Using artificial intelligence in digital branding: a two-phase qualitative approach

Purpose Artificial intelligence (AI) plays a crucial role in executing marketing tasks such as identifying risks, targeting customers, advertising brands and optimizing pricing for maximum profit. In today's digital age, AI's presence in communication and marketing channels has had a substantial impact. Experts and scholars contend that the growing use of AI in analyzing big data, employing machine learning, analyzing social media, making algorithmic decisions, modeling and simulating has significantly influenced brand presentation in the global market. As a result, AI greatly changes brand preferences, marketing strategies and customer attitudes. This research primarily aims to explore the persuasive effects, methods, advancements and challenges of implementing AI in digital branding. Design/methodology/approach To address the research questions, a two-phase qualitative study has been conducted. The study's first phase involved a systematic literature review. The databases Scopus and Web of Science were used, resulting in an initial collection of 3,983 studies. These studies were then filtered through Preferred Reporting Items for Systematic Reviews and Meta-Analyses, including an evaluation of titles and abstracts, quality assessment and the application of ten specific criteria, ultimately narrowing the selection to 78 articles. In the second phase, 17 experts in AI and digital branding were selected for semi-structured interviews. The data from both phases were analyzed by thematic analysis. Findings Key themes related to the application of AI in branding include scalable computational algorithms, machine learning, reinforcement learning algorithms, search algorithms, operational automation, recommendation algorithms, data interpretation and processing, human–computer interaction algorithms and AI-based platforms. The transformations due to AI in branding involve dynamic digital marketing, changes in distribution channels, personalized brand communications, dynamic pricing, adaptive business strategies, enhanced cybersecurity, development of internal and external databases, improved customer experiences, strengthened brand positioning and status, advancements in organizational processes and systems, improved decision-making quality, brand globalization, the creation of digital business models and added value creation. Originality/value This is the first study to use a multi-method qualitative approach to explore the functionalities of AI in branding.

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Publication Details

Journal
EuroMed Journal of Business
Published
2026-01-05
DOI
https://doi.org/10.1108/emjb-12-2024-0353
Primary Topic
AI in Service Interactions
Type
article
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article

Using artificial intelligence in digital branding: a two-phase qualitative approach

Mohammad Reza Jalilvand, Jamileh Ataei
EuroMed Journal of Business
AI in Service Interactions
article

Using artificial intelligence in digital branding: a two-phase qualitative approach

Mohammad Reza Jalilvand, Jamileh Ataei
article en

Abstract

Purpose Artificial intelligence (AI) plays a crucial role in executing marketing tasks such as identifying risks, targeting customers, advertising brands and optimizing pricing for maximum profit. In today's digital age, AI's presence in communication and marketing channels has had a substantial impact. Experts and scholars contend that the growing use of AI in analyzing big data, employing machine learning, analyzing social media, making algorithmic decisions, modeling and simulating has significantly influenced brand presentation in the global market. As a result, AI greatly changes brand preferences, marketing strategies and customer attitudes. This research primarily aims to explore the persuasive effects, methods, advancements and challenges of implementing AI in digital branding. Design/methodology/approach To address the research questions, a two-phase qualitative study has been conducted. The study's first phase involved a systematic literature review. The databases Scopus and Web of Science were used, resulting in an initial collection of 3,983 studies. These studies were then filtered through Preferred Reporting Items for Systematic Reviews and Meta-Analyses, including an evaluation of titles and abstracts, quality assessment and the application of ten specific criteria, ultimately narrowing the selection to 78 articles. In the second phase, 17 experts in AI and digital branding were selected for semi-structured interviews. The data from both phases were analyzed by thematic analysis. Findings Key themes related to the application of AI in branding include scalable computational algorithms, machine learning, reinforcement learning algorithms, search algorithms, operational automation, recommendation algorithms, data interpretation and processing, human–computer interaction algorithms and AI-based platforms. The transformations due to AI in branding involve dynamic digital marketing, changes in distribution channels, personalized brand communications, dynamic pricing, adaptive business strategies, enhanced cybersecurity, development of internal and external databases, improved customer experiences, strengthened brand positioning and status, advancements in organizational processes and systems, improved decision-making quality, brand globalization, the creation of digital business models and added value creation. Originality/value This is the first study to use a multi-method qualitative approach to explore the functionalities of AI in branding.

EuroMed Journal of Business
University of Tehran (IR)
Openalex Percentile: Top 96%
AI in Service Interactions
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