CHATBOT AS AN ADAPTIVE BUSINESS COMMUNICATION STRATEGY IN FACING DIGITAL ECONOMIC DISRUPTION

Authors

  • Ahmad Rizqi Suryadi UIN Sunan Gunung Djati Bandung, Indonesia , Indonesia

Keywords:

Chatbot, Adaptive Communication, Digital Disruption, Business Resilience, Artificial Intelligence.

Abstract

This article evaluates the impact of chatbots as an adaptive business communication strategy in the face of digital economic disruption. Digital economic disruption requires companies to implement agile communication strategies so that services can continue to operate amidst unstable market conditions. Chatbots are artificial intelligence-based conversational agents that have efficient interfaces and are always available for use. This article analyzes the role of chatbots as an adaptive communication strategy in the context of digital economic disruption. Rapid technological developments force the business world to innovate in how to interact with customers, especially amid uncertainty and changes in market demand. Chatbots—automated systems that can simulate conversations—are increasingly used by companies to improve communication efficiency and maintain service sustainability. Through a literature-based analysis, this article examines how chatbot adoption can support organizational agility, customer service innovation, and communication responsiveness. In addition, this article also highlights the ethical and practical challenges in implementing chatbots. The findings suggest that integrating chatbot technology into business communication strategies offers a relevant and adaptive solution to the demands of a disruptive digital economy.

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References

1. Accenture. (2020). COVID-19: Responsive customer service through automation and AI. Accenture. https://www.accenture.com

2. Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922

3. Company, M. &.(2021). Digital customer care: AI-powered transformation for service operations. https://www.mckinsey.com

4. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5

5. Følstad P. B., A. A.-B. (2017). Chatbots and the new world of HCI. Interactions, 24(4), 38–42. https://doi.org/10.1145/3085558

6. Guntara, R. G. (2022). Aplikasi Chatbot Konsultan Bisnis untuk UMKM Berbasis Dialogflow pada Platform Android A B S T R A K Informasi Artikel. https://ejournal.upi.edu/index.php/IJDB

7. Haskel, J., & Westlake, S. (2018). The Rise of the Intangible Economy. Princeton University Press. https://doi.org/10.2307/j.ctvc77hhj

8. Huang, M. H., & Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459

9. Jain, V., Wadhwani, K., & Eastman, J. K. (2024). Artificial intelligence consumer behavior: A hybrid review and research agenda. Journal of Consumer Behaviour, 23(2), 676–697. https://doi.org/10.1002/cb.2233

10. Mctear, M. (2020). Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots. Synthesis Lectures on Human Language Technologies, 13, 1–251. https://doi.org/10.2200/S01060ED1V01Y202010HLT048

11. Sheth, J. (2020). Impact of Covid-19 on consumer behavior: Will the old habits return or die? Journal of Business Research, 117, 280–283. https://doi.org/10.1016/j.jbusres.2020.05.059

12. Tenti Tri Apriani, E., Desti Pertiwi, R., Permata Sari, R., Maharani, S., Jeni Meirisha, P., Rosalina, F., Bisnis dan Manajemen, J., Ekonomi Syariah Yang Inklusif Dan Berkelanjutan Tenti Tri Apriani, P., Zelvia, M., & Tinggi Ekonomi dan Bisnis Syariah, S. (2024). Transformasi Digital Berbasis E-Commerce Dalam Mendukung Pertumbuhan Transformasi Digital Berbasis E-Commerce Dalam Mendukung (Vol. 2, Issue 4).

13. Widianto, T. (2022). Rancang Bangun Aplikasi Chatbot Untuk Pendukung Perdagangan Dengan Menggunakan Metode Fuzzy String Matching-RUP (Studi Kasus : Warung Kedelai Edamame Kalibagor). Jurnal Sains Dan Manajemen, 10(2).

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Published

2025-08-15

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