEs). The study employs documentary research and in-depth interviews with three individuals experienced in using Generative AI in customer service, selected through purposive sampling. Content analysis was used to evaluate and synthesize the data. The research findings indicate that Generative AI helps improve customer experience by personalizing interactions, enhancing work efficiency, and predicting customer behavior to design appropriate marketing strategies. However, the implementation of Generative AI in SMEs faces challenges in data security, privacy, AI model accuracy, and the readiness of organizational resources and personnel. The impact of Generative AI on customer experience and loyalty can be assessed through its use in real-time customer data analysis, the ability to respond to customer needs, and the development and improvement of service quality based on the analysis of customer feedback or complaints. This research demonstrates how SMEs can use generative AI to manage and provide customer experiences in order to build loyalty and maintain a competitive edge.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The content within the published articles, including images and tables, is copyrighted by Rajamangala University of Technology Rattanakosin. Any use of the article's content, text, ideas, images, or tables for commercial purposes in various formats requires permission from the journal's editorial board.
Rajamangala University of Technology Rattanakosin permits the use and dissemination of article files under the condition that proper attribution to the journal is provided and the content is not used for commercial purposes.
The opinions and views expressed in the articles are solely those of the respective authors and are not associated with Rajamangala University of Technology Rattanakosin or other faculty members in the university. The authors bear full responsibility for the content of their articles, including any errors, and are responsible for the content and editorial review. The editorial board is not responsible for the content or views expressed in the articles.
References
Abrokwah-Larbi, K., & Awuku-Larbi, Y. (2023). The impact of artificial intelligence in marketing on the performance of business organizations: evidence from SMEs in an emerging economy. Journal of Entrepreneurship in Emerging Economies, 16(4), 1090-1117. https://doi.org/10.1108/jeee-07-2022-0207
AI Government Center. (2024). The future and challenges of public innovation development and administration using artificial intelligence. https://www.etda.or.th/getattachment/Our-Service/AIGC/Research-and-Recommendation/05-FutureAndChallengesofDevelopingPublicSector InnovationAndMgmtUsingAI-Numtip.pdf.aspx?lang=th-TH
Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114(1), 106548. https://doi.org/10.1016/j.chb.2020.106548
Arora, R. (2024). Leveraging Generative AI in E-commerce: Enhancing customer experience from conversation to reviews. International Journal For Multidisciplinary Research, 6(5), 1-8. https://doi.org/10.36948/ijfmr.2024.v06i05.25833
Bertalanffy, L. von. (1968). General system theory: Foundations, development, applications. George Braziller.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Dwivedi, Y., & Kurde, A. (2024). AI-Driven innovation in CRM: Exploring the potential of generative models for customer experience optimization. Indian Scientific Journal Of Research in Engineering and Management, 8(10), 1-4. https://doi.org/10.55041/ijsrem37873
Ibecheozor, U. H., Iwuchukwu, E. C., & Akinyele, A. R. (2024). Deep learning application in sales automation and customer experience personalization in small and medium-sized business: A hybrid approach using transformer-based large language models and reinforcement learning. International Journal of Innovative Science and Modern Engineering (IJISME). 13(1), 1-8. DOI: 10.35940/ijisme.A1321.13010125
Jatupornthanaphat, P. (2024). Policy on using artificial intelligence innovation Ai to increase the country's competitiveness. Journal of Administration Management and Sustainable Development, 2(2), 331-340.
Kshetri, N., Rojas-Torres, D., Hanafi, M. M., Al-kfairy, M., O’Keefe, G., & Feeney, N. (2024). Harnessing generative artificial intelligence: A game-changer for small and medium enterprises. IT Professional, 26(6), 84-89. https://doi.org/10.1109/MITP.2024.3501552
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
Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96.
Mladenović, M., Jauković Jocić, K., Đukić, T., Momčilović, O., & Maričić, S. (2024). Reshaping digital landscapes: Analyzing the impact of Ai in digital marketing strategies on local Smes. SCIENCE International Journal, 3(4), 99-104. https://doi.org/10.35120/sciencej0304099m
Nwachukwu, D., & Affen, M. P. (2023). Artificial intelligence marketing practices: The way forward to better customer experience management in Africa (Systematic Literature Review). International Academy Journal of Management, Marketing and Entrepreneurial Studies, 9(2), 44-62.
Office of Small and Medium Enterprises Promotion. (2024). Situation report of MSMEs in 2024. https://www.sme.go.th/uploads/file/20240529154251_%E0%B8%A3%E0%B8%B2%E0%B8%A2%E0%B8%87%E0%B8%B2%E0%B8%99%E0%B8%AA%E0%B8%96%E0%B8%B2%E0%B8%99%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%93%E0%B9%8C_MSME2567_TH_Online.pdf#page=51.00
Office of the Personal Data Protection Committee, PDPC. (2025). Personal Data Protection Act. https://www.pdpc.or.th/pdpcbook/%e0%b8%ab%e0%b8%99%e0%b8%b1%e0%b8%87%e0%b8%aa%e0%b8%b7%e0%b8%ad%e0%b8%81%e0%b8%8f%e0%b8%ab%e0%b8%a1%e0%b8%b2%e0%b8%a2%e0%b8%a7%e0%b9%88%e0%b8%b2%e0%b8%94%e0%b9%89%e0%b8%a7%e0%b8%a2%e0%b8%81%e0%b8%b2/#flipbook-df_9617/1/
Okeke, N. I., Alabi, O. A., Igwe, A. N., Ofodile, O. C., & Ewim, C. P.-M. (2024). AI-driven personalization framework for SMES: Revolutionizing customer engagement and retention. World Journal Of Advanced Research and Reviews, 24(01), 2019–2035. https://doi.org/10.30574/wjarr.2024.24.1.3208
Panawong, C. (2019). Qualitative research methodology. Naresuan University Publishing House.
Patil, D. (2024). Generative artificial intelligence in marketing and advertising: Advancing personalization and optimizing consumer engagement strategies. SSRN 5057404.
Patil, D., Rane, N., & Rane, J. (2024). Challenges in implementing ChatGPT and generative artificial intelligence in various business sectors. The Future Impact of ChatGPT on Several Business Sectors. In The Future Impact of ChatGPT on Several Business Sectors (pp. 107-145). Deep Science Publishing. https://doi.org/10.70593/978-81-981367-8-7_3
SCB EIC. (2024). Generative AI helps enhance the potential of Thai SMEs. https://www.scbeic.com/th/detail/file/product/9671/h2n9glj94p/In-focus-Generative-AI-20241129.pdf
Simion, P. C., & Popescu, M. A. M. (2023). Assessing the use of artificial intelligence in digital marketing: Evidence from Romanian companies. Proceedings of the International Conference on Business Excellence, 17(1), 1128-1138. https://doi.org/10.2478/picbe-2023-0101
Soni, V. (2023). Adopting generative AI in digital marketing campaigns: An empirical study of drivers and barriers. Sage Science Review of Applied Machine Learning, 6(8), 1-15. https://journals.sagescience.org/index.php/ssraml/article/view/108
Srivastava, A., Bose, I., Sharma, V., & Jain, G. (2025). AI-driven customer engagement strategies for small businesses. In M. N. Tunio (Ed.), AI, Corporate Social Responsibility, and Marketing in Modern Organizations (pp. 245-262). IGI Global. https://doi.org/10.4018/979-8-3373-0219-5.ch012
Udomlappaisan, C., & Chueachainat, K. (2023). Generative AI in mass communication. Saint Johns Journal, 26(39), 179-194.
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). https://doi.org/10.1016/j.jjimei.2020.100002
Yaprak, B. (2024). Generative artificial intelligence in marketing: The invisible danger of
AI hallucinations. Journal of Economy, Business and Management, 31(12), 102-115.
