ASSESSING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON VISUAL MARKETING MANAGEMENT

Authors

  • Mahaveerakannan R Professor, Department of CSE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India
  • Dr. Sarala P Adhau Associate Professor, Department of Electrical Engineering, Yeshwantrao Chavan College of Engineering, Nagpur Maharashtra, India
  • P. Ramya Associate Professor, Department of Artificial Intelligence and Data Science, PSNA College of Engineering and Technology, India
  • N. V. Ratnakishor Gade Research Scholar, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India
  • M. Saravanan Associate Professor, Department of Artificial Intelligence and Data Science, KPR Institute of Engineering and Technology, Coimbatore, India
  • Jebakumar Immanuel D Associate Professor Department of Artificial Intelligence and Data Science, Karpagam Institute of Technology, Coimbatore - 641105, India

DOI:

https://doi.org/10.29121/shodhkosh.v6.i4s.2025.6973

Keywords:

Artificial Intelligence, Visual Marketing Management, Computer Vision, Predictive Analytics, Digital Marketing Analytics, Brand Performance

Abstract [English]

The growing role of the visual content in the internet has made visual marketing as a highly significant strategic position in the contemporary marketing management. At the same time, the evolution of Artificial Intelligence (AI) has enabled organizations to analyze, customize, and streamline the marketing efforts in visuals on a platform and scale never before attempted or achieved. The paper discusses the AI application in visual marketing management by examining the ways that the AI capabilities have transformed strategic planning, content creation, personalization, monitoring, and optimization of visual campaigns. The research that is founded on the overall assessment of academic literature and formulated analytical theories frames AI as the empowering management attribute, but not the technology application. Consequently, based on the analysis, one can mention that the visual marketing processes are supported by the use of computer vision, predictive analytics, and generative AI in data-driven decision-making, the real-time performance measurement, and the continuous learning processes. The paper also provides the assessment of whether visual marketing can be affected by AI or not and induce the short-term performance indicators, such as engagement and conversion rates, and the long-term brand equity indicators, such as brand recall and consumer trust. In addition, the study describes the managerial and ethical issues regarding the AI adoption, including data privacy, algorithmic bias, transparency and human control. The current research contributes an analytical value to the management of AI-based visual marketing by combining strategic, operational, and governance strategies. The findings may be applicable to researchers and specialists who are interested in referring to AI as the basis of effective and responsible visual marketing in online services that are more competitive.

References

Braun, C., Batt, V., Bruhn, M., and Hadwich, K. (2016). Differentiating Customer Engaging Behavior by Targeted Benefits—An Empirical Study. Journal of Consumer Marketing, 33, 528–538. https://doi.org/10.1108/JCM-02-2016-1711 DOI: https://doi.org/10.1108/JCM-02-2016-1711

Davenport, T. H., and Ronanki, R. (2018). Artificial Intelligence for the Real World. Harvard Business Review, 96, 108–116.

Dogru, T., et al. (2025). Generative Artificial Intelligence in the Hospitality and Tourism Industry: Developing a Framework for Future Research. Journal of Hospitality and Tourism Research, 49, 235–253. https://doi.org/10.1177/10963480231188663 DOI: https://doi.org/10.1177/10963480231188663

Gupta, Y., and Khan, F. M. (2024). Role of Artificial Intelligence in Customer Engagement: A Systematic Review and Future Research Directions. Journal of Modeling in Management, 19, 1535–1565. https://doi.org/10.1108/JM2-01-2023-0016 DOI: https://doi.org/10.1108/JM2-01-2023-0016

Hollebeek, L. D., Menidjel, C., Sarstedt, M., Jansson, J., and Urbonavicius, S. (2024). Engaging Consumers Through Artificially Intelligent Technologies: Systematic Review, Conceptual Model, and Further Research. Psychology and Marketing, 41, 880–898. https://doi.org/10.1002/mar.21957 DOI: https://doi.org/10.1002/mar.21957

Kotler, P., Kartajaya, H., and Setiawan, I. (2021). Marketing 5.0: Technology for Humanity. John Wiley and Sons.

Sang, N. M. (2024). Bibliometric Insights into the Evolution of Digital Marketing Trends. Innovative Marketing, 20, 1–14. https://doi.org/10.21511/im.20(2).2024.01 DOI: https://doi.org/10.21511/im.20(2).2024.01

Shaik, M. (2023). Impact of Artificial Intelligence on Marketing. East Asian Journal of Multidisciplinary Research, 2, 993–1004. https://doi.org/10.55927/eajmr.v2i3.3112 DOI: https://doi.org/10.55927/eajmr.v2i3.3112

Shawky, S., Kubacki, K., Dietrich, T., and Weaven, S. (2020). A Dynamic Framework for Managing Customer Engagement on Social Media. Journal of Business Research, 121, 567–577. https://doi.org/10.1016/j.jbusres.2020.03.030 DOI: https://doi.org/10.1016/j.jbusres.2020.03.030

So, K. K. F., Kim, H., and King, C. (2021). Thematic Evolution of Customer Engagement Research: A Comparative Systematic Review and Bibliometric Analysis. International Journal of Contemporary Hospitality Management, 33, 3585–3609. https://doi.org/10.1108/IJCHM-04-2021-0470 DOI: https://doi.org/10.1108/IJCHM-04-2021-0470

Wirtz, V., et al. (2013). Managing Brands and Customer Engagement in Online Brand Communities. Journal of Service Management, 24, 223–244. https://doi.org/10.1108/09564231311326978 DOI: https://doi.org/10.1108/09564231311326978

van Doorn, J., et al. (2010). Customer Engagement Behavior: Theoretical Foundations and Research Directions. Journal of Service Research, 13, 253–266. Https://Doi.Org/10.1177/1094670510375599 DOI: https://doi.org/10.1177/1094670510375599

Şenyapar, H. N. D. (2024). Artificial Intelligence in Marketing Communication: A Comprehensive Exploration of the Integration and Impact of AI. Technium Social Sciences Journal, 55, 64–81. https://doi.org/10.47577/tssj.v55i1.10651 DOI: https://doi.org/10.47577/tssj.v55i1.10651

Żyminkowska, K., Perek-Białas, J., and Humenny, G. (2023). The Effect of Product Category on Customer Motivation for Customer Engagement Behaviour. International Journal of Consumer Studies, 47, 299–316. https://doi.org/10.1111/ijcs.12837 DOI: https://doi.org/10.1111/ijcs.12837

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Published

2025-12-25

How to Cite

Mahaveerakannan R, Adhau, S. P., P. Ramya, Gade, N. V. R., M. Saravanan, & Immanuel D, J. (2025). ASSESSING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON VISUAL MARKETING MANAGEMENT. ShodhKosh: Journal of Visual and Performing Arts, 6(4s), 582–592. https://doi.org/10.29121/shodhkosh.v6.i4s.2025.6973