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Other literature type . 2025
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2025
License: CC BY
Data sources: Datacite
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The Future of Digital Marketing in Yemen Amidst AI Developments: A Theoretical Foresight Study

Authors: Sakher Farea Ghaleb Algonaid; Hani Gamil Mohammed Murshed;

The Future of Digital Marketing in Yemen Amidst AI Developments: A Theoretical Foresight Study

Abstract

This foresight study explores the future of digital marketing in Yemen in light of the rapid global advancements in artificial intelligence. Employing a theoretical and analytical methodology, the study assesses the current situation through a SWOT analysis, revealing a young and growing digital base confronted by structural challenges such as weak infrastructure, a shortage of specialized skills, and difficult economic conditions. The study aims to bridge a knowledge gap concerning how the Yemeni market can leverage the potential of artificial intelligence such as campaign automation, hyper-personalization, and data analysis—despite these obstacles. Through an analysis of supporting and hindering factors, the study presents three potential future scenarios for the period (2025-2035): Slow Growth (under the continuation of the status quo), Accelerated Growth (with improved conditions and adoption of practical applications), and a Quantum Leap scenario (in the event of comprehensive stability and significant investment). It concludes that achieving any meaningful growth is contingent upon stability and investment in human capital and digital infrastructure. The study concludes by presenting a set of practical recommendations for decision-makers and business owners to harness these technologies in support of economic recovery and building digital competitiveness. Keywords: Digital Marketing, Artificial Intelligence, Foresight Study, Yemen.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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