Systematic Literature Review on Application, Challenges, and Future Directions of Artificial Intelligence in Marketing

Dong Siyu, Basheer Al-Haimi () and Lu Juyan
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Dong Siyu: University Technology Malaysia, Azman Hashim International Business School
Basheer Al-Haimi: University Technology Malaysia, Azman Hashim International Business School
Lu Juyan: University Technology Malaysia, Azman Hashim International Business School

A chapter in Business and Sustainable Development in a Globalized and Digitalized Era, 2026, pp 468-486 from Springer

Abstract: Abstract Artificial Intelligence (AI) is transforming marketing by improving customization, efficiency, and consumer engagement, while also raising new managerial and ethical challenges. This systematic review, conducted following PRISMA guidelines and analyzing research papers from 2019 to 2024, consolidates scattered insights into a clear framework for understanding AI in marketing. It highlights four main applications: customer analysis, content creation, campaign management, and customer service. Unlike earlier reviews that focused narrowly on specific marketing areas, this paper combines these applications with related adoption issues such as ethical, legal, and social concerns, data quality and security, and human-AI collaboration, along with future directions. These include responsible AI implementation, advancements in generative and predictive technologies, hybrid human-AI teamwork, and the development of regulations and ethical guidelines. By providing this comprehensive perspective, the review underscores that sustainable competitive advantage in the digital age depends not only on technological progress but also on building consumer trust and maintaining ethical standards. This integrated approach paves the way for future research and helps practitioners adopt AI responsibly, fostering innovation and sustainable growth in marketing.

Keywords: Artificial Intelligence (AI); Marketing; Applications; challenges; future direction; Systematic Literature Review (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-29346-6_23

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