AI, Platforms and Brand Loyalty: What X and Threads Reveal About Consumer Engagement
In a groundbreaking study, LAU scholars identify key differences in branding content across two microblogging platforms that can inform more efficient future marketing strategies.
In this fast-paced era of digital transformation, generative AI content is increasingly influencing branding strategies and customer behavior on microblogging platforms. While these effects have thus far been underresearched in emerging platforms, an LAU-led study sets a precedent for future studies on the role of AI in consumer-brand connections, focusing on two popular platforms: X and Threads.
Published in the Marketing Intelligence & Planning, the qualitative study, “The role of generative AI in shaping consumer brand relationships,” was authored by Dr. Zahy Ramadan, associate professor of marketing and Dr. Maya Farah, professor of marketing and assistant dean at LAU’s Adnan Kassar School of Business, along with PhD student Yaman Nassereddine (MBA ’24).
“By empirically examining Threads alongside X, this study positions LAU at the forefront of research on emerging digital platforms that are already influencing consumer behavior but remain largely underexplored academically,” said Dr. Ramadan. “It demonstrates LAU’s commitment to anticipatory, forward-looking research rather than retrospective analysis.”
The research, which provides deep insights into user sentiment, focused on brands that publicly disclosed their use of AI. It was based on in-depth interviews with 70 users to map out the phases in key consumer journeys: Awareness, engagement, purchase and loyalty. Participants included 40 respondents who interacted with brands that did not use generative AI and 30 users who engaged with brands that did. All interviewees used both platforms.
The scholars identified key differences in user loyalty and interaction with AI-driven brands on X (formerly Twitter) and Threads. Based on the findings, they concluded that the platform was as important as the technology in engaging consumers.
According to the data, although generative AI content on X was critical in promoting awareness and purchase, the depth of perceived user engagement was adversely impacted as interactions became “less centered on long-term community development and more transactional.”
In contrast, user engagement and loyalty to brands were “noticeably higher” on Threads, especially for non-AI-driven content—a pattern the authors explain was driven by the platform’s focus on community and visual storytelling, which enabled more meaningful and lasting connections.
However, although Threads gives brands the chance to build more personal and in-depth relationships, the challenge is to translate this engagement into fast, immediate purchases.
Based on these differences, the study recommends that marketers implement platform-specific strategies and move away from a “one-size-fits-all” approach to AI-driven content. An example is using AI on X for immediate impact while focusing on in-depth consumer interactions on Threads to build long-lasting relationships.
“Generative AI is not inherently effective or ineffective; its impact depends on how well it aligns with platform-specific logics and user gratifications,” the data showed.
According to Dr. Farah, this gap in user experience between X and Threads can be explained primarily by differences in platform affordances, defined as the capabilities and restrictions made by the digital platform that determine how users and businesses can communicate, and user motivations.
“X is structured around speed, immediacy, and information flow,” said Dr. Farah. “Prior research shows that such environments favor content that is concise, repetitive, and algorithmically optimized for visibility.”
Subsequently, she added, when personalized and automated, AI-generated brand content aligns well with this logic, thus allowing brands to surface quickly and repeatedly in users’ feeds.
“As a result, AI-driven brands are noticed faster on X, especially at the awareness stage of the consumer journey. By contrast, Threads is organized around visual storytelling, community formation, and extended conversations,” she explained.
One of the study’s more surprising findings for the researchers was the “clear decoupling between engagement and conversion.” While Threads users reported hours-long engagement with AI-generated brand content, it rarely translated into purchase behavior, noted Dr. Farah.
“Conversely, on X, users often reported limited emotional attachment to AI-driven content, yet it was significantly more effective in driving brand recall and purchase decisions,” she added.
This finding challenges the “widespread assumption that higher engagement necessarily leads to stronger commercial performance and underscores the need for more nuanced impact metrics.”
The idea for the study started with a simple observation, said Dr. Ramadan, “brands are embracing generative AI much faster than we are studying its real impact on people. Yet we still know very little about how individuals actually feel about, interpret, or engage with this type of content. As researchers, we found this gap between what brands are doing and what academia is examining increasingly difficult to ignore.”
What distinguishes the research is that it sheds light on emerging platforms that are rarely studied at the early stages of their evolution, despite their early impact in shaping user expectations and interaction habits.
“Studying AI-driven brand communication while these platforms are still evolving allows us to better understand how early interactions may influence long-term relationships between brands and users,” he said.
For academic institutions in the region, including LAU, this research is significant, as it also underscores the presence of a digitally advanced population in the MENA region that can serve as a case study.
“It allows universities to engage with global technological changes from a regional perspective, rather than treating them as distant or purely Western developments,” said Dr. Ramadan. The Middle East is digitally advanced, socially active, and culturally diverse, which makes it a valuable context for understanding how people respond to AI-driven communication in everyday digital life.”
The study opens multiple avenues for future research, including demographic differences, causal mechanisms behind the observed gap between engagement and conversion, and consumer-to-consumer interactions around AI-generated content.
“The current study can also be expanded to other under-researched or decentralized platforms and enhance understanding of how generative AI reshapes digital culture, trust, and brand meaning across evolving ecosystems,” said Dr. Farah.