International Peer-Reviewed Journal•Open Access•ISSN 2456-8880
irejournals@gmail.com•+91-7433024337

Home / Current Issue / Paper 1715914

1715914 Vol 9 · Issue 10 Download Paper

Investigating AI Integration Within the Indian Wedding Industry

Dr. Rakshita. M Allappanavar Ujwal P Arha Jain Riya Modi Vaibhav Shaw

Subject area: Science,Engineering and Technology  ·  Area of research: Artificial Intelligence

DOI: 10.64388/IREV9I10-1715914

Abstract

The Indian wedding market has an estimated revenue of USD 50-75 Billion per annum and caters to about 10 million marriages every year. Though the industry has conventionally been based on personal recommendation and local supplier systems, online systems are quickly changing the process of the couple planning, as well as the manner in which suppliers act. The paper reviews descriptions of the use of artificial intelligence (AI) to reshape the factor dictating the success of the Indian digital wedding industry through the profiling of ten websites: WedMeGood, ShaadiSaga, WeddingWire India, The Knot Worldwide, Zola, Joy Wedding App, WeddingHappy, Appy Couple, Hitchd, and Loverly. Based on a method of secondary data, which involves the utilisation of industry reports, scholarly studies, and company correspondence, the research evaluates AI usages in vendor recommendation systems, personalisation algorithms, chatbots, image tagging, and budgeting software. The article is based on the Technology Acceptance Model and the Platform Economy theory. The results show that AI has optimised the search of vendors, personalisation of planning and engagement of users across the platforms. Nevertheless, the paper also finds some difficulties that are deeply unique to the Indian context, such as biasing algorithms, issues with data privacy and inequalities in access to digital technologies, and cultural diversity that cannot be easily generalized using algorithms.

Keywords

artificial intelligence, Indian wedding industry, digital platform, matching of vendors, platform economy, personalisation, WedMeGood.

References

[1] Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427–445. https://doi.org/10.1007/s12525-020-00414-7

[2] Buhalis, D., & Sinarta, Y. (2019). Real-time co-creation and nowness service: Lessons from tourism and hospitality. Journal of Travel & Tourism Marketing, 36(5), 563–582. https://doi.org/10.1080/10548408.2019.1592059

[3] Crunchbase. (2023). Zola company profile and funding rounds. https://www.crunchbase.com/organization/zola

[4] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

[5] Dellarocas, C. (2020). Designing platforms for AI development: The data network effect. Communications of the ACM, 63(4), 32–34. https://doi.org/10.1145/3381755

[6] Eisenmann, T., Parker, G., & Van Alstyne, M. W. (2006). Strategies for two-sided markets. Harvard Business Review, 84(10), 92–101.

[7] Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519

[8] Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in Human Behavior, 97, 304–316. https://doi.org/10.1016/j.chb.2019.01.020

[9] 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

[10] Inc42. (2022). WedMeGood's technology growth and funding rounds. Inc42 Media. https://inc42.com

[11] Keniston, K., & Kumar, D. (Eds.). (2004). IT experience in India: Bridging the digital divide. Sage Publications.

[12] KPMG. (2022). Indian wedding industry report: Market size, trends, and digital transformation. KPMG India.

[13] Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy and how to make them work for you. W. W. Norton & Company.

[14] Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115–143. https://doi.org/10.2307/25148720

[15] Rauch, M., Scholl-Grissemann, U., & Mathmann, F. (2021). Technology acceptance of AI-based wedding planning tools: An extended TAM perspective. Journal of Hospitality and Tourism Technology, 12(3), 489–508. https://doi.org/10.1108/JHTT-09-2020-0234

[16] Ricci, F., Rokach, L., & Shapira, B. (2015). Recommender systems: Introduction and challenges. In F. Ricci, L. Rokach, & B. Shapira (Eds.), Recommender systems handbook (2nd ed., pp. 1–34). Springer. https://doi.org/10.1007/978-1-4899-7637-6_1

[17] Rochet, J. C., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990–1029. https://doi.org/10.1162/154247603322493212

[18] The Knot Worldwide. (2022). 2022 annual report. The Knot Worldwide Inc.

[19] Tussyadiah, I. P. (2020). A review of research into automation in tourism. Annals of Tourism Research, 81, 102883. https://doi.org/10.1016/j.annals.2020.102883

How to cite this paper

Dr. Rakshita. M Allappanavar, Ujwal P, Arha Jain, Riya Modi, Vaibhav Shaw "Investigating AI Integration Within the Indian Wedding Industry" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 18-24 https://doi.org/10.64388/IREV9I10-1715914
Dr. Rakshita. M Allappanavar, Ujwal P, Arha Jain, Riya Modi, Vaibhav Shaw "Investigating AI Integration Within the Indian Wedding Industry" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026, doi: https://doi.org/10.64388/IREV9I10-1715914
Dr. Rakshita. M Allappanavar, Ujwal P, Arha Jain, Riya Modi, Vaibhav Shaw (2026). Investigating AI Integration Within the Indian Wedding Industry. Iconic Research And Engineering Journals, 9(10). doi: https://doi.org/10.64388/IREV9I10-1715914
Dr. Rakshita. M Allappanavar, Ujwal P, Arha Jain, Riya Modi, Vaibhav Shaw "Investigating AI Integration Within the Indian Wedding Industry" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026. Crossref, https://doi.org/10.64388/IREV9I10-1715914
@article{1715914,
      author = {Dr. Rakshita. M Allappanavar, Ujwal P, Arha Jain, Riya Modi, Vaibhav Shaw},
      title = {Investigating AI Integration Within the Indian Wedding Industry},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {18-24},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715914.pdf},
      abstract = {The Indian wedding market has an estimated revenue of USD 50-75 Billion per annum and caters to about 10 million marriages every year. Though the industry has conventionally been based on personal recommendation and local supplier systems, online systems are quickly changing the process of the couple planning, as well as the manner in which suppliers act. The paper reviews descriptions of the use of artificial intelligence (AI) to reshape the factor dictating the success of the Indian digital wedding industry through the profiling of ten websites: WedMeGood, ShaadiSaga, WeddingWire India, The Knot Worldwide, Zola, Joy Wedding App, WeddingHappy, Appy Couple, Hitchd, and Loverly. Based on a method of secondary data, which involves the utilisation of industry reports, scholarly studies, and company correspondence, the research evaluates AI usages in vendor recommendation systems, personalisation algorithms, chatbots, image tagging, and budgeting software. The article is based on the Technology Acceptance Model and the Platform Economy theory. The results show that AI has optimised the search of vendors, personalisation of planning and engagement of users across the platforms. Nevertheless, the paper also finds some difficulties that are deeply unique to the Indian context, such as biasing algorithms, issues with data privacy and inequalities in access to digital technologies, and cultural diversity that cannot be easily generalized using algorithms.},
      keywords = {artificial intelligence, Indian wedding industry, digital platform, matching of vendors, platform economy, personalisation, WedMeGood.},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1715914}
  }