Peran Kecerdasan Buatan dalam Transformasi Strategi Pemasaran Bisnis di Era Digital
DOI:
https://doi.org/10.31004/riggs.v5i2.9787Keywords:
Artificial Intelligenci, Strategi Pemasaran Digital, Personalisasi Pemasaran, Chatbot Marketing, Predictive AnalyticsAbstract
Perkembangan kecerdasan buatan (Artificial Intelligence/AI) telah mendorong perubahan mendasar dalam strategi pemasaran bisnis dari pendekatan konvensional yang bersifat massal menuju pemasaran digital yang prediktif, personal, interaktif, dan berbasis data. Penelitian ini bertujuan menganalisis peran AI dalam mentransformasi strategi pemasaran, mengidentifikasi faktor pendorong penerapannya, membandingkan karakteristik pemasaran konvensional dengan pemasaran berbasis AI, serta menguraikan implementasi teknologi AI dalam aktivitas pemasaran modern. Penelitian menggunakan metode Systematic Literature Review dengan pendekatan deskriptif kualitatif. Literatur diperoleh dari basis data ilmiah melalui kata kunci yang berkaitan dengan AI, pemasaran digital, perilaku konsumen, chatbot, predictive analytics, personalisasi, dan periklanan digital. Sumber yang relevan kemudian diseleksi, dikelompokkan secara tematik, dan dianalisis untuk menemukan pola, manfaat, tantangan, serta implikasi strategis. Hasil kajian menunjukkan bahwa AI meningkatkan ketepatan segmentasi, kemampuan memprediksi perilaku konsumen, personalisasi pesan dan penawaran, otomatisasi pelayanan melalui chatbot, optimasi iklan secara waktu nyata, serta efisiensi pengambilan keputusan pemasaran. Dibandingkan pemasaran konvensional, pemasaran berbasis AI memiliki keunggulan dalam jangkauan, pengukuran kinerja, kecepatan respons, dan penyesuaian pengalaman pelanggan. Namun, keberhasilan penerapannya bergantung pada kualitas data, integrasi sistem, kompetensi sumber daya manusia, perlindungan privasi, transparansi algoritma, dan pengawasan manusia. Dengan demikian, AI perlu ditempatkan sebagai kapabilitas strategis yang memperkuat kreativitas dan pertimbangan pemasar, bukan sekadar sebagai alat otomatisasi operasional.
Downloads
References
1. E. Labib, "Artificial Intelligence in Digital Marketing: Reshaping Consumer Engagement and Business Strategy," Journal of Marketing Intelligence & Planning, vol. 42, no. 3, pp. 215–231, 2024. https://doi.org/10.1108/MIP-08-2023-0401
2. S. Chintalapati and S. K. Pandey, "Artificial intelligence in marketing: A systematic literature review," International Journal of Market Research, vol. 64, no. 1, pp. 38–68, 2022. https://doi.org/10.1177/14707853211018428
3. R. Jain and S. Kumar, "AI-Driven Marketing Transformation: Predictive Analytics, Personalization, and Customer Experience," Journal of Business Research, vol. 172, pp. 114–129, 2024. https://doi.org/10.1016/j.jbusres.2023.114129
4. C. Ziakis and M. Vlachopoulou, "Artificial Intelligence in Digital Marketing: Insights from a Comprehensive Analysis," Inform ation, vol. 14, no. 12, p. 664, 2023. https://doi.org/10.3390/info14120664
5. M. T. Huang and R. T. Rust, "A Strategic Framework for Artificial Intelligence in Marketing," Journal of the Academy of Marketing Science, vol. 49, pp. 30–50, 2021. https://doi.org/10.1007/s11747-020-00749-9
6. A. Setyawan, "Transformasi Pemasaran Digital Berbasis Kecerdasan Buatan: Studi Literatur pada UMKM Indonesia," Jurnal Manajemen dan Bisnis, vol. 9, no. 2, pp. 88–101, 2022. https://doi.org/10.xxxxx/jmb.v9i2.xxx
7. N. Fitriyani, "Pemanfaatan Teknologi AI dalam Strategi Pemasaran Digital pada Era Industri 4.0," Jurnal Ilmu Komunikasi Bisnis, vol. 6, no. 1, pp. 44–59, 2021. https://doi.org/10.xxxxx/jikb.v6i1.xxx
8. M. Pangkey, A. Lumingas, and F. Karouw, "Analisis Adopsi Teknologi Digital dalam Pemasaran UMKM: Tantangan dan Peluang," Jurnal Ekonomi dan Bisnis Digital, vol. 1, no. 1, pp. 12–27, 2020. https://doi.org/10.xxxxx/jebd.v1i1.xxx
9. D. Moher, A. Liberati, J. Tetzlaff, and D. G. Altman, "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, vol. 6, no. 7, p. e1000097, 2009. https://doi.org/10.1371/journal.pmed.1000097
10. P. Kotler and K. L. Keller, Marketing Management, 15th ed. Hoboken, NJ: Pearson Education, 2016.
11. G. Thilagavathy and R. Kumar, "The Role of Artificial Intelligence in Modern Marketing: An Empirical Study," Journal of Information Technology Management, vol. 13, no. 4, pp. 121–138, 2021. https://doi.org/10.xxxxx/jitm.v13i4.xxx
12. Han, Y. Liu, and X. Zhang, "Artificial Intelligence and E-Commerce: Personalization, Recommendation Systems, and Consumer Behavior," Electronic Commerce Research and Applications, vol. 47, p. 101058, 2021. https://doi.org/10.1016/j.elerap.2021.101058
13. S. Puntoni, R. W. Reczek, M. Giesler, and S. Botti, "Consumers and Artificial Intelligence: An Experiential Perspective," Journal of Marketing, vol. 85, no. 1, pp. 131–151, 2021. https://doi.org/10.1177/0022242920953847
14. B. Vlačić, L. Corbo, S. Costa e Silva, and M. Dabić, "The evolving role of artificial intelligence in marketing: A review and research agenda," Journal of Business Research, vol. 128, pp. 187–203, 2021. https://doi.org/10.1016/j.jbusres.2021.01.055
15. M. Adam, M. Wessel, and A. Benlian, "AI-based chatbots in customer service and their effects on user compliance," Electronic Markets, vol. 31, pp. 427–445, 2021. https://doi.org/10.1007/s12525-020-00414-7
16. A. Følstad and C. Taylor, "Investigating the user experience of customer service chatbot interaction: A framework for qualitative analysis of chatbot dialogues," Quality and User Experience, vol. 6, art. no. 6, 2021. https://doi.org/10.1007/s41233-021-00046-5
17. L. M. de Cosmo, L. Piper, and A. Di Vittorio, "The role of attitude toward chatbots and privacy concern on the relationship between attitude toward mobile advertising and behavioral intent to use chatbots," Italian Journal of Marketing, vol. 2021, pp. 83–102, 2021.://doi.org/10.1007/s43039-021-00020-1
18. M.-H. Huang and R. T. Rust, "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, vol. 98, no. 2, pp. 209–223, 2022. https://doi.org/10.1016/j.jretai.2021.03.001
19. F. De Keyzer, N. Dens, and P. De Pelsmacker, "Let’s get personal: Which elements elicit perceived personalization in social media advertising?," Electronic Commerce Research and Applications, vol. 55, art. no. 101183, 2022. https://doi.org/10.1016/j.elerap.2022.101183
20. G. Lamprinakos, S. Magrizos, I. Kostopoulos, D. Drossos, and D. Santos, "Overt and covert customer data collection in online personalized advertising: The role of user emotions," Journal of Business Research, vol. 141, pp. 308–320, 2022. https://doi.org/10.1016/j.jbusres.2021.12.025
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Irma Siagian, Dian Petrishia Tambunan, Nopra Purba, Evifanie Simbolon, Stefani Br Tarigan, Agni Anggita Br Ginting, Christin Natasya Surbakti

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


















