Main Article Content

Abstract

This systematic literature review employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to synthesize empirical evidence on the effects of AI-driven marketing interactions including chatbots, virtual assistants, recommendation systems, AI customer service, personalized advertising, and conversational commerce on consumer trust, purchase intention, and brand engagement. Following a comprehensive search across eight reputable databases (Scopus, Web of Science, ScienceDirect, Emerald Insight, SpringerLink, Taylor & Francis, Wiley Online Library, and Sage Journals) for publications between 2019 and 2026, a total of 124 peer-reviewed empirical studies were included in the qualitative synthesis, with 48 studies providing sufficient quantitative data for meta-analytic procedures. The findings reveal that AI-driven marketing interactions predominantly exert positive effects on consumer trust (72% of studies), purchase intention (78%), and brand engagement (68%), contingent upon perceived anthropomorphism, transparency, personalization quality, and system responsiveness. Key mediating variables include perceived value, social presence, customer experience, and cognitive absorption, while privacy concerns, technology readiness, consumer innovativeness, and brand familiarity emerge as significant moderators. This review contributes theoretically by integrating Technology Acceptance Model (TAM), Social Presence Theory, Trust Theory, and Stimulus-Organism-Response (S-O-R) Framework into a comprehensive conceptual model explaining consumer responses to AI marketing. Practically, the findings provide actionable insights for marketers, brand managers, and AI developers to design human-centered, transparent, and ethically responsible AI marketing systems that foster meaningful consumer-brand relationships.

Keywords

Artificial Intelligence Marketing AI-Driven Interaction Consumer Trust Purchase Intention Brand Engagement

Article Details

How to Cite
Aulianda, M., Hakim, Y. P., & Lasnoto, L. (2026). Human or Artificial? A Meta-Analysis of the Effects of AI-Driven Marketing Interactions on Consumer Trust, Purchase Intention, and Brand Engagement. Golden Ratio of Mapping Idea and Literature Format, 6(3), 2160–2172. https://doi.org/10.52970/grmilf.v6i3.2409

References

  1. Açikgöz, F., Perez‐Vega, R., Okumuş, F., & Stylos, N. (2023). Consumer engagement with AI‐powered voice assistants: A behavioral reasoning perspective. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.21873
  2. Akdim, K., & Casaló, L. V. (2023). Perceived value of AI-based recommendations service: The case of voice assistants. Service Business. https://doi.org/https://doi.org/10.1007/s11628-023-00527-x
  3. Baek, T. H., Kim, J., Kim, J., Kim, J. H., & Kim, J. H. (2024). Effect of disclosing AI-generated content on prosocial advertising evaluation. International Journal of Advertising. https://doi.org/https://doi.org/10.1080/02650487.2024.2401319
  4. Balachandran, D. (2026). A study on the impact of personalization strategies on consumer buying behaviour in e-commerce. International Journal for Research in Applied Science and Engineering Technology. https://doi.org/10.22214/ijraset.2026.82988
  5. Balakrishnan, J., & Dwivedi, Y. K. (2021a). Conversational commerce: Entering the next stage of AI-powered digital assistants. Annals of Operations Research. https://doi.org/https://doi.org/10.1007/s10479-021-04049-5
  6. Balakrishnan, J., & Dwivedi, Y. K. (2021b). Role of cognitive absorption in building user trust and experience. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.21462
  7. Belanche, D., Casaló, L. V., Schepers, J., & Flavián, C. (2021). Examining the effects of robots” physical appearance, warmth, and competence in frontline services: The humanness‐value‐loyalty model. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.21532
  8. Blut, M., Wang, C., Wünderlich, N. V., & Brock, C. (2021). Understanding anthropomorphism in service provision: A meta-analysis of physical robots, chatbots, and other AI. Journal of the Academy of Marketing Science. https://doi.org/https://doi.org/10.1007/s11747-020-00762-y
  9. Cai, D., Li, H., & Law, R. (2022). Anthropomorphism and OTA chatbot adoption: A mixed methods study. Journal of Travel & Tourism Marketing. https://doi.org/https://doi.org/10.1080/10548408.2022.2061672
  10. Chen, Q., Gong, Y., Lu, Y., & Luo, X. (2024). The golden zone of AI’s emotional expression in frontline chatbot service failures. Internet Research. https://doi.org/https://doi.org/10.1108/intr-07-2023-0551
  11. Chen, Y., Tajuddin, R. B. M., Zainol, A. S. B., Suxia, Y., & Zijie, C. (2024). Toward understanding elderly consumers’ impulse buying in the digital marketing: A conceptual paper. International Journal of Research and Innovation in Social Science. https://doi.org/10.47772/ijriss.2024.8120282
  12. Dwivedi, Y. K., Balakrishnan, J., Baabdullah, A. M., & Das, R. (2023). Do chatbots establish “humanness” in the customer purchase journey? An investigation through explanatory sequential design. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.21888
  13. Flavián, C., Belk, R. W., Belanche, D., & Casaló, L. V. (2024). Automated social presence in AI: Avoiding consumer psychological tensions to improve service value. Journal of Business Research. https://doi.org/https://doi.org/10.1016/j.jbusres.2024.114545
  14. Gerlich, M. (2023). The power of virtual influencers: Impact on consumer behaviour and attitudes in the age of AI. Administrative Sciences. https://doi.org/https://doi.org/10.3390/admsci13080178
  15. Hasan, S., & Mayr, A. (2026). Consumer trust in digital marketing: A systematic literature review and conceptual framework. Global Insights in Management and Economic Research. https://doi.org/10.53905/gimer.v2i01.04
  16. Hassan, N., Abdelraouf, M., & El-Shihy, D. (2025). The moderating role of personalized recommendations in the trust–satisfaction–loyalty relationship: An empirical study of AI-driven e-commerce. Future Business Journal. https://doi.org/https://doi.org/10.1186/s43093-025-00476-z
  17. Hedhli, K. E., Zourrig, H., Khateeb, A. A., & Alnawas, I. (2023). Stereotyping human-like virtual influencers in retailing: Does warmth prevail over competence? Journal of Retailing and Consumer Services. https://doi.org/https://doi.org/10.1016/j.jretconser.2023.103459
  18. Hollebeek, L. D., Menidjel, C., Sarstedt, M., Jansson, J., & Urbonavičius, S. (2024). Engaging consumers through artificially intelligent technologies: Systematic review, conceptual model, and further research. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.21957
  19. Li, J., Wu, L., Qi, J., Zhang, Y., Wu, Z., & Hu, S. (2023). Determinants affecting consumer trust in communication with AI chatbots. Journal of Organizational and End User Computing. https://doi.org/https://doi.org/10.4018/joeuc.328089
  20. Mariani, M. M., Hashemi, N., & Wirtz, J. (2023). Artificial intelligence empowered conversational agents: A systematic literature review and research agenda. Journal of Business Research. https://doi.org/https://doi.org/10.1016/j.jbusres.2023.113838
  21. Molinillo, S., Rejón‐Guardia, F., Anaya‐Sánchez, R., & Liébana‐Cabanillas, F. (2023). Impact of perceived value on intention to use voice assistants: The moderating effects of personal innovativeness and experience. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.21887
  22. Mouritzen, S. L. T., Penttinen, V., & Pedersen, S. (2023). Virtual influencer marketing: The good, the bad and the unreal. European Journal of Marketing. https://doi.org/https://doi.org/10.1108/ejm-12-2022-0915
  23. Musa, H. G., Fatmawati, I., Nuryakin, N., & Suyanto, M. (2024). Marketing research trends using technology acceptance model (TAM): A comprehensive review of researches (2002–2022). Cogent Business & Management. https://doi.org/https://doi.org/10.1080/23311975.2024.2329375
  24. Nguyen, M., Ferm, L. C., Quach, S., Pontes, N., & Thaichon, P. (2023). Chatbots in frontline services and customer experience: An anthropomorphism perspective. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.21882
  25. Nicolescu, L., & Tudorache, M. T. (2022). Human-computer interaction in customer service: The experience with AI chatbots—a systematic literature review. Electronics. https://doi.org/https://doi.org/10.3390/electronics11101579
  26. Odekerken‐Schröder, G., Mennens, K., Steins, M., & Mahr, D. (2021). The service triad: An empirical study of service robots, customers and frontline employees. Journal of Service Management. https://doi.org/https://doi.org/10.1108/josm-10-2020-0372
  27. Pitardi, V., & Marriott, H. R. (2021). Alexa, she”s not human but… unveiling the drivers of consumers” trust in voice‐based artificial intelligence. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.21457
  28. Prince, A. A., Siddiqui, H. A., Lakho, M. B., Ahmad, S., & Asghar, A. (2025). Leveraging artificial intelligence for hyper-personalized marketing: Opportunities and challenges in the digital era. Inverge Journal of Social Sciences. https://doi.org/10.63544/ijss.v4i3.166
  29. Puntoni, S., Reczek, R. W., Giesler, M., & Botti, S. (2020). Consumers and artificial intelligence: An experiential perspective. Journal of Marketing. https://doi.org/https://doi.org/10.1177/0022242920953847
  30. R, V. A., R, Mr. R. K., & S, R. (2026). Role of AI recommendation on consumer behavior. International Journal of Advanced Research in Science, Communication and Technology. https://doi.org/10.48175/ijarsct-30755
  31. Rainy, T. A., & Dhanekula, A. (2025). Development of model influence on consumer behavior in u.s. E-commerce and digital marketing. American Journal of Interdisciplinary Studies. https://doi.org/10.63125/1brehy25
  32. Rakesh. (2025). AI-powered chatbots as a marketing tool: Customer perception and trust. Scriptora International Journal of Research and Innovation (SIJRI). https://doi.org/10.65579/sijri.2025.v1i2.07
  33. Sahu, Dr. J. K., Sankhla, Mr. D., & Anjana, Dr. C. (2025). Personalized marketing in the digital age: The role of AI in consumer behavior analytics. European Economic Letters (EEL). https://doi.org/10.52783/eel.v15i3.3415
  34. Saura, J. R., Škare, V., & Došen, Đ. O. (2024). Is AI-based digital marketing ethical? Assessing a new data privacy paradox. Journal of Innovation & Knowledge. https://doi.org/https://doi.org/10.1016/j.jik.2024.100597
  35. Sui, J., Shen, H., & Zhou, X. (2024). Impact of cultural tightness on consumers” preference for anthropomorphic AI services. Psychology and Marketing. https://doi.org/https://doi.org/10.1002/mar.22086
  36. Swarnali, S. H. (2026). A systematic review of AI-driven customer analytics for personalized marketing in digital commerce (2019–2026). American Journal of Data Science and Analytics. https://doi.org/10.63125/kef4vh98
  37. Uddin, H. (2026). A systematic review of artificial intelligence-based customer analytics in personalized digital marketing (2019–2026). American Journal of Data Science and Analytics. https://doi.org/10.63125/x3e0dx27
  38. Vazova, T. (2026). PSYCHOSOCIAL MECHANISMS OF AI ACCEPTANCE IN SOCIAL SERVICES FOR ADULTS AND OLDER PEOPLE: TRUST, CONTROL, AND PERCEIVED USEFULNESS. International Interdisciplinary Scientific Journal "Expert". https://doi.org/10.62034/2815-5300/2026-v3-001
  39. Wang, C., Ahmad, S. F., Ahmad, A. Y. A. B., Awwad, E. M., Irshad, M., Ali, Y. A., Al‐Razgan, M., Khan, Y., & Han, H. (2023). RETRACTED: An empirical evaluation of technology acceptance model for artificial intelligence in e-commerce. Heliyon. https://doi.org/https://doi.org/10.1016/j.heliyon.2023.e18349
  40. Xu, H., Law, R., Lovett, J. C., Luo, J. M., & Liu, L. (2024). Tourist acceptance of ChatGPT in travel services: The mediating role of parasocial interaction. Journal of Travel & Tourism Marketing. https://doi.org/https://doi.org/10.1080/10548408.2024.2364336