AI storytelling for global consumers: does it improve luxury brand experience and what is the role of culture?

Modern consumers increasingly seek meaningful, immersive, and authentic experiences, prompting brands, especially in the luxury industry, to prioritize bespoke brand experiences (Tarquini et al., 2022). In today's global luxury market, brands are placing greater emphasis on customers cultural backgrounds, recognizing that cultural sensitivity enhances the brand experience (Bai et al., 2022; Nie and Wang, 2021). To personalize experiences across diverse markets, luxury brands are seeking strategies to account for local cultural contexts (Hong et al., 2023; Rao-Nicholson and Khan, 2017). In this context, businesses increasingly view artificial intelligence (AI) as a promising tool for delivering engaging, culturally relevant luxury experiences (Chow et al., 2025).

AI creates novel opportunities for luxury brands to fulfill consumer demands for novelty, personalization, and exclusivity (Rahman et al., 2023; Xu and Mehta, 2022). Specifically, generative AI (GenAI) offers an opportunity to learn from data and generate new content in various forms, such as text, images, music, audio, and video (Wen et al., 2024). For luxury brands, GenAI enables more engaging content and changes how they interact with consumers (Chan and Choi, 2025).

AI storytelling is one such innovation that offers luxury brands a new opportunity to enhance brand experience. Traditionally, storytelling is a tool for brands to generate meaning that shapes interpretations of past, present, and future events, while conveying socially constructed meanings to others (Júnior et al., 2023). With GenAI, individuals can experience their own self-directed storytelling. By formulating their own inquiries, such as questions about history, craftsmanship, or values, users can receive personalized storytelling generated by AI. For example, users can input prompts such as “What is the brand's biggest inspirational value?” to receive a tailored answer. One example of such technology is BrunelloCucinelli.ai, an AI-powered platform developed by an Italian luxury fashion brand. It is designed exclusively to allow visitors from all over the world to explore the brand's philosophy, its founder, and the company's story in a personalized manner (Vogue, 2024).

AI storytelling may benefit the luxury brand experience in numerous ways. It satisfies luxury consumers' need for personalization and customization (Venkatesh et al., 2010) by creating an opportunity for one-on-one storytelling with the brand. Thus, AI may help address the question of how digital technologies enable luxury brands to internationalize while maintaining high levels of personalization for global consumers (Katsikeas et al., 2020). As luxury is no longer reserved for the ultra-rich, AI storytelling enables brands to build experiences not only for core buyers but also for occasional consumers, such as luxury excursionists worldwide (Dubois et al., 2021). However, the literature on implementing AI in luxury brands' operations, such as product or advertisement development, shows that consumers may react negatively to AI, perceiving lower effort and authenticity (To et al., 2025) and a diminished brand essence (Xu and Mehta, 2022). This undesirable effect is particularly pronounced for luxury brands that rely heavily on emotional value (Xu and Mehta, 2022). This may challenge the brand experience, as luxury storytelling traditionally creates an emotional connection between the brand and its audience (Kim et al., 2016).

Brand storytelling is inherently cultural, shaped by myths and archetypes (Woodside et al., 2008). This cultural factor makes international marketing particularly challenging, as global brands typically choose between adopting a globalized message or tailoring their communication to local cultural contexts (Nie and Wang, 2021; Rao-Nicholson and Khan, 2017). Recent literature, however, suggests that this binary distinction is increasingly outdated, as digital technologies enable brands to pursue both approaches simultaneously (Hoyer et al., 2020; Katsikeas et al., 2020). In particular, integrating AI into storytelling may facilitate cultural adaptation by providing personalized, culturally relevant content (Kopalle et al., 2022; Huang and Rust, 2022). Despite these advantages, the use of AI in culturally adaptive storytelling also presents potential risks. These include varying levels of AI acceptance across countries (Hoyer et al., 2020), potential algorithmic bias (Kopalle et al., 2022), psychological resistance due to the uncanny valley effect (Oliveira et al., 2024), the “black box” nature of AI decision-making (Grewal et al., 2021), and the lack of human emotionality in AI-driven interactions (Wien and Peluso, 2021), to name a few. These considerations lead to the following research questions:

Methodologically, the study adopts a qualitative approach and collects data through 30 semi-structured interviews. The study contributes to the literature by introducing the concept of AI storytelling, a phenomenon that remains underexplored due to its novelty. The paper discusses both the potential of AI storytelling to enrich the brand experience and the ways it may complicate it. Thus, we contribute to the ongoing debate on AI's compatibility with the luxury industry by offering a consumer perspective on AI storytelling in the luxury sector. Additionally, this study raises a novel question for cultural branding in luxury: consumers, aware of AI's personalization capabilities, expect luxury storytelling to reflect their cultural background. From a managerial perspective, our research guides luxury brand managers on effective practices and potential pitfalls when integrating AI into brand storytelling.

Brand experience refers to the subjective consumer responses evoked by specific brand-related experiential stimuli (design, packaging, marketing communications) across various settings, such as when consumers interact with, shop for, and consume brands (Brakus et al., 2009). These responses arise across multiple experiential dimensions. For example, sensory dimension (also called sense, sensorial, or physical) involves immediate impressions formed through sight, sound, touch, taste, or smell (Gentile et al., 2007; Schmitt, 1999). Emotional dimension (also called “feel” or “affective”) encompasses the moods, feelings, and emotional responses a brand elicits (Brakus et al., 2009; Dubé and Le Bel, 2003). Intellectual dimension (also named “think”, or “cognitive”) relates to mental engagement, curiosity, and problem-solving triggered by brand interactions (Dubé and Le Bel, 2003; Schmitt, 1999). The behavioral dimension (“act” or “pragmatic”) reflects physical actions, usability, and bodily participation (Brakus et al., 2009; Gentile et al., 2007). Finally, social dimension (“relate” or “relational”) refers to how brand experiences promote shared consumption, community building, and social identity signaling (Gentile et al., 2007; Schmitt, 1999).

In the luxury industry, intense brand experiences across all dimensions justify the exclusivity and premium value associated with luxury offerings (Kim, 2018). To communicate these attributes and to amplify the experiential impact, luxury storytelling is an important tool. Storytelling helps brands generate meaning that shapes interpretations of their past, present, and future events, while conveying socially constructed symbolism to others (Júnior et al., 2023). In the luxury sector, storytelling creates the “luxury dream” for consumers by highlighting the symbolic meaning of luxury (Dubois et al., 2021; Kim et al., 2016). It solidifies an emotional connection between the brand and its audience (Gurzki et al., 2019). It creates narrative transportation, a state in which consumers become immersed in the brand's story (Kim et al., 2016). Luxury brands tell their stories across many platforms: from traditional heritage stores (De Boissieu and Chaney, 2024) to social media (González Romo et al., 2017) and the metaverse (Hu et al., 2025).

Luxury brands are increasingly experimenting with AI-enabled storytelling. The operation of AI storytelling rests on two antecedents: brand-controlled inputs and system-level capabilities. Brand-controlled inputs are elements that firms deliberately embed in AI systems to shape narrative output. These include heritage cues (e.g. founder stories, craftsmanship, origin myths; Venkatesh et al., 2010; Li et al., 2026), esthetic codes such as tone of voice and stylistic expressions (Kim et al., 2020), and brand values and philosophies (Woodside et al., 2008). Together, these inputs anchor AI storytelling in a coherent brand identity. System-level capabilities refer to the technological properties that enable storytelling generation. These include generativity and personalization, as well as adaptiveness and real-time interactivity, which allow AI systems—powered by large language models—to produce contextually relevant, dialogic narratives (Dayo et al., 2023; Wen et al., 2024; Chan and Choi, 2025; Feng and Sun, 2026; Hermann and Puntoni, 2024). Multimodality and emotion modeling may further enhance the experiential richness of AI storytelling (Wen et al., 2024). Thus, the core of AI storytelling is dialogic personalization and co-creation. Rather than passively reading brand descriptions, users formulate their own inquiries—such as questions about brand history, craftsmanship, or values (e.g. “Tell me who and why founded the brand and why”)—and receive tailored responses. This dialogic format allows users to ask follow-up questions, transforming storytelling from a unidirectional process into an interactive experience (Woodside et al., 2008).

While AI storytelling draws on advances in GenAI (Hermann and Puntoni, 2024; Wen et al., 2024), it is conceptually distinct from adjacent digital communication formats and grounded in interdisciplinary research. From a communication perspective, AI storytelling reflects dialogic models of communication, in which understanding emerges through reciprocal interaction (such as turn-taking and grounding) rather than through one-way content delivery (Bergner et al., 2023). From a human–computer interaction perspective, AI storytelling differs from AI-driven personalization, which adapts content or recommendations based on inferred user preferences derived from browsing behavior, purchase history, and preferences. In contrast, AI storytelling relies on active, ongoing user requests rather than inferred preferences. This creates a shared agency between users and systems (Shneiderman, 2020). AI storytelling also differs from chatbots and AI assistants that are primarily task-oriented, utilitarian, and designed for efficiency (Grewal et al., 2021; Huang and Rust, 2022). Instead, AI storytelling is oriented toward experiential and symbolic engagement (Van Laer et al., 2019; Holt, 2004). Rather than completing a single task (such as providing a product price), it enables users to explore the brand through narrative dialog about, for example, its roots, history, philosophy, or founder in a story-like format. Further, research in digital narratology conceptualizes storytelling in digital environments as a dynamic process that unfolds through interaction rather than as a fixed, authored text (Koenitz, 2015; Lisboa et al., 2025). Accordingly, AI storytelling differs from branded content on websites or social media, which is firm-authored and static (Woodside et al., 2008; Hoyer et al., 2020), as AI-generated narratives adapt continuously in response to user input. At the same time, AI storytelling remains distinct from human storytelling, which involves human narrators engaging other humans through emotion, embodied presence, and socially performed cues (e.g. tone, gestures, and audience responsiveness) (Woodside et al., 2008; Longoni and Cian, 2022).

AI storytelling is expected to enhance the luxury brand experience across multiple dimensions. AI enables more innovative approaches to luxury storytelling that are personalized, interactive, and immersive (Dayo et al., 2023), further amplifying consumers' emotional and cognitive engagement (Van Laer et al., 2019). In particular, AI storytelling can enhance the intellectual experience by responding to personalized inquiries and evoking curiosity (Brakus et al., 2009; Dubé and Le Bel, 2003). With GenAI's creative capabilities (Chan and Choi, 2025), it can stimulate excitement and surprise, enriching the emotional dimension. Furthermore, its interactive nature, where users actively pose questions, can influence the behavioral dimension by encouraging participation. Given the variety of experience dimensions in the literature (Brakus et al., 2009; Dubé and Le Bel, 2003; Gentile et al., 2007), it is essential to assess which experience dimensions AI storytelling activates and the effects it has. Not all dimensions are equally affected by technology; Hoyer et al. (2020) suggest that AI particularly affects the cognitive, sensory/emotional, and social experience dimensions, offering new value when implemented effectively. This leads to our first research question: “How does AI storytelling influence luxury brand experience?”

Brand storytelling is a culturally situated activity rooted in myths, values, and archetypes (Woodside et al., 2008). Culture shapes how individuals think, communicate, and interpret brand meanings (Kim et al., 2023). Therefore, it is a central factor in global brand communication (Katsikeas et al., 2020). From a cultural branding perspective, strong brands communicate their identity through stories and cultural elements that are familiar to their audiences, such as symbols, images, language, and style (Holt, 2004). In international marketing, the strategic use of these codes has long been debated, particularly in relation to the tension between globalized (standardized) and localized communication strategies (Nie and Wang, 2021). Many global brands, especially in luxury, have historically favored standardized branding strategies to maintain brand consistency, reduce risk, and limit localization costs (Bai et al., 2022). However, societies differ in how they perceive and respond to globalization and standardization (Appadurai, 2000). As a result, standardized communication often fails to resonate with local consumers and may limit brands' cultural responsiveness (Bai et al., 2022). In contrast, localization strategies adapt brand communication to local symbols, language, and narratives, and cultural mixing approaches—where global brand meanings are combined with local cultural elements—have been shown to enhance brand evaluations (Nie and Wang, 2021; Rao-Nicholson and Khan, 2017).

Some scholars argue that the strict divide between globalization and localization is becoming outdated, as digital technologies now allow global brands to pursue both strategies simultaneously (Hoyer et al., 2020; Katsikeas et al., 2020). Specifically, AI technologies can help global brands deliver personalized and culturally tailored communication at scale (Huang and Rust, 2022; Kopalle et al., 2022). From a cultural branding perspective, these technologies enable brands to maintain a consistent core ideology and myth across international markets while selectively adapting to local cultural codes (Holt, 2004). From a technical perspective, AI systems can be trained on consumer data from diverse local markets and adapt content to regional contexts. For instance, text mining, sentiment analysis, emotion detection, and speech recognition are increasingly language-specific, reflecting a shift toward glocalization (Kopalle et al., 2022). AI can support the automated analysis of text, audio, images, and video to extract cultural nuances from unstructured data (Kopalle et al., 2022).

Brands create value by expressing ideologies, telling myths, and using cultural codes that consumers draw on to make sense of their consumption (Holt, 2004). Storytelling is the mechanism at the core of cultural branding because it is uniquely suited to translating, recombining, or localizing cultural myths and codes (Woodside et al., 2008). This is why AI storytelling merits attention in discussions of adaptation to different cultural contexts while preserving the brand's overarching ideological stance (Holt et al., 2004). GenAI can support the localization of brand websites by creating culturally adapted content (narratives, imagery, slogans) (Katsikeas et al., 2020; Kopalle et al., 2022). Such adaptation can enhance brand authenticity when consumers perceive indexical cues that signal fidelity to the brand's origins and existential cues that align with local identity needs (Morhart et al., 2015). AI-driven solutions can also reduce the risk of cultural offense by avoiding messages or products that conflict with local traditions and values (Katsikeas et al., 2020). This is particularly important for consumers with strong local identities, who evaluate global brands based on cultural fit and derive less enjoyment when brands appear culturally misaligned (Torelli and Stoner, 2019; Makri et al., 2019). Through reinforcement learning, AI storytelling can continuously refine cultural adaptation by tracking user engagement and feedback, and by generating multiple culturally sensitive versions of brand narratives for different markets (Kopalle et al., 2022). These capabilities are especially valuable in the luxury sector, where brand heritage and cultural identity are central to value creation (Venkatesh et al., 2010).

Using AI for culturally adapted storytelling also entails important risks. Not all consumers value localization: “global dreamers,” who view global brands as symbols of universal, cosmopolitan ideals, may respond more positively to standardized narratives (Holt et al., 2004). For these consumers, global brands derive value from expressing global cultural meanings rather than local ones (Torelli and Stoner, 2019; Makri et al., 2019). More broadly, acceptance of AI technologies varies across cultures, with greater openness in more individualistic and technologically advanced societies (Hoyer et al., 2020). Consumer trust in AI also differs, as AI systems are often perceived as opaque “black boxes,” raising concerns about a lack of transparency, empathy, and sensitivity to individual preferences (Grewal et al., 2021; Wien and Peluso, 2021). These concerns are amplified by power asymmetries between firms and consumers, which can trigger fears of manipulation and dehumanized interaction (Grewal et al., 2021). Additional risks may arise when AI storytelling closely imitates human or culturally resonant communication. Small inaccuracies—such as awkward language or shallow cultural references—may produce discomfort, consistent with the “uncanny valley” effect (Oliveira et al., 2024), and undermine perceptions of authenticity, which consumers seek to feel control, connection, and moral alignment with brands (Beverland and Farrelly, 2010). Finally, algorithmic bias poses a structural challenge: AI systems trained on non-diverse data may reproduce racial, gender, and cultural biases rooted in Western-centric norms, reinforcing existing inequalities and limiting cultural inclusivity (Noble, 2018; Eubanks, 2018; Kopalle et al., 2022). This two-fold perspective on AI storytelling and culture leads to our second question: “How do consumers perceive the role of culture in a luxury brand's AI storytelling?”

The study employs an inductive qualitative exploratory approach through a series of semi-structured interviews. Semi-structured interviews allow researchers to guide the conversation around specific themes while still giving participants the freedom to express their own opinions and ideas (Kvale, 1996).

The qualitative sample included diverse participants varying in age, nationality, ethnicity, social class, and life stage. The final sample consisted of 30 participants (aged 24–72) from diverse national backgrounds, including Italian, American, Russian, French, Mexican, Polish-American, Nigerian, and Indian participants. Participants represented a range of professional profiles (e.g. students, professionals, researchers, retirees) and varied levels of self-reported luxury consumption experience and familiarity with AI technologies. Participants were recruited using purposive sampling through professional and academic networks. Given the objective to explore consumer perceptions of AI in luxury brand storytelling, this study recruited: (1) consumers who regularly engage with luxury brands (e.g. purchase luxury items or interact with luxury brand content); (2) consumers with varying AI familiarity, from tech-savvy to less experienced, to capture diverse perspectives. This approach aligns with the broader view of AI as a marketing tool for scaling communication and reaching wide audiences. AI storytelling is intended to be a global strategy that engages anyone who wishes to learn about the brand (see participant profiles in  Supplementary 1).

Participants received no financial incentives for joining the study. Before the interviews, participants reviewed and signed a consent form. Interviews were conducted at times most convenient for participants. The interviews were conducted between November 2024 and February 2025. All interviews were conducted online via Google Meet or in person, depending on participants' availability and geographic location. The interviews were conducted in English/Italian/Russian, as these were the native or fluent languages of the participants and the researchers. Each semi-structured interview lasted approximately between 30 min and 1 h and was audio-recorded with participants' consent. Data collection stopped at the 30th interview as theoretical saturation was achieved (Clark, 2008) (see  Supplementary 1 for participants' profiles). There were no discernible differences between the data collected in person and online. Each interview was recorded with the participant's permission.

The interview started with a brief introduction to the research and a brief discussion of participants' backgrounds, experience with luxury brands, and familiarity with AI. Subsequently, we asked participants about their perceptions of luxury storytelling and AI. We then explored their views on AI storytelling in the luxury brand experience. Finally, participants shared their opinions on the role of culture in AI storytelling (see the interview protocol in  Supplementary 2).

This exploratory study examines the emerging phenomenon of AI storytelling. To help participants engage with this novel concept, we used elicitation techniques based on stimulus material (Barton, 2015). As a stimulus, we employed BrunelloCucinelli.ai, the first known AI storytelling website developed by a luxury brand, created to allow users to explore the brand's philosophy, founder, and history (Vogue, 2024). The platform was used solely as an illustrative example due to its pioneering role in the luxury industry. Participants were encouraged to ask brand-related questions and receive personalized narrative responses. To limit stimulus-specific bias, the interview protocol focused on AI storytelling and luxury brand experiences in general rather than on evaluating the platform itself. Participants were explicitly informed that the website served only as an example. Interviews explored perceptions of AI storytelling, including its perceived functions, communication style, engagement potential, drawbacks, and cultural adaptability. To reduce novelty and social desirability effects, participants were encouraged to provide honest reflections, and the interviewer adopted a neutral, non-judgmental stance. All participants were anonymized using identification codes to protect privacy and foster open discussion (Larson, 2019).

The analytic process followed Braun and Clarke's (2021) reflexive thematic analysis. It involved iterative phases of data familiarization, inductive coding, theme development, and refinement, with continuous movement between the data, emerging interpretations, and relevant literature. All interviews were transcribed verbatim and repeatedly read to support familiarization, during which researchers annotated transcripts with reflexive notes capturing initial insights. Initial inductive codes were then generated to label meaningful data segments and capture participants' perceptions of AI storytelling. Coding was conducted without reliance on pre-existing models. To enhance trustworthiness, a collaborative coding approach was adopted: team members independently coded a shared subset of transcripts, compared interpretations, discussed discrepancies, and iteratively refined the codebook through consensus-building (Richards and Hemphill, 2018), consistent with the principles of reflexive thematic analysis (Braun and Clarke, 2023). Next, codes were grouped into higher-order thematic categories through iterative engagement with the data and research question. These categories were reviewed and refined for coherence, distinctiveness, and analytical depth, informed by relevant literature on luxury storytelling, international marketing, and human–AI interaction. Each theme was then defined and named to reflect its central organizing concept and the specific aspect of the AI storytelling experience it captured. Themes were collaboratively reviewed to ensure conceptual clarity, non-overlap, and alignment with the research question. Finally, the analysis was written up using illustrative data extracts, and all team members reviewed the findings to ensure accuracy and representativeness (Pera et al., 2020). Throughout the process, all researchers participated in the creation, discussion, and refinement of themes, integrating multiple interpretive perspectives while mitigating individual bias (Gioia et al., 2013; Miles, 1994). Figure 1 illustrates the analytic progression from initial inductive codes to higher-order thematic patterns.

Our findings indicate that AI storytelling shapes the luxury brand experience across five key dimensions: intellectual, affective, behavioral, sensory, and cultural.

All interviewees referred to AI storytelling in relation to learning about the brand. As one participant explained, “I learned where the founder is from and what he's trying to do with the brand” (P14). This suggests that participants experienced AI storytelling as a tool for acquiring knowledge about the brand. Further, one interviewee described it as “an easy way to sum up the brand info from the ‘About Us’ section” (P19), while another highlighted the possibility of asking individualized questions: “All you have to do is type in the text box at the bottom of the page and it will give you any answers you need” (P18). These accounts suggest that AI storytelling facilitates efficient, personalized access to brand information. Some participants emphasized the experience's exploratory, curiosity-driven nature. One interviewee noted that “The website shows you things you'd never find otherwise. I'm curious about the brand's story” (P9). At the same time, another compared the experience to “an interactive experience to be on their website, almost like a museum” (P20). This indicates that AI storytelling may stimulate intellectual curiosity by encouraging exploration beyond standard informational content.

Other participants reported a diminished intellectual experience when AI-generated responses lacked clarity or specificity. One interviewee remarked, “The answers could have been more intentional. When it mentioned the start of sales in Germany, it didn't tell me much … just shifted to general ideas about friendly work environments” (P16). Similarly, another participant stated that “The responses for my second and third questions were general and did not provide a straight answer to my question” (P19). These accounts suggest that vague responses limit the perceived informativeness of AI storytelling. Participants also described how a lack of precise information shaped their evaluation of the brand. One interviewee commented that “The brand is media-trained … it floats around [a question] like a politician” (P15), while another stated that “AI should make things clear, not more mysterious” (P20). Others likened the experience to a “black box” when information was missing (P20) or felt that the platform “leaves out … important information” and should be “more concise” (P8). Taken together, these perceptions indicate that informational ambiguity may lead participants to interpret AI storytelling as evasive or overly promotional, as reflected in comments such as “It kind of hypes the brand … maybe too much” (P14) and “The details … exaggerate their skills and capabilities” (P3).

The affective dimension refers to a brand's ability to evoke a positive emotional response through customer interaction (Brakus et al., 2009; Dubé and Le Bel, 2003). All respondents emphasized emotions as the fundamental aspect of luxury brand communication.

One interviewee expressed satisfaction with the quality of the responses: “Oh wow … At first, I was skeptical, but the text is really well-written! … It answered all of my questions, so I'm not mad at it!” (P15). Another participant emphasized enjoyment and playfulness: “Wow, it is so cool! It feels like a new toy!” (P27). A further interviewee highlighted: “I'm curious to see how it would respond to something bold! That feels a bit provocative” (P13). These accounts suggest that AI storytelling can evoke positive affective responses such as surprise, excitement, and enjoyment. Some interviewees perceived the interaction as natural, stating that “The responses felt very similar to what an employee might say” (P14) and “It felt like talking to a real person” (P10). However, many participants described the experience as emotionally distant: “It feels cold … not engaging” (P3); “I perceive it as quite cold and detached” (P11); “It lacks empathy” (P8). These contrasting accounts indicate that AI storytelling may struggle to meet emotional expectations when compared to human-generated communication. Several interviewees also expressed discomfort with the idea of forming an emotional bond with AI: “I'm fine when AI just provides information, but I don't think it should feel like it's sitting around a dinner table trying to tell a story” (P12). Others emphasized a preference for a conversational tone: “The text should be more conversational, that's what makes the story meaningful” (P16). One participant commented on the impact of language on emotional connection: “The language AI used made it sound a little stiff. I definitely don't feel connected with this brand” (P20). Taken together, these accounts suggest that tone, warmth, and perceived empathy play a key role in shaping the affective experience of AI storytelling.

The behavioral dimension encompasses physical actions, lifestyle-related behaviors, and motor responses associated with the brand (Brakus et al., 2009; Schmitt, 1999). In our study, we show how AI prompts users to engage, explore, click, respond, or take physical or digital action.

One interviewee reflected on the durability of engagement: “It's engaging to a certain extent … but after a while, I'd probably stop using it” (P16). Others questioned the platform's purpose: “I can't see the purpose of this site” (P5), or its intended audience: “It might appeal to some retailers, but perhaps not to the general public” (P7). These accounts suggest that participants may perceive AI storytelling as limited in its ability to sustain behavioral engagement over time. Further, one interviewee remarked, “You ask a question, and within a few seconds, the AI provides an answer, but that's it” (P3). Another expressed skepticism about the platform's relevance to storytelling: “AI can assist in conducting market research, but I don't really see how it works for storytelling” (P4). These responses indicate that when AI storytelling is perceived primarily as fast but functionally limited, it may fail to prompt deeper interaction or continued use. One interviewee expressed interest in product-focused storytelling: “I'd love to read stories about specific products the brand is proud of, or about their campaigns and collaborations” (P16). Others suggested: “I would allow the AI to generate images of products and suggest items to purchase. For example: ‘I'd like to buy my husband a jacket—what products are trending or would you recommend?’” (P27). Therefore, participants may associate meaningful behavioral engagement with actionable outputs that extend beyond informational storytelling. Finally, some participants emphasized the importance of clearly communicating the platform's function. One interviewee stated, “I would add something that explains what this AI is for and how it helps you learn more about the brand” (P25). This suggests that clarifying the purpose of AI storytelling may shape users' expectations and willingness to engage behaviorally with the platform.

The sensory dimension of brand experience refers to how a brand engages the five senses (sight, sound, smell, taste, and touch) to create memorable experiences (Brakus et al., 2009; Gentile et al., 2007). In AI storytelling, this dimension is harder to activate unless rich multimedia (e.g. sound, visuals, animation) is used to simulate sensory input.

One interviewee stated: “AI storytelling should enable users to ask questions and receive answers not only in text but potentially also via voice commands. It should offer interactivity through the integration of images” (P2). Others emphasized that “videos could make it feel more real” (P11) and help “highlight values and distinguish the brand” (P8). These accounts suggest that participants expect AI storytelling to incorporate multimodal elements to enrich sensory engagement. Some respondents expressed appreciation for background music: “There is also the option to add background music. Nice!” (P24) and “I love the classical music option. It adds timelessness and sophistication to the browsing experience” (P7). One participant emphasized that the design “should avoid feeling cold and anonymous” (P7). Others described the site as “clean and minimalist, which makes it both welcoming and well-organized” (P1), and noted that “The colors and designs are aligned with the brand's identity. The font they used is very nice, it almost looks handwritten. Very lovely!” (P24). These accounts suggest that visual design plays a role in conveying a sense of luxury within AI storytelling. Finally, although AI storytelling cannot engage touch directly, one participant described a metaphorical physical sensation evoked through text: “It feels like someone is taking your hand and guiding you through the answer. It feels like a hug” (P15). This suggests that sensory experiences may also be evoked symbolically through language.

In our study, the cultural dimension refers to the extent to which a brand experience resonates with, reflects, or adapts to the consumer's cultural background. Culture shapes how individuals think, communicate, and decide (Kim et al., 2023). Consequently, consumers from different cultures may interpret the same brand message differently (Seo et al., 2015), underscoring the need for cultural adaptation in global brand communication.

Almost all participants emphasized the need for cultural adaptation in AI luxury storytelling: “If we're going to elevate this technology, AI storytelling should adapt to the language, values, humor, and cultural references” (P15); “It can adapt the communication style, the language, the sense of humor depending on the target segment” (P14). Participants suggested that it could make interactions between the user and the brand “more intimate” (P16), “avoid miscommunication and prevent offense on the cultural basis” (P27), and feel “warmer and more human” (P26). One interviewee commented, “I don't see how this website is adapted to me, except for the language: English from Italian” (P18), while another stated, “All websites have multiple language versions, so it's not really a cultural adaptation” (P25). Some participants suggested adapting the language tone: “This AI sounds very formal, very European. Communication should be simpler and friendlier for the American market” (P20). Several participants from the USA noted that “The sentences are too long … the message gets lost” (P13). Another interviewee suggested that the AI should “use bullet points for longer responses” (P21). These accounts indicate that participants expect cultural adaptation to involve changes in communication style and structure, not only language translation. Also, one interviewee noted: “If you're Italian and know fashion, the conversation can be deeper. But if you're like me and know little, it's better to keep it simple” (P25). This suggests that participants associate cultural adaptation with adjusting the depth of information to different audience backgrounds.

Several participants observed that visuals also carried different meanings: “There are lots of images of Italian villages and fields, but I don't think everyone can appreciate that. In some countries, village means poverty or peasantry” (P17); “I think the countryside doesn't go well with luxury. In my country, luxury has different associations” (P27). For P30, even color choice mattered: “A color that looks fancy in one country might mean something sad or boring in another.”

Alongside this desire for localization, many valued preserving the brand's cultural identity, which must stay authentic. Some interviewees stated: “If I'm looking at an Italian brand, I don't want it sounding and looking too American … It should still feel Italian” (P12); “Clearly, for this brand, it's important to show its Italian roots … changing it wouldn't feel right”; “Changing it too much would ruin brand heritage” (P17). Participants leaned toward glocalization—keeping heritage while adding local touches, such as the visual design tied to Italian heritage. Several participants described this balance through examples of localized additions. One interviewee referred to “cute old photography of Italian landscapes” (P16). Other examples included references to “local celebrities who wear the brand” (P17) and to “product preferences in the customer's country” (P14). Local humor was often cited as a way to make AI storytelling feel more “conversational and relatable” (P16). One participant stated: “Humor doesn't translate, it needs to feel local to be funny” (P14). Other cultural mixing examples included local poetry (“It would be amazing if the response included a line from a famous poet from my country”, P27) and local celebrations (“On special holidays like Diwali, Ramadan, Lunar New Year, the AI could say something to congratulate those who celebrate”, P30). As one participant explained, “For me, references to my country would be unexpected and definitely create a wow effect!” (P19).

Finally, a few participants felt that cultural adaptation was unnecessary for AI storytelling. One participant noted: “I think AI can help find information or do routine tasks. I don't see how it relates to culture” (P13). Others expressed discomfort with cultural personalization: “I'd feel uncomfortable if AI tried to get even more personal and started to mimic my background” (P12). Another interviewee warned that “AI in luxury shouldn't be too convincing. The luxury industry already promotes unrealistic lifestyle standards and beauty ideals … AI can only amplify that” (P15). Table 1 summarizes the findings.

The study examines consumers' perceptions of AI storytelling in luxury brand experiences and the role of culture. Figure 2 synthesizes the AI-mediated luxury brand experience into a cohesive conceptual framework in which AI storytelling shapes five interconnected experiential dimensions, as explained below.

In the intellectual dimension, AI storytelling facilitates personalized access to luxury brand information, enhancing brand knowledge beyond traditional media and reinforcing storytelling's core function of informing the public (Kim et al., 2016). By adding interactivity and personalization, it can also heighten narrative transportation (Van Laer et al., 2019). Whereas personalization in luxury typically occurs through customized products, designs, or packaging (O'Rourke et al., 2025), AI storytelling introduces personalized brand learning, which participants found more engaging than a standard “About Us” page. However, when information is vague or unclear, consumers may evaluate the intellectual experience negatively, suspect information withholding, or perceive excessive positivity. Such shortcomings conflict with luxury's error-free standards (Boukis et al., 2024), contradict expectations of AI as an informative and accessible tool (Chan and Choi, 2025), and may ultimately harm brand reputation. Thus, information quality links the intellectual, affective, and behavioral dimensions. Clear, accurate, and informative content fosters positive emotions, such as surprise and excitement, when using the platform. Also, it stimulates behavioral engagement such as seeking new information, using the platform for learning, and exploring it out of curiosity. In contrast, vague, biased, or overly promotional content triggers frustration and disengagement. It undermines the affective dimension of experience and consumers' behavioral intentions to interact with the platform.

Second, AI storytelling shapes luxury brand experience through the affective dimension. Consumers reported surprise and excitement driven by its innovativeness and interactivity, particularly when testing its ability to answer brand-related questions. In luxury, innovation and creativity are known to excite consumers (Tarquini et al., 2022), while interactivity supports experiential value co-creation and narrative enjoyment (Hoyer et al., 2020). Positive emotions also translated into behavioral engagement: when consumers liked and felt excited by the platform, they were more willing to continue exploring it. However, emotional engagement weakened when AI storytelling was perceived as cold, robotic, distant, or arrogant. Some participants preferred human storytelling, viewing AI as lacking warmth. This aligns with storytelling's traditional role in fostering social and emotional connection (Ganassali and Matysiewicz, 2021) and luxury's reliance on hedonic symbolism (Gurzki et al., 2019). Because AI is often associated with rational, utilitarian tasks rather than emotional expression (Longoni and Cian, 2022), it may unintentionally reinforce perceptions of arrogance and social distance already associated with luxury brands. Thus, emotional quality links the affective and behavioral dimensions. Surprise, excitement, and delight stimulate behavioral engagement, such as continued exploration, deeper interaction, and willingness to return to the platform. In contrast, negative affect (such as frustration, coldness, or perceived arrogance) reduces motivation to engage further.

Next, AI storytelling influences the behavioral dimension of the luxury brand experience. While consumers found it useful for learning about the brand, many perceived limited value beyond information retrieval, viewing AI as better suited for product recommendations or market research. To enhance behavioral relevance, AI storytelling should extend beyond brand narratives to include product-specific content and personalized recommendations. This reflects perceptions of AI as primarily suited to operational and analytical tasks (Longoni and Cian, 2022; Huang and Rust, 2022), with marketing value tied to efficiency, customization, and timely delivery across the customer journey (Grewal et al., 2021; Chan and Choi, 2025). Importantly, behavioral evaluations were closely linked to affective responses: when platform functionalities were limited, consumers expressed skepticism, whereas broader and more useful features elicited positive affect. However, because storytelling is traditionally associated with human emotional competence, consumers may question the practical value of AI-based storytelling platforms.

AI storytelling also shapes the sensory dimension of the luxury brand experience. Sensory cues influence consumer decisions, often unconsciously, and luxury brands rely on multisensory engagement to evoke emotion (Shahid et al., 2022). Activating this dimension requires refined multimedia elements—such as visuals, sound, and animation—to create esthetic coherence. Participants expected high-quality design, appreciating classical music and minimalist layouts, which they associated with a refined luxury experience. The sensory dimension also connects to other experiential dimensions: clear layouts support the intellectual dimension by facilitating learning, visually appealing design causes positive affect, and increases consumers' intention to continue engaging with the platform. This is particularly important given AI's limited emotional competence (Longoni and Cian, 2022), as multisensory cues help preserve the emotional depth of luxury storytelling.

Finally, AI storytelling introduces a cultural dimension of luxury brand experience. Participants expected AI not merely to translate content but to reflect culturally grounded communication preferences, consistent with storytelling as a culturally situated meaning-making activity rooted in myths and archetypes (Woodside et al., 2008). In line with international marketing research, participants favored a balance between global brand identity and local cultural relevance (Alden et al., 1999), preferring a glocalized approach in which AI storytelling preserves core brand ideology while selectively adapting to local cultural codes (Holt, 2004; Nie and Wang, 2021).

Participants valued authentic cues of brand origin (Beverland and Farrelly, 2010), viewing Italian heritage as a key source of symbolic value that should not be diluted by AI personalization. This shapes the intellectual dimension: when brand heritage is clearly communicated, consumers engage with brand knowledge and perceive the storytelling as more credible. At the same time, subtle cultural references—such as local humor, holidays, or poetry—were emotionally enhancing. This shapes the affective dimension: culturally resonant storytelling generated positive emotions such as warmth and connection. These preferences reflect the role of cultural codes as meaning-making resources (Holt, 2004; Woodside et al., 2008) and show how hybrid global–local strategies can strengthen perceptions of authenticity and heritage (Nie and Wang, 2021; Seo et al., 2015; Li et al., 2026). However, participants warned that excessive or superficial localization may undermine both indexical authenticity (signaling origin and heritage) and existential authenticity (supporting personal identity) (Morhart et al., 2015). This shapes the behavioral dimension: consumers were more willing to engage with AI storytelling that struck the right cultural balance, while excessive personalization reduced their motivation to interact further. This tension mirrors consumer identity research, which shows that individuals simultaneously hold global and local identity orientations and evaluate brand communication based on how well it balances cosmopolitan symbolism with cultural relevance (Holt et al., 2004; Makri et al., 2019; Torelli and Stoner, 2019). AI storytelling thus emerges as a mechanism for selective cultural adaptation without eroding core brand ideology. This also shapes the sensory dimension: participants associated specific esthetic choices, such as classical music, minimalist design, and visual references, with brand origin and cultural authenticity. These cues reinforced the overall cultural coherence of the storytelling experience.

Finally, overly personalized interactions sometimes caused emotional discomfort. Participants who were already skeptical of AI expressed unease when the system appeared “too personal” or attempted to mimic their cultural background. This discomfort can be interpreted through cultural and individual differences in technology acceptance, as prior research shows that consumers vary in their tolerance for algorithmic inference, perceived intrusiveness, and the extent to which they welcome adaptive technologies (Hoyer et al., 2020; Kopalle et al., 2022). Another explanation relates to global consumer identity, which suggests that consumers who derive symbolic value from global brands, because they evoke a sense of cosmopolitanism, borderlessness, and participation in a worldwide consumer culture, may prefer less cultural adaptation (Torelli and Stoner, 2019).

This study makes several theoretical contributions. First, this research formally introduces and theorizes AI storytelling within the luxury context. Prior research examines storytelling through social media (González Romo et al., 2017), brand museums (De Boissieu and Chaney, 2024), and the metaverse (Hu et al., 2025). Also, prior storytelling theories conceptualize brand storytelling as human-authored, linear, and emotionally grounded in human interaction (Woodside et al., 2008). Existing research on AI in brand communications, meanwhile, has predominantly framed AI as a functional, task-oriented tool (Chan and Choi, 2025; Feng and Sun, 2026; Grewal et al., 2021; Huang and Rust, 2022; Longoni and Cian, 2022; Van Laer et al., 2019), leaving its experiential and symbolic dimensions largely unexplored. None of these bodies of literature, therefore, accounts for how AI can simultaneously function as a storytelling, experiential, and symbolic mechanism in luxury brand communication. We define AI storytelling as the use of AI to generate, personalize, and deliver brand-related narrative content in real time. We distinguish AI storytelling through its brand-controlled inputs (e.g. brand heritage narratives, product descriptions, brand values) and system-level capabilities (e.g. real-time personalization, dialogic interaction, and co-creation). The algorithm acts as a mediator between the brand and the consumer, generating symbolically resonant content (such as narratives tied to heritage, identity, or cultural values) based on patterns, data, and system logic.

Second, we clarify what AI storytelling explains that existing storytelling and AI-enabled communication constructs do not. Prior storytelling theories largely conceptualize brand storytelling as human-authored, linear, and emotionally grounded in human interaction (Woodside et al., 2008). In contrast, our findings demonstrate that AI storytelling operates as a dialogic and co-creative process between consumers and an algorithmic system. Existing research on AI in brand communications has framed AI as a functional, task-oriented tool (Chan and Choi, 2025; Feng and Sun, 2026). For example, chatbots are designed for service resolution, while AI assistants are optimized for query response; personalization engines focus on content relevance, and websites deliver static brand information (Grewal et al., 2021; Huang and Rust, 2022; Longoni and Cian, 2022; Van Laer et al., 2019). Yet none of these studies examine whether AI can also function as an experiential storytelling instrument that enhances brand symbolism. Our research presents AI storytelling as an experiential and symbolic mechanism that shapes intellectual, emotional, sensory, behavioral, and cultural dimensions of luxury brand experience.

Third, we propose a conceptual framework of AI-mediated brand experience comprising four AI-modified experiential dimensions (intellectual, affective, behavioral, and sensory) and one new dimension (cultural). AI enhances these experiential dimensions through its real-time personalization, dialogic interaction, and co-creation. Our contribution lies in extending brand experience theory (Brakus et al., 2009; Dubé and Le Bel, 2003; Gentile et al., 2007; Schmitt, 1999) to AI-driven storytelling and explicating how each dimension manifests within an AI-mediated environment. Intellectually, AI shifts brand learning from passive information processing (Dubé and Le Bel, 2003; Gentile et al., 2007) toward interactive inquiry through prompts and iterative exchanges. In practice, AI introduces an emotional duality in which technological novelty generates excitement, but the perceived absence of human warmth limits emotional depth (Brakus et al., 2009; Dubé and Le Bel, 2003). Behaviorally, AI redirects engagement from physical actions (Brakus et al., 2009) to digitally mediated micro-behaviors such as prompting, testing, and exploring the system. Sensory experience is reframed from embodied multisensory immersion (Gentile et al., 2007; Schmitt, 1999) to digital atmospheres conveyed through aesthetics, typography, color palette, and sound. These AI-mediated experiential dimensions offer a basis for analyzing consumer experiences across a wide range of AI-mediated digital interactions. In addition, this study introduces a cultural dimension to the established brand experience framework. It refers to the extent to which a brand experience resonates with, reflects, or adapts to the consumer's cultural background. The existing dimensions explain how consumers think, feel, act, and perceive, but they do not account for how experiences are interpreted through culture (Brakus et al., 2009; Dubé and Le Bel, 2003; Gentile et al., 2007; Schmitt, 1999).

Fourth, we advance the literature on AI integration in the luxury sector. Recent studies have started exploring consumer reactions to AI-generated luxury advertising (To et al., 2025), AI-designed luxury products (Xu and Mehta, 2022), and AI assistants (Rahman et al., 2023) suggesting that AI may backfire by being associated with lower effort and authenticity (To et al., 2025) and reduced brand essence (Xu and Mehta, 2022), but can benefit the brand by being engaging and using multisensory cues (Rahman et al., 2023). Our results show that AI storytelling can support fast, personalized learning about the brand, surprise and excite consumers, and provide sensory appeal. However, many consumers can express skepticism or dissatisfaction with AI storytelling. Specifically, its vague or impersonal responses can frustrate users, and the emotional depth of human storytelling is often lacking. Moreover, some consumers doubt the usefulness of AI storytelling and expect more concrete help, such as product recommendations.

Finally, we contribute to the globalization–localization debate in international branding (Bai et al., 2022; Katsikeas et al., 2020). This manuscript assesses AI's potential as a glocalization tool that connects global luxury brands with local markets. On the one hand, AI storytelling can incorporate cultural elements such as humor, tone, message length and complexity, and references to local literature, art, pop culture, aesthetics, and holidays. This expands the literature on how digital technologies can be used for more precise cultural adaptation (Hoyer et al., 2020; Katsikeas et al., 2020; Kopalle et al., 2022). Such attention to the user's culture may be especially important in the luxury industry, where respect and individual attention are required (O'Rourke et al., 2025). On the other hand, consumers may not want complete adaptation to their cultures because a brand's authenticity is important (Li et al., 2026). Therefore, AI storytelling should become an automated yet flexible tool for cultural adaptation without undermining brand authenticity. This finding challenges the binary framing of globalization vs. localization (Rao-Nicholson and Khan, 2017) and shows how consumers expect AI to enable a hybrid approach (Hong et al., 2023). Additionally, while international consumers view the cultural adaptation of AI-driven storytelling in luxury branding positively, they do not see it as a priority. Culturally adapted storytelling is perceived as an added value-enhancing component of the luxury experience. AI is primarily viewed as a tool for practical tasks, making its cultural adaptation efforts in luxury storytelling appear less valuable. This perception can contribute to the broader literature on the role of culture in AI-mediated environments (Chow et al., 2025; Kopalle et al., 2022) by highlighting that, as a novel technology, AI is currently expected to address more practical and functional needs. Moreover, culturally tailored AI storytelling may alienate consumers who are resistant to AI or uncomfortable with machines mimicking their cultural identity. This can be explained by individual and national differences in technology acceptance and trust (Grewal et al., 2021; Hoyer et al., 2020; Oliveira et al., 2024).

Our research can serve as a guide to enhance brand experience through AI storytelling. To support the intellectual aspect, AI storytelling should be trained to deliver precise answers and suggest additional resources for consumer inquiries. Apart from the brand's story, AI storytelling should also provide detailed product information and personalized recommendations. From a model-development perspective, luxury brands should train their AI systems using brand-controlled and system-level antecedents. On the brand-controlled side, the model must be fed with rich internal brand assets: brand stories, myths, symbols, founder narratives, and core ideological cues to anchor AI in the brand's authentic identity. This also includes tone-of-voice guidelines and editorial rules that specify which themes, vocabulary, and stylistic elements the AI should emphasize or avoid. If the brand wishes to adapt its storytelling to different markets, additional inputs may include locally relevant myths and symbols, localized tone-of-voice guidance, and market data such as customer preferences or their perceptions of the brand in a given country. At the system level, AI models should be structured to support interactive dialog through input–output flows. This involves AI capabilities such as adaptive response modeling and multimodal generation. This way, the system can respond flexibly, refine outputs in real time, and sustain a back-and-forth exchange.

Although consumers may remain skeptical of AI's capacity for human-like emotional storytelling, our findings show that emotional engagement can be achieved through sensory and experiential design. AI storytelling should move beyond text to incorporate multimodal elements such as voice, images, and video, enhancing realism and narrative immersion. Sound and music—especially classical or brand-aligned compositions—effectively evoke atmosphere and emotional resonance. Likewise, clean layouts, elegant typography, and brand-consistent color palettes signal care and intentionality, counteracting perceptions of AI as cold or anonymous and reinforcing authenticity. Finally, the use of warm, empathetic, and relational language further fosters emotional connection, encouraging users to perceive AI as emotionally attuned rather than mechanical.

For global luxury marketers, our findings show that AI storytelling can support glocalized communication by balancing brand consistency with cultural adaptation. Luxury brands should maintain a clear core ideology across markets to preserve global meanings such as quality, modernity, and heritage. At the same time, small and selective cultural adjustments—such as changes in language style, imagery, or subtle references to local culture (e.g. poetry or music)—can increase relevance for local audiences without weakening the brand's global identity.

This study raises important societal and ethical implications that align with contemporary debates in AI ethics. As AI storytelling becomes embedded in luxury brand communication, it does not simply convey information; it also influences luxury meanings related to desire, status, and identity. Therefore, transparency is critical. Brands should disclose when content is AI-generated and provide explanations of how outputs are produced, including the data sources and system logic used. Clarifying what the system can and cannot do (such as whether conversational inputs are stored) can mitigate concerns about consumer surveillance and hidden persuasion. In luxury, privacy is part of the exclusive, trust-based relationship between the brand and the consumer. Undermining privacy through opaque AI systems risks eroding the very foundations of luxury. Second, AI storytelling introduces risks of subtle manipulation. By amplifying narratives of exclusivity, AI systems may nudge consumers toward desire-based evaluations rather than rational judgment. This is particularly important in luxury, where consumption is tied to aspirational self-expression (Gurzki et al., 2019). When AI systems reinforce desire in a personalized way, they may exploit consumers' identity aspirations. This raises questions about the ethical boundaries of algorithmic persuasion in high-involvement consumption contexts. Third, algorithmic and cultural bias represent a critical ethical challenge (Noble, 2018). When AI storytelling relies on training data that privilege Western representations of luxury, it may reinforce narrow ideological constructions of status and aesthetics, marginalizing alternative cultural interpretations. This is especially problematic in the luxury sector, where consumers from non-Western markets are among the fastest-growing segments (Bai et al., 2022). Western-centric vision of luxury risks alienating these consumers and perpetuating cultural hierarchies. To mitigate these risks, brands should incorporate culturally diverse training data, conduct regular review cycles with local experts, and implement bias-detection mechanisms such as culturally sensitive “bias flags” or forbidden vocabulary lists. In this way, each market may maintain a “local ethical layer” on top of a global AI model (Katsikeas et al., 2020). Overall, these considerations underscore the need to situate AI storytelling within a framework of responsible luxury brand communication.

This study has limitations that open avenues for future research. Given the novelty of AI storytelling, we conducted an exploratory qualitative analysis to examine its impact on luxury brand experiences. Our aim was to introduce the concept within the context of luxury branding and initiate discussion on its potential, rather than test specific experience components, such as visual aesthetics, content type, emotional language, or cultural references, in isolation. The focus was on understanding consumers' holistic perceptions.

Our findings suggest that AI storytelling can enhance brand experience across five dimensions: intellectual, emotional, behavioral, sensory, and cultural. Future research could quantitatively test the influence of specific elements within each dimension, using experimental designs to isolate and measure their effect on overall consumer perceptions. Participants responded positively to background music, noting its role in deepening emotional engagement and creating a sophisticated atmosphere. Further studies could test which music types are most effective on AI platforms. Similarly, design elements such as color palettes, layout, and typography were considered essential for a welcoming, brand-consistent interface by participants. Research could examine visual design strategies that align with luxury brand identities, particularly the symbolic use of color (Kim et al., 2020). Participants also emphasized enhancing interactivity through diverse content formats, such as images and videos. Narratives that reveal the human craftsmanship and commitment behind products may strengthen emotional connection (Tarquini et al., 2022). Future studies could identify which formats support this goal.

We used BrunelloCucinelli.ai, the first and only AI storytelling platform in the luxury sector at the time of the study. While appropriate for exploratory analysis, reliance on a single, heritage-driven brand may introduce brand-specific effects that limit the generalizability of the findings. First, Brunello Cucinelli is a heritage-driven luxury brand with a strong identity, which may shape the style of AI-generated storytelling and consumers' expectations toward it. Participants' evaluations of AI storytelling may therefore partially reflect perceptions of this specific brand's tone, values, and positioning rather than AI storytelling as a generic technological practice. Second, brand-specific design choices (such as language and visual style) may have influenced how participants assessed their experiential dimensions, as well as authenticity cues and cultural adaptation perspectives. This means that some findings may be more specific to Brunello Cucinelli's brand ideology than to AI storytelling as a broader phenomenon. Brands with different identities, such as younger, more playful, or more accessible luxury brands, may elicit different experiential dimensions. As a result, the experiential dimensions identified in this study should be interpreted as analytically transferable rather than statistically generalizable (Braun and Clarke, 2021). They offer conceptual insights into how consumers make sense of AI storytelling in luxury contexts, but their manifestation may vary across brands with different identities. Future research should therefore compare AI storytelling platforms across brands with distinct identities and positioning. Studies could also use fictional brand prototypes to isolate the experiential mechanisms of AI storytelling from brand-specific effects. It would allow for more controlled comparisons. Additionally, research could examine how the five experiential dimensions manifest differently across brand types. For instance, heritage luxury brands may differ from contemporary or accessible luxury brands. This could establish the boundary conditions of the proposed framework.

Despite precautions during data collection, participants' responses may have been influenced by novelty and social desirability biases. As AI storytelling in luxury branding is still emerging, reactions may reflect curiosity or skepticism driven by novelty rather than stable attitudes, while luxury brand prestige may have encouraged more favorable or aspirational responses. Although steps were taken to reduce these effects, they cannot be fully ruled out. Future research could address this limitation by using longitudinal or experimental designs to assess how perceptions evolve with increased familiarity with AI technologies. Moreover, future research with a more narrowly defined focus on user behavior could benefit from the development of experimental AI storytelling platforms. Such an approach would enable methodological triangulation by combining qualitative insights with platform-level behavioral data—such as time spent on pages, the number of prompts submitted, and navigation paths—typically accessible only to platform developers or brand owners.

Finally, cultural adaptation emerged as a critical factor. Future research could explore how to tailor AI storytelling for different cultural contexts. This could be interpreted through the high-vs. low-context culture theory (Hall, 1976), and tone and language adapted accordingly. For example, adopting a formal tone in markets where politeness is valued and a more casual style in markets favoring informality (Kim et al., 1998).