Article Dans Une Revue International Journal of Engineering Trends and Technology Année : 2025

Artificial Intelligence for Data-Driven Marketing: Catalyst for Digital Business Transformation

Résumé

In this study, the use of AI in marketing in Morocco is assessed, showcasing the disparity in the use of this technology per sector. Adoption is very advanced in the Banking and E-commerce sectors (92% and 78%, respectively), where chatbots and predictive analytics are used, achieving an ROI of 3.2 years. In contrast, SMEs and other traditional sectors have much more difficulty (23% adoption) because of the initial investment of 380,000 MAD on average and the local expertise drain (only 12% of the trainers in academia have any knowledge about AI).SMEs sit within the longest timeframes (3.2 years) to see positive ROI, while large companies see it in 1.8 years, highlighting the disparity of digital maturity in sectors. 367 professionals from diverse sectors participated in the survey, and the quantitative results show the positive impact of AI on performance, achieving a 22% decrease in acquisition costs, 34% increase in customer satisfaction, and 27% increase in marketing ROI. Additional barriers encumber the expected results, including cultural (scepticism from 44% of managers) and geographic (78% of all projects are concentrated in Casablanca and Rabat).Using a score of 3.2/5 for Adoption, Morocco is ranked higher than Egypt, 3.0, but still lacks behind South Africa, 3.8, which possesses a more advanced technological ecosystem. To boost adoption, the study recommends: (1) Partnerships between universities and businesses to provide custom training, (2) A policy for the rational use of data, and (3) Local, affordable (language, mobile-first) tailored pockets for the informal sector/SMEs.Based on the above, the promise AI offers Morocco is tangible, but not without the need for customized and differentiated policies to address interregional and inter-sector imbalance. For this to happen, coordinated action from the public and private sectors and academia will be necessary to support the shift.

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hal-05383511 , version 1 (26-11-2025)

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Sanaa Dfouf, Kaoutar Errakha, Hanan Elharissi, Mohammed Khaouja, Fekkak Hamdi. Artificial Intelligence for Data-Driven Marketing: Catalyst for Digital Business Transformation. International Journal of Engineering Trends and Technology , 2025, ⟨10.14445/22315381/IJETT-V73I11P102⟩. ⟨hal-05383511⟩
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