Charting the course: embracing challenges and anticipating future trends in building AI capacity for marketing excellence in emerging markets
DOI:
https://doi.org/10.25077/amar.8.2.44-64.2024Keywords:
Artificial Intelligence, Emerging Markets, AI Capacity, MarketingAbstract
The marketing landscape is undergoing a profound transformation with the emergence of artificial intelligence as a game-changer in driving innovation and customer engagement. Businesses are strategically integrating AI-powered solutions into their marketing decision-making to gain a competitive edge. Marketers are increasingly recognizing the immense potential of AI in enhancing their ability to identify competitors, understand customer preferences, and uncover valuable insights. The application of AI in marketing spans intelligent content generation, predictive analytics, personalized customer experiences, and automated campaign optimization. However, successful implementation of AI in marketing comes with its own set of challenges. This study aims to explore the evolving dynamics of AI in marketing, delve into its transformative impact, and identify key considerations for businesses looking to effectively harness this technological revolution by embracing challenges and anticipating new trends in AI adoption for achieving excellence in emerging markets.
References
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Boustani, N.M. (2022). Artificial intelligence impact on banks clients and employees in an Asian developing country. Journal of Asia Business Studies, 16(2), 267-278. https://doi.org/10.1108/JABS-09-2020-0376
Brueck, C. (2024). The role of foreign MNEs in China’s twin transition: a study on the organization of green and digital innovation processes. Competitiveness Review, 34(7), 44-60. https://doi.org/10.1108/CR-08-2023-0207
Cannavale, C., Esempio Tammaro, A., Leone, D. and Schiavone, F. (2022). Innovation adoption in inter-organizational healthcare networks – the role of artificial intelligence. European Journal of Innovation Management, 25(6), 758-774. https://doi.org/10.1108/EJIM-08-2021-0378
Chawla, Y., Shimpo, F. and Sokołowski, M.M. (2022). Artificial intelligence and information management in the energy transition of India: lessons from the global IT heart. Digital Policy, Regulation and Governance, 24(1), 17-29. https://doi.org/10.1108/DPRG-05-2021-0062
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Emerald Publishing. (2020). About Emerald. Retrieved June 5, 2024 from https://www.emeraldgrouppublishing.com/
Emerald Publishing. (2021). Our journals. Retrieved June 5, 2024 from https://www.emeraldgrouppublishing.com/our-journals
Eriksson, T., Bigi, A. and Bonera, M. (2020). Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation. The TQM Journal, 32(4), 795-814. https://doi.org/10.1108/TQM-12-2019-0303
Gao, J., Ren, L., Yang, Y., Zhang, D. and Li, L. (2022). The impact of artificial intelligence technology stimuli on smart customer experience and the moderating effect of technology readiness. International Journal of Emerging Markets, 17(4), 1123-1142. https://doi.org/10.1108/IJOEM-06-2021-0975
Guercini, S. (2023). Marketing automation and the scope of marketers' heuristics. Management Decision, 61(13), 295-320. https://doi.org/10.1108/MD-07-2022-0909
Gupta, Y. and Khan, F.M. (2024). Role of artificial intelligence in customer engagement: a systematic review and future research directions. Journal of Modelling in Management, ahead-of-print(ahead-of-print. https://doi.org/10.1108/JM2-01-2023-0016
Haleem, A., Javaid, M., Qadri, M A., Singh, R P., & Suman, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks 3, 3, 119-132. https://doi.org/10.1016/j.ijin.2022.08.005
Han, R., Lam, H.K.S., Zhan, Y., Wang, Y., Dwivedi, Y.K. and Tan, K.H. (2021). Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions. Industrial Management & Data Systems, 121(12), 2467-2497. https://doi.org/10.1108/IMDS-05-2021-0300
Handoko, I. and Tjaturpriono, H.A. (2023). The evolution of organizational design: the case of digital startups. International Journal of Emerging Markets, ahead-of-print (ahead-of-print. https://doi.org/10.1108/IJOEM-05-2022-0847
Harzing, A. W., & Alakangas, S. (2016). Google Scholar, Scopus and the Web of Science: A longitudinal and cross-disciplinary comparison. Scientometrics, 106(2). 787-804. https://doi.org/10.1007/s11192-015-1798-9
International Finance Corporation. (2020). Artificial Intelligence in Emerging Markets—Opportunities, Trends, and Emerging Business Models. Retrieved May 27, 2024, from https://www.ifc.org/en/insights-reports/2020/artificial-intelligence-in-emerging-markets.
Kang, J., Diao, Z. and Zanini, M.T. (2021). Business-to-business marketing responses to COVID-19 crisis: a business process perspective. Marketing Intelligence & Planning, 39(3), 454-468. https://doi.org/10.1108/MIP-05-2020-0217
Karimova, G.Z. and Goby, V.P. (2021). The adaptation of anthropomorphism and archetypes for marketing artificial intelligence. Journal of Consumer Marketing, 38(2), 229-238. https://doi.org/10.1108/JCM-04-2020-3785
Khan, A.W. and Mishra, A. (2024). AI credibility and consumer-AI experiences: a conceptual framework. Journal of Service Theory and Practice, 34(1), 66-97. https://doi.org/10.1108/JSTP-03-2023-0108
Kietzmann, J. and Pitt, L.F. (2020). Computerized content analysis of online data – opportunities for marketing scholars and practitioners. European Journal of Marketing, 54(3), 473-477. https://doi.org/10.1108/EJM-01-2020-0007
Korinek, A., & Stiglitz, J E. (2021). Artificial Intelligence, Globalization, and Strategies for Economic Development. National Bureau of Economic Research, Working Paper, 28453. https://doi.org/10.3386/w28453
Kowalkowski, C., Wirtz, J. and Ehret, M. (2024). Digital service innovation in B2B markets. Journal of Service Management, 35(2), 280-305. https://doi.org/10.1108/JOSM-12-2022-0403
Kulkov, I. (2023). Next-generation business models for artificial intelligence start-ups in the healthcare industry. International Journal of Entrepreneurial Behavior & Research, 29(4), 860-885. https://doi.org/10.1108/IJEBR-04-2021-0304
Ledro, C., Nosella, A. and Vinelli, A. (2022). Artificial intelligence in customer relationship management: literature review and future research directions. Journal of Business & Industrial Marketing, 37(13), 48-63. https://doi.org/10.1108/JBIM-07-2021-0332
Liu, S.Q., Vakeel, K.A., Smith, N.A., Alavipour, R.S., Wei, C.(V). and Wirtz, J. (2024). AI concierge in the customer journey: what is it and how can it add value to the customer? Journal of Service Management, 35(6), 136-158. https://doi.org/10.1108/JOSM-12-2023-0523
Malhotra, G. and Ramalingam, M. (2023). Perceived anthropomorphism and purchase intention using artificial intelligence technology: examining the moderated effect of trust. Journal of Enterprise Information Management, (ahead-of-print). https://doi.org/10.1108/JEIM-09-2022-0316
Marino, D., Gil Lafuente, J. and Tebala, D. (2023). Innovations and development of artificial intelligence in Europe: some empirical evidences. European Journal of Management and Business Economics, 32(5), 620-636. https://doi.org/10.1108/EJMBE-03-2023-0085
Massa, S., Annosi, M.C., Marchegiani, L. and Messeni Petruzzelli, A. (2023). Digital technologies and knowledge processes: new emerging strategies in international business: A systematic literature review. Journal of Knowledge Management, 27(11), 330-387. https://doi.org/10.1108/JKM-12-2022-0993
Mathur, V., Purkayastha, S., & Gichoya, J W. (2020). Artificial Intelligence for Global Health: Learning From a Decade of Digital Transformation in Health Care. Paper presented at the International Conference on Learning Representations. Full paper retrieved from https://www.researchgate.net/publication/341668299_Artificial_Intelligence_for_Global_Health_Learning_From_a_Decade_of_Digital_Transformation_in_Health_Care
Mogaji, E. and Nguyen, N.P. (2022). Managers' understanding of artificial intelligence in relation to marketing financial services: insights from a cross-country study. International Journal of Bank Marketing, 40(6), 1272-1298. https://doi.org/10.1108/IJBM-09-2021-0440
Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics, 106(1). 213-228. https://doi.org/10.1007/s11192-015-1765-5
Mou, Y., Gong, Y. and Ding, Z. (2024). Complement or substitute? A study of the impact of artificial intelligence on consumers’ resistance. Marketing Intelligence & Planning, 42(4), 647-665. https://doi.org/10.1108/MIP-04-2023-0187
Mrad, M., Ramadan, Z. and Nasr, L.I. (2022). Computer-generated influencers: the rise of digital personalities. Marketing Intelligence & Planning, 40(5), 589-603. https://doi.org/10.1108/MIP-12-2021-0423
Paesano, A. (2023). Artificial intelligence and creative activities inside organizational behavior. International Journal of Organizational Analysis, 31(5), 1694-1723. https://doi.org/10.1108/IJOA-09-2020-2421
Paschen, J., Kietzmann, J. and Kietzmann, T.C. (2019). Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of Business & Industrial Marketing, 34(7), 1410-1419. https://doi.org/10.1108/JBIM-10-2018-0295
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Published
2024-12-31
How to Cite
Septeanny, P., Sulungbudi, B. M. and Alijoyo, F. A. (2024) “Charting the course: embracing challenges and anticipating future trends in building AI capacity for marketing excellence in emerging markets”, AMAR (Andalas Management Review), 8(2), pp. 44–64. doi: 10.25077/amar.8.2.44-64.2024.
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