Gen AI – Gen Z: understanding Gen Z’s emotional responses and brand experiences with Gen AI-driven, hyper-personalized advertising

Peter, Rupa; Roshith, Veni; Lawrence, Sheethal; Mona, Arthi Efcibha; Narayanan, Kodhai B.; Yusaira, Fathima

doi:10.3389/fcomm.2025.1554551

ORIGINAL RESEARCH article

Front. Commun., 11 July 2025

Sec. Advertising and Marketing Communication

Volume 10 - 2025 | https://doi.org/10.3389/fcomm.2025.1554551

Gen AI – Gen Z: understanding Gen Z’s emotional responses and brand experiences with Gen AI-driven, hyper-personalized advertising

Rupa Peter¹^*

¹St Joseph's University, Bengaluru, India
²Bath Spa University, Bath, United Kingdom
³Christ University, Bengaluru, Karnataka, India
⁴Central University of Karnataka, Gulbarga, India

Introduction: Gen Z, a tech-savvy consumer group, has highly evolved in its approach to new-age advertising. The rise of Generative Artificial Intelligence (Gen AI) has revolutionized advertising by enabling hyper-personalized content, making it essential to understand its influence on Generation Z (Gen Z) population. This study explores the responses of Gen Z participants in India to Generative Artificial Intelligence based, hyper-personalized advertisements, with a specific focus on emotional responses and brand interactions which are significant predictors of advertisement success.

Methods: Using qualitative research methods, semi-structured interviews were conducted with 40 Gen Z participants. Thematic analysis of the data was performed to understand the major themes pertaining to emotional responses and brand interactions to this form of Gen AI-driven advertising.

Results: Two major themes and five sub-themes were revealed through thematic analysis. The first theme, diverse emotional responses, encompassed two sub-themes, curiosity and interest as well as fear and suspicion. The second major theme, enhanced brand experience, encompassed three sub-themes of advanced targeted marketing; initial attraction and brand engagement; and brand connection and loyalty, as perceived by the participants.

Discussion: Findings imply that brands can harness Gen AI-driven, hyper-personalized advertisements to evoke meaningful emotions, enhancing consumer loyalty and building stronger, more personal connections with their audience.

1 Introduction

Generative AI is here to stay. It is this newest form of disruptive technology that holds tremendous transformative potential in the creative ecosystem (Thibault et al., 2023). Gen AI refers to a category of AI systems capable of creating new content (Susarla et al., 2023) in the form of text, images, audio and video. This novel technology offers an opportunity to co-create; the practice of humans and machines working together, to create something new, termed AI Creativity (Wu et al., 2021). An example is Coca-Cola’s advertisement, Masterpiece, created in collaboration with OpenAI (Marr, 2023).

With the creative promise that Gen AI holds, Gen AI has the potential to revolutionize the advertising sector (Gao et al., 2023). Creative AI can reshape many aspects of advertising production and distribution (Campbell et al., 2022). AI has reorganized and upgraded traditional advertising and improved advertising efficiency (Qin and Jiang, 2019).

In the AI advertising scenario, there is an interconnectedness between four elements—targeting, personalization, content creation and ad optimization (Gao et al., 2023). AI is extensively used for personalization and creating audience-specific advertising campaigns. Personalization of advertisements using AI technologies enhances relevance and consumers engage more with these advertisements (Guo and Jiang, 2023) as in Gen AI-driven, personalized video advertisements which were effective in engaging historically ‘non-engaged’ customers (Kumar and Kapoor, 2024). Hyper-personalization, which involves the use of individuals’ data to provide targeted, personalized content (Vavliakis et al., 2019), enabled by Gen AI, has changed the way marketers and advertisers reach their consumers across the web and in mobile apps (Yoon, 2022). Using the innovative and generative nature of AI, hyper-personalization creates tailor-made (Maddodi, 2021), subjective experiences for individual consumers.

2 Review of literature

2.1 The era of hyper-personalization

Hyper-personalization using Gen AI is new and exciting and it is taking the marketing and advertising world by storm (Rusiñol, 2023). Through hyper-personalization, brands can send individual-centric, highly contextualized marketing communications to specific customers at the right place and time, and through the right channel, based on data, including demographics, behavioral patterns, preferences, and contextual factors (Deloitte, 2020). Hyper-personalization provides specific content for interaction with individuals and not with segments or groups (Bali et al., 2021). Customer’s digital footprints are combined with browsing and purchase history to create hyper-personalized advertising (Ooi et al., 2025) and highly contextualized customer experiences (Desai, 2022). This advancement removes problems related to ‘choice-overload’ and saves time by narrowing down the options to those that the consumer is interested in (Tyagi and Bhatnagar, 2021), thereby, enhancing consumer-centricity (Morton et al., 2024). Advertisers are leveraging Gen AI and providing consumers with an opportunity to create their own unique hyper-personalized promotional messages as in the case of Virgin Voyages Jen AI customization (Day and DiLella, 2023) and Not Just a Cadbury Ad (Desk, 2021) that hyper-localizes content to promote local businesses.

However, there are ethical considerations surrounding data utilization in personalized advertising (Bashynska, 2023), limitations in data accuracy (Singh and Adhikari, 2023) and the perceived eeriness of AI advertising (Wu and Wen, 2021). AI techniques such as deepfakes can create content that depicts an unreal, artificial version of reality and manipulated advertising presents significant opportunities and threats (Campbell et al., 2022). Despite there being a sharing of intelligence, between humans and AI, the moral and legal responsibility still rests with humans alone (Sharakhina et al., 2023). Despite these apparent drawbacks, this novel approach to advertising is resonating with the tech-savvy, individualistic Gen Z consumer (Pichler et al., 2021).

2.2 Gen Z goes hyper

Youth as a social collective are early adopters of technological innovation (Antón and Salas, 2019; Ratten and Ratten, 2007). Naturally, Gen AI’s ‘super users’ are the young, confident Generation Z (Gen Z) who use this technology frequently and are bullish about mastering it (Revell, 2023). Gen Z are the digital natives who were raised in the age of social networks (Francis and Hoefel, 2018). They have an estimated $450bn in spending power and are a major contributor to the global economy (Noenickx, 2023). Marketers are using Gen AI to tap into this growing sector with promotional messages that can boost sales and increase loyalty (Bhat, 2023). Lays Messi Messages, (Adams, 2021), Cadbury’s #MyBirthdaySong (Ganguly, 2023), and Spotify Wrapped’s AI DJ (Perez, 2023) offer a unique hyper-personalized, promotional experience for young people. While Gen Z is accepting of AI use for marketing and promotions, they do have higher levels of concern regarding personal data, psychological profiling and manipulation (Jeffrey, 2021).

2.3 Theoretical background

The exploration of hyper-personalized advertising’s influence on brand interactions and consumer behavior can be grounded in several psychological and marketing theories. These frameworks provide a comprehensive understanding of how AI-generated personalized advertising influences consumer perceptions, emotions, and interactions with brands.

Attachment theory, originally rooted in developmental psychology and first proposed by Bowlby (1979), describes attachment as a lasting emotional bond formed to fulfil basic needs, such as the bond between a mother and child. In marketing, this concept extends to brand attachment, which refers to the emotional connection between consumers and brands. Studies have shown a positive relationship between consumer emotional attachment and brand loyalty. A connection among consumer emotional factors such as loyalty, price premium, and purchase situation were also partially mediated by affective and cognitive factors (Sathyanarayan and Subburaj, 2021). When consumers form strong brand attachments, it fosters brand loyalty and establishes long term relationships. Personalized advertising strengthens these emotional bonds by creating tailored brand experiences, which increase brand equity (Tran et al., 2022; Tran et al., 2023).

Building on this, Self Congruity Theory, introduced by Sirgy (1982), explores the relationship between a consumer’s self-concept and their perception of a product, brand, or service. Self-congruity refers to the psychological process and outcome where a consumer compares their perception of a brand’s image, specifically its personality or user image, with their own self-concept such as their actual self-image. In other words, it reflects the consumer’s identification with a brand (Sirgy et al., 2016). The theory suggests that individuals tend to prefer brands that mirror their self-concept. Research shows that personalization enhances this alignment, strengthening the emotional bond between consumers and brands (Tran et al., 2020).

The Elaboration Likelihood Model (ELM), developed by Petty and Cacioppo (1986), provides a comprehensive dual-process framework for understanding attitude change and persuasion. It identifies two primary routes: the central route, and the peripheral route. The central route engages consumers through deep processing of relevant, tailored advertisements, leading to lasting attitude changes (Pan, 2024). In contrast, the peripheral route targets less motivated consumers using heuristic cues like visual appeal or endorsements (Schumann et al., 2012; Park et al., 2023). This model has been widely applied, including in advertising, to explain how consumers process persuasive messages. AI-generated content can effectively activate both routes by engaging consumers with varying levels of involvement. Evidence shows that AI personalizes the entire customer journey, from targeted ads that capture attention to personalized product recommendations and post-purchase support, creating a seamless and engaging experience across all touchpoints (Babatunde et al., 2024).

Together, these theoretical perspectives provide a comprehensive framework for understanding the emotional responses and brand interactions triggered by Gen AI-driven, hyper-personalized advertising.

2.4 Purpose of the study

With Gen AI-driven, hyper-personalized advertising, marketers are at the cusp of a new wave of consumer interaction. Studies have explored hyper-personalization using Gen AI in relation to the use of consumer data for hyper-personalization (Ooi et al., 2025), adaptive strategies (Rane et al., 2023), reach of hyper-personalized algorithms (Yoon, 2022), AI’s role in interactions through marketing chatbots (Cheung et al., 2021; Lin and Wu, 2022), predictive marketing (Avinash, 2021), hyper-personalization’s alignment with societal values (Bashynska, 2023) and ethical considerations (Jeffrey, 2021; Sharakhina et al., 2023).

However, advertising as a promotional exercise thrives largely in the realm of emotion (Poels and Dewitte, 2019). Consumers relate to advertisements on an emotional level (Bhatia, 2019; Mizerski and Dennis, 1986) and emotional responses represent a pivotal aspect in consumer-brand interactions (Jindal et al., 2023; Qutp et al., 2022). Existing research has highlighted that, emotional responses to AI-driven advertisements, range from joy and pride to anxiety and social disgust (Bagozzi et al., 2022). Yet, there is a lack of in-depth qualitative exploration into how these emotions develop and influence consumer-brand interactions.

Previous studies have also demonstrated that AI-powered personalized marketing can enhance targeting, engagement, and customer satisfaction, leading to stronger brand loyalty (De Keyzer et al., 2015; Babatunde et al., 2024; Gautham and Rao, 2024; Singh, 2024) and helps create personalized customer experiences (Ho and Chow, 2023). Existing studies predominantly use quantitative methods, measuring engagement, clicks, and purchases. These metrics only partially capture the phenomenon, overlooking the emotional depth of consumer reactions to Gen AI-driven, hyper-personalized advertising campaigns. Hyper-personalization’s unprecedented precision in individualized targeting profoundly alters consumer-brand interactions, introducing new dynamics that remain unexplored.

This gap highlights the need for conducting a qualitative exploratory study to delve into the emotional experiences of consumers in response to Gen AI-driven, hyper-personalized advertisements and how this influences their interactions with the brand. Through this, the study aims to uncover the subtle and often conflicting emotions that consumer’s experience, providing richer insights into how these emotions shape their interactions with brands and their willingness to engage with personalized content.

Furthermore, the generational aspect of this exploration is pertinent. Digital nativeness has become synonymous with a younger demographic, such as Gen Z, who are early adopters of AI technology (Revell, 2023) and who actively seek personalized experiences (Gutfreund, 2016).

At present, the digital advertising industry in India is a 4.95-billion-dollar industry and the entry of AI technologies has given rise to new avenues to reach consumers across this diverse nation (Dentsu, 2024). Though AI adoption is still in its nascency, the industry has started to utilize hyper-personalization for its targeted marketing efforts (Das, 2024). With greater internet accessibility among the Gen Z youth of India (Koutsou-Wehling, 2024), Gen AI-driven, hyper-personalized advertisements have the potential to create a significant impact and an in-depth exploration of this generates practical implications for advertisers.

The present study explores the identified gap by investigating the emotional responses elicited by Gen AI-driven, hyper-personalized advertisements among Gen Z young adults and their influence on brand interactions, with the potential to enhance practical applications in real-world scenarios.

2.5 Research questions

1. What are the emotions elicited by Gen AI-driven, hyper-personalized advertisements among consumers?

2. How do Gen AI-driven, hyper-personalized advertisements influence consumer interactions with the brand?

3 Methodology

3.1 Research paradigm

This study used an interpretivist paradigm, which focuses on understanding the meanings individuals attach to their experiences and social realities. Interpretivism emphasizes subjective interpretations over objective measurements, making it particularly suitable for exploring complex human behaviors in their natural context (Schwandt, 2000). This approach is often employed in qualitative research to uncover how people perceive and make sense of their world. For this study, interpretivism was ideal for examining participants’ subjective experience of Gen AI-driven, hyper-personalized advertising as it facilitated an exploratory investigation into the experiences of Gen Z participants in India with Gen AI-driven hyper-personalized advertisements.

3.2 Participants and recruitment

Gen Z are associated with increased activity on internet-driven media platforms, frequently viewing online advertisements, as evidenced by the reviewed literature (Sebastian et al., 2021). Therefore, the participants for the present study were individuals who belonged to the Gen Z cohort and were exposed to Gen AI driven, hyper-personalized advertisements. As Gen AI-driven, hyper-personalized advertisements seen online varies tremendously from individual-to-individual, uniform categorization is a difficult task. Hence, in order to get different perspectives from a diverse group of individuals on this novel form of advertising, a large sample of 40 participants was taken for the current study. An expected sample size of around 40–50 was decided a priori based on a previous study that used a similar methodology (Sebastian et al., 2021).

To identify potential participants, a digital poster with a google form link was circulated on online messaging apps and social media platforms, inviting Gen Z volunteers to participate. To be included in the study, the participants had to be between 18 to 27 years, residing in India, and exposed to Gen AI-driven, hyper-personalized advertisements. English proficiency was also required to ensure effective communication during interviews and maintain consistency in the data. A total 172 participants responded to the invite by filling a screening tool which was shared as a google form. The screening tool assessed, volunteers’ prior exposure to and awareness of Gen AI-driven, hyper-personalized advertisements through questions such as, ‘Have you heard of Gen AI-driven, hyper-personalized advertisements?’ ‘Can you explain what they are?’ ‘How are they different from regular advertisements?’ ‘Can you give some examples of Gen AI-driven, hyper-personalized advertisements?’ Using purposive sampling method, a total of 40 eligible participants were selected out of 172 respondents, based on their awareness and exposure to this form of advertising, while ensuring a balance of gender, age and occupation (see Table 1).

Table 1

Table 1. The socio-demographic characteristics of the participants.

3.3 Procedure

Data was collected between March and July of 2024 through individual semi-structured interviews conducted online via recorded sessions on Google Meet. The interview schedule was formulated based on the existing literature and was validated by a team of experts, including four academicians from media studies and psychology, and one consumer insights specialist. The interview schedule concentrated on participants’ emotions towards Gen AI-driven, hyper-personalized advertisements and their influence on brand interactions including questions such as ‘What are your feelings towards Gen AI-driven, hyper-personalized advertisements? and ‘What aspects of hyper-personalized advertisements, do you think will influence your decision to consider buying the product/brand that is advertised?’ ‘Brands use our personal data to hyper-personalize advertisements, what are your views on this?’ how do you feel about a brand that uses such technologies?’ The interviews lasted approximately 30–40 min, and included questions along with probes and examples of Gen AI-driven, hyper-personalized advertisements, when required. These interviews were then, transcribed using Google services and later proofread by researchers.

Before the online interviews, participants read and signed an online consent form detailing the research purpose, privacy rights and confidentiality. At the beginning of each interview, participants were reminded of their privacy rights and option to withdraw. Participation was voluntary and non-remunerated. Confidentiality of recordings and transcripts was ensured. The research adhered to the ethical guidelines of the University wherein two of the authors are employed.

3.4 Code classification

The interview transcripts of the 40 participants were analyzed using the six-step process of thematic analysis outlined by Braun and Clarke (2006). Coding was done independently and simultaneously by two researchers, with a third researcher further examining the codes to avoid discrepancies. Initially, the researchers immersed themselves in the data, identifying recurrent elements and patterns as initial codes (Braun and Clarke, 2006; Nowell et al., 2017). Codes were derived from existing literature and refined based on participant responses, grouping similar words to streamline analysis. These codes were then organized into sub-themes, from which main themes eventually emerged. In the final stage, these themes were named and defined as relevant to the study’s objectives (Braun and Clarke, 2006). To facilitate the organization, coding, and retrieval of qualitative data, NVivo (Version 14) was used as the data management tool.

When it comes to methodological rigor, the researchers ensured credibility of the study by engaging deeply with participants, building rapport through the sessions and observing verbal cues to capture nuanced emotional responses. The researchers made every effort to critically reflect on the responses to minimize participant biases stemming from their previous exposure and understanding of these advertisements. To mitigate this, efforts were made to avoid taking information at face value. Further probing and non-leading, open-ended questions were used to minimize biases and ensure more accurate responses. The investigators also reflected on the fact that emotional responses were not directly measured during the interviews. Instead, in this study, emotional responses were assessed based on participants’ recollections of their responses when encountering Gen AI hyper-personalized advertisements, which they explained through specific examples.

Member checks were conducted with participants representing diverse perspectives to validate themes. Data triangulation was achieved by gathering data from diverse demographics, and consulting experts in marketing, AI, and psychology. An organized audit trail documented the entire research process, including transcripts, guides, and recordings, ensuring transparency and consistency. Investigator triangulation was ensured with two coders and a third reviewer examining the codes. The researcher’s adherence to these strategies ensured trustworthy, accurate, and context-rich insights into Gen Z’s emotional responses to Gen AI-driven hyper-personalized advertisements.

4 Results and discussion

In-depth interviews were conducted on 40 participants to understand their emotional responses to Gen AI-driven, hyper-personalized advertising and its influence on brand interactions. The thematic categories derived from the study are presented below (Table 2).

Table 2

Table 2. Thematic categories.

4.1 Research question 1: what are the emotions elicited by gen AI-driven, hyper-personalized advertisements among consumers?

The study’s findings indicated that participants experienced a wide range of emotions, when encountering these advertisements. In this study, emotional responses were based on participants’ recollections of their experiences when encountering Gen AI-driven hyper-personalized advertisements. These responses reflect their perceived experiences rather than their actual, real-time emotional reactions. Positive emotions such as curiosity, excitement, interest and negative emotions like fear, worry and suspicion were reported in diverse manifestations. These emotions are associated with the generalized concept of Gen AI-driven, hyper-personalized advertising and not with specific advertisements or their messaging. Two sub-themes emerged from the major theme of diverse emotional responses: (1) curiosity and interest (2) fear and suspicion (Figure 1).

Figure 1

Flowchart depicting emotional responses. It starts with

Figure 1. Thematic categories on diverse emotional responses.

4.1.1 Curiosity and interest

This sub-theme describes participants’ experience of a variety of positive emotions when encountering Gen AI-driven, hyper-personalized advertisements. These commercials generate experiential marketing encounters that connect with consumers deeply, resulting in positive feelings like interest, excitement, happiness, and fascination (Bagozzi et al., 2022; Pieters et al., 2002; Zhang et al., 2007). Many participants reported that they find these advertisements to be interesting and captivating. Participant 29 (AH), suggested that these advertisements elicit an immediate interest, prompting viewers to watch them multiple times due to their engaging nature.

“Firstly, I think AI driven ads are really interesting and at least if I watch a single ad once, I'm probably going to watch an AI ad twice or thrice.” (Participant 29, AH)

Participants in the study were curious and intrigued by Gen AI-driven, hyper-personalized advertising content, citing its uniqueness and novel approach compared to traditional advertising (Pieters et al., 2002; Smith et al., 2008). This emotion reflects consumers’ tendency to enjoy and find diverse stimuli interesting, leading to increased engagement and receptivity (Yang and Smith, 2009). Participant 34, DS pointed out.

“I would be intrigued about it because it's something new and something engaging. That was my first reaction. I thought, this is something I want to look into… it was interesting to know that this is how advertising is pushing [itself].” (Participant 34, DS).

This view is also expressed by Participant 6 (SB),

“The ad has created so much curiosity. If it has not convinced the person, it has definitely confused the person.” (Participant 6, SB).

Personalized messages are more persuasive and impacts attention, cognitive responses, and attitudes towards the message (Maslowska et al., 2016). Participant 13 (AY) noted that these advertisements fostered a sense of belonging and made individuals feel special and validated.

“When it is a bit more personalized, you feel like you are more invested in the ad; you are invested more in the brand; you feel like you are part of the brand; that they specifically target you, that, it is just for you and [you get] that feeling of validation - feeling special.” (Participant 13, AY).

The popular, Gen AI-driven, hyper-personalized advertising campaign by Cadbury (Ganguly, 2023) that allowed users to create AI-driven, hyper-personalized birthday songs make recipients feel extremely special, potentially leading to a positive experience for both the recipient of the song and the creator. Participant 33 (FV) shared such a personal experience.

“So, I tried it for a friend of mine…for her birthday and she really liked it because, you see it does sound a bit cringe in tone and everything, okay. But then she actually really enjoyed it. The part that she liked is that her name is taken [mentioned], so, it was a good experience and giving it [the song] as a gift made her feel special.” (Participant 33, FV).

Participant 9 (GC) also referenced Cadbury’s #MyBirthday Ganguly (2023) and noted that the advertisement captured attention by creating an engaging and seemingly magical experience.

“For example, regarding Dairy Milk [chocolates], personalized happy birthday songs are being used [Cadbury’s #MyBirthdaySong]. It sounds a bit magical.” (Participant 9, GC).

Personalization enhances the emotional aspects of engagement by making audience’s feel like the focal point (Casaca and Miguel, 2024). Participant 36 (RS) expressed their opinion on the potential benefits for small businesses when famous celebrity icons endorse their products or shops as in the case of Cadbury’s ‘Not Just A Cadbury Ad’ advertising campaign that featured Shah Rukh Khan (Desk, 2021). The participant highlighted how such endorsements could contribute to business growth and evoke happiness and other positive emotions for the business owners.

“I can talk about this from the perspective of the shopkeepers themselves. They feel super special…they feel very happy when celebrities like Hrithik Roshan, Shah Rukh Khan talk about their shop…they feel very special. They feel very happy and that's a win for any ad.” (Participant 36, RS).

The current findings are consistent with the findings of Matic et al. (2017) that showed that participants experienced positive emotional reactions to highly personalized advertisements, suggesting that these advertisements are effective in capturing attention and eliciting favorable responses.

4.1.2 Fear and suspicion

While initial encounters with Gen AI-driven, hyper-personalized advertisements spark Curiosity and Interest, privacy and data security concerns can moderate their impact on perceived advertising value (Lina and Setiyanto, 2021) as evinced in the sub-theme Fear and Suspicion. This apprehension often stems from awareness of extensive personal data retrieval by advertisers and the potential misuse or exploitation of personal information (Smit et al., 2014; Gironda and Korgaonkar, 2018), a concern that is shared by Participant 29 (AH):

“I think I have two very contrasting perspectives to it. On one hand, it is very interesting because I feel like I'm involved in that particular message. It gives me that connect but, then, there's also this sense of fear, and it can get a little creepy…people might become very conscious of the kind of data that is being put out for use.” (Participant 29, AH).

The ‘creepy’ aspect of Gen AI-driven, hyper-personalized advertising is addressed by several participants. While Participant 13 (AY) reflected on this creepiness, Participant 2(MK) additionally emphasized on how individuals are mere data points for large corporations.

“It is a little bit on the creepy side… because at times when they follow algorithms and they create [ad] content, it is a little bit creepy for me personally.” (Participant 13, AY).

“It's just very creepy… I mean, how big giant corporations are using our data and we are just digits and numerals for them; not real people with identities.” (Participant 2, MK).

This is in line with previous research which posits that moderate personalization of advertisements can increase feelings of creepiness and intrusiveness (De Keyzer et al., 2022).

Innovation inherently entails uncertainty (Kim, 2019) and uncertainty can induce fear, especially with Gen AI-driven, hyper-personalized advertising, where the collection of personal data heightens concerns about privacy and autonomy (Smit et al., 2014; Wang et al., 2022). Similar views regarding data privacy and protection were shared by Participant 27 (GM) and Participant 21 (TK).

“…It seems very big and, to an extent, scary because our data is out there, especially our fears. They can literally control us using our fears and they could sell it to corporations.” (Participant 27, GM).

“It’s just name, location, gender and my background, my interests now; but I don't know what could be the next thing that they would want from me. Yeah, that feeling of anticipation is what makes me fear.” (Participant 21, TK).

While Gen Z accept the use of AI for marketing, they do have higher levels of concern regarding the use of personal data for the same (Jeffrey, 2021). The extensive data demands in such advertising gives rise to skepticism about security and fear of potential misuse, (Helsloot et al., 2019) as expressed by Participant 23 (PB).

“I am really skeptical about the data that is being stored about me and could be definitely used to target me as a consumer.” (Participant 23, PB).

Concerns of privacy invasion and potential data misuse (Bol et al., 2020) can lead to consumer resistance to personalized advertisements (Tucker, 2014). Similar views are shared by participants in this study. Participant 32, KV has expressed that this form of advertising evokes hatred and does not work for them as Gen AI-driven hyper-personalization seeks to analyze and understand human behavior, based on surveillance by marketers and advertisers.

“I would really hate it…it will be very creepy personally. I feel like this is something that shouldn't really exist. I understand why companies would do that, why you would want to have something that is capable of understanding a person's behavior and analyze it…it's very creepy, right. I'm just totally against it. It doesn't work for me”. (Participant 32, KV).

Similarly, Participant 1 expressed that while those familiar with algorithms might accept Gen AI-driven, hyper-personalized advertisements, less tech-savvy individuals could feel anxious, insecure and distressed.

“People who know how algorithms work, it is okay for them; but those who are not up-to- date with that kind of technology, they might just panic. For example, if my grandmother gets a video with her name she would panic - how do they know where I am staying [or] how much I am paying - so that could create panic and it creates insecurity.” (Participant 1, AT).

Summarizing, the sub-themes show that Gen AI-driven, hyper-personalized advertisements, per se, elicit positive emotions of curiosity and interest; however, privacy and surveillance issues related to sourcing of personal data for hyper-personalization are perceived negatively.

4.2 Research question 2: how do gen AI-driven, hyper-personalized advertisements influence consumer interactions with the brand?

Brand interaction refers to the different ways in which a brand relates to its consumers; the outcomes expected from these interactions, and their role in building relationships between a brand and its consumer. The study’s findings indicated that Gen AI-driven, hyper-personalized advertisements have a positive influence on brand interactions and makes for an enhanced brand experience. The major theme of Enhanced Brand Experience has emerged and encompasses three sub-themes: (1) advanced targeted marketing, (2) initial attraction and brand engagement (3) brand connection and loyalty (Figure 2).

Figure 2

Figure 2. Thematic categories on enhanced brand experience.

4.2.1 Advanced targeted marketing

This sub-theme emphasizes how AI is revolutionizing the digital landscape by enhancing customer engagement and experiences (van Esch and Stewart Black, 2021). By utilizing real-time data, AI personalizes advertisements to boost engagement and conversion rates through customer-centric approaches (Arora and Thota, 2024). This idea is further supported by the self-congruity theory (Sirgy, 1982), suggesting that personalization based on the advanced targeted marketing improves the alignment between consumers’ self-concept and the brand, thereby deepening the emotional connection between them. Many participants’ views align with these findings. For instance, Participant 11 (SL), an advertising professional expressed that AI uses real data from users’ online actions to understand individuals precisely and targeted them accurately.

“AI has made it very targeted. It has helped us know exactly who our target audience is, what its exact preferences are. This is not based on information collected through surveys and interviews. It is actual data based on tracking user’s actions…basically, there is this phenomenon where everything we are doing on the internet is like a learning for AI.” (Participant 11, SL)

Participant 2 (MK) shared similar views, noting that hyper-personalization, which tracks searches and displays relevant content on an individual’s feed is highly effective.

“I feel with hyper-personalization in terms of algorithms, they [marketers] are getting to know what you are searching for and then popping up those things on your feed - stuff like that will definitely work.” (Participant 2,MK)

AI in marketing enables precise ad targeting and better consumer interaction through data-driven insights and automation (Bharathi et al., 2024; Abbasi and Esmaili, 2024) and Participant 9 (GC) evinced that this leads to higher conversion rates.

“AI enables precise audience targeting by analyzing user data and predicting which demographics are most likely to respond to specific ads; leading to higher conversion rates…it is cost-effective.” (Participant 9, GC)

Similarly, Participant 1 (AT) noted that Gen AI-driven, hyper-personalized advertising is accurate in capturing people’s attention by tracking their thoughts and activities on various devices.

“AI [hyper-personalized] advertising is extremely accurate in terms of what you want; it captures your mind. It tracks what you are thinking, what you are doing on your cellphones or laptops.” (Participant 1, AT)

Research also indicates that AI use allows for targeted advertising which can enhance brand relationships, purchase intentions, and brand loyalty, which in turn fosters consumer brand engagement and identification (Tran et al., 2020; Babatunde et al., 2024).

4.2.2 Initial attraction and brand engagement

The Initial Attraction and Brand Engagement sub-theme describes participants experiencing a sense of attraction towards Gen AI-driven, hyper-personalized advertisements, which are also perceived as engaging. Participants view personalized advertisements longer compared to non-personalized advertisements (Bang and Wojdynski, 2016; Pfiffelmann et al., 2020). Self-relevant cues such as name, preferences, etc., in personalized advertisements are found to have greater attention-capturing properties (Tacikowski and Nowicka, 2010). Participant 32, (KV) shared their view on this attention-grabbing factor of Gen AI-driven, hyper-personalized advertisements.

“It's always special when someone calls out for your name rather than addressing you as every other hundredth customer. So, I think that's a small aspect of it [in] itself [that] can grab so much attention of mine; and then that a brand gives me exactly what I'm looking for.” (Participant 32, KV).

Individuals are attracted to the co-creational features of these advertisements, such as customizing the birthday song (Ganguly, 2023), citing its relevance to self and usefulness, when compared to traditional advertising (Gaber et al., 2019; Lu, 2016). Participants conveyed that hyper-personalization provides individual-centric messages and engagement, which has a greater appeal compared to the mass messaging of traditional media. Participant 36 (RS) shared a similar view.

“To curate a message to a single person; to each single person rather; helps the objective of advertising [more] than any other traditional forms of media …whatever you gather from your ad is not wasted because it reaches exactly who you want to reach and it appeals to them on a personal level” (Participant 36, RS).

Brand interactivity refers to consumers’ interactions with brands through brand-related information (Daems et al., 2019). When advertisements are personalized, it leads to greater interaction with the brands (De Keyzer et al., 2021). Participant 28 (AJ) expressed that with hyper-personalized advertisements, users can engage with the advertisement, customize their experience, and interact meaningfully with the brand.

“So, as a committed buyer, the brand is speaking to me. I feel like that there is a chance of interactivity, engagement and that's what the consumer wants. And that's where the brand actually succeeds in introducing new products.” (Participant 28, AJ).

Participant 39 (DD) also expressed similar opinions referencing the popular Gen AI-driven, hyper-localized, Zomato advertisement (Ramesh, 2022).

“Major takeaway from this is brand interactivity. So, when you mention the company, the shop near me, I go back to the ad. I went back for the Zomato [ad]. There's the brand interaction that happened - the relationship that's between the brand and the customer.” (Participant 39, DD).

Studies show that AI-powered personalized marketing enhances targeting, engagement (Babatunde et al., 2024; Gautham and Rao, 2024), effectiveness (Sehgal, 2020; Chandra et al., 2022) and customer satisfaction (Singh, 2024). These findings align with participants’ views in the current study, as noted by Participant 7 (KK) that Gen AI-driven, hyper-personalized advertisements make it easy for them to find relevant products, increasing their engagement with the brand.

“I open the [web] site and it is there. I do not have to look. Hyper-personalized ads are a very great way to increase brand engagement.” (Participant 7, KK)

Personalization through customized web experiences, targeted emails, and social media can increase brand reach and awareness (Sehgal, 2020). Similarly, the individual level of personalization afforded by these advertisements allows for greater brand reach as the targeted advertisement becomes exclusive to each person; but this does not translate to purchase intention as elucidated by Participant 2 (MK).

“That level of hyper-personalization would be something that can increase brand reach. But I am not sure if I will buy the product… so, this is just for me to know that this brand exists.” (Participant 2, MK)

AI-based personalized video advertisements increase engagement by 6–9 percentage points over the baseline (Kumar and Kapoor, 2024). The increased engagement and reach from Gen AI-driven, hyper-personalized advertisements enhances brand recall, a key indicator of advertising effectiveness (Mehta and Purvis, 2006). As Participant 2 (MK) noted, Gen AI-driven, hyper-personalized advertisements connect with Gen Z consumers and enhance brand recall by demonstrating genuine engagement efforts. To stand out, brands need unique and creative ideas that will capture attention.

“…Higher brand recall, it's easier to know that this brand is here. Another thing is, at least I know that they are putting some effort in connecting with their consumers… to bring about a different idea, something unique, some more effort and if a brand is creative, people will definitely notice.” (Participant 2, MK)

Gen AI-driven, hyper-personalized advertisements are targeted, attract attention and engage individuals. They improve brand reach and recall and have transformed marketing by enabling personalized customer experiences (Ho and Chow, 2023). These advertisements foster a strong personal brand connection, enhancing consumer responses such as brand loyalty and trust (Mostafa and Kasamani, 2020; De Keyzer et al., 2021).

4.2.3 Brand connection and loyalty

The sub-theme Brand Connection and Loyalty refers to individuals’ relationship with the brand and involves a strong positive emotional response towards the brand (Dick and Basu, 1994). Personalized advertisements allow consumers to relate to a brand that mirrors their own personality, making them feel unique and prestigious (Tran et al., 2020), enhancing brand connection. The theme aligns with Attachment Theory (Bowlby, 1979) which highlights how strong emotional bonds between consumers and brands foster loyalty and establish long-term relationships.

Participant 31 (GY) expressed that Gen AI-driven, hyper-personalized advertisements are appealing, offering a personalized experience that enables consumer to build stronger attachment with the brand.

“I think these hyper-personalized ads are allowing consumers to connect better with a brand…it's giving users a far better and far more personal experience…it also allows for better relationships, like consumer relations with the brand.”(Participant 31, GY).

Participant 30 (AS) noted that these advertisements can establish a powerful personal connection with the consumer and can also stand out in terms of recall.

“… It connects on a personal level. So, I think the only reason why I actually remembered it [Gen AI-driven, hyper-personalized ads] is because it connected with me” (Participant 30, AS).

Research indicates that celebrity endorsements improve brand recall, recognition, image, and purchase intention, particularly when the celebrity is perceived as trustworthy and relatable (Khan and Maheshwari, 2023; Mehmood et al., 2022). This suggests that incorporating celebrities or hyper-personalized celebrity-likeness through Gen AI in advertisements may enhance consumer connect as expressed by Participant 3 (PT) who stated that Gen AI-driven, hyper-personalized advertisements featuring celebrity-likeness (Khan, 2023) feels more meaningful due to the personal touch.

“I think they [Gen AI-driven, hyper-personalized advertisements] are different because they give us a sense of personal touch. A celebrity like Amitabh Bachchan would generally never say your name in public or wish you a happy birthday. When you can get someone like him to do that and it looks very real with technology, I guess, it gives you a sense of importance.” (Participant 3, PT).

A similar view was shared by Participant 14 (MN).

“For some people, it could feel like…the celebrity is actually talking to me, so that would have a positive impact.” (Participant 14, MN).

Relevance theory posits that individuals focus on information pertinent to them and disregard irrelevant content (Sperber and Wilson, 1995). AI enhances relevance by crafting tailored advertising messages and experiences (Gautham and Rao, 2024). Participant 13 (AY) highlighted that these tailored messages in Gen AI-driven, hyper-personalized advertisements create a unique connection to brands, boosting relevance.

“I think one of the biggest positives [of Gen AI-driven, hyper-personalized advertisements] is that you can reach out to every single person, [and make them] feel that this brand is made for you and you alone.” (Participant 13, AY).

Emotional attachment to a brand may influence individuals’ commitment to maintaining a relationship with the brand and a willingness to invest in the brand, indicating brand loyalty (Lee and Workman, 2014; van der Westhuizen, 2018; Shimul, 2022). Participant 37 (SS) made similar observations, stating that when consumers feel emotionally connected to a brand, they are more inclined to be loyal and these advertisements help achieve that.

“I think it's going to be really a good step to build a stronger connection with your customers… I feel it helps their loyalty factor or keeps them coming back for more.” (Participant 37, SS).

Research indicates that Gen AI-driven, hyper-personalized advertisements enhance emotional connections through interactive experiences (Babatunde et al., 2024; Bhuiyan, 2024). Participant 13 (AY) expressed that personalization increased their brand loyalty and they chose to keep their Spotify subscription despite the switch to a paid model because the personalized year-end playlist (Perez, 2023) deepened their appreciation for the service, and reinforced their loyalty.

“Spotify, I used the one [version] where we did not have to pay. We just had to create an account and we had ads in the middle; but then, they started the paid version. I was going to drop it, but then I saw the personalized, customized end of the year Wrapped playlist - all the artists, the amount of time spent, including the minutes on [each] song and I got interested. I was like I will pay for it. I will just go with it. I wanted to stay loyal because I like the personalization that it [Spotify] brings to me.” (Participant 13, AY).

Participant 22 (AB) reiterated these observations, stating that brand connection helps build brand loyalty in the future.

“…It's AI hyper personalized ads, these ads are made in a way that engages the person, on a one-on-one basis with the brand, so they can build more connectivity with the brand; and they can also in the future build up on brand loyalty.” (Participant 22, AB).

Participant 12 (SG) supported this view, noting that Gen AI-driven advertisements increase brand loyalty as these advertisements serve as good talking points and hence, consumer’s actively advocate for the brand.

“It makes for brand loyalty and people's engagement…also, awareness and advocacy and people easily talk about it [advertisement] and refer to the brand.” (Participant 12, SG).

In summary, the sub-theme shows that these advertisements boost engagement, allowing brands to communicate more effectively and connect with consumers.

The findings of the study reveal that participants experienced a diverse range of emotional responses when exposed to Gen AI-driven, hyper-personalized advertisements. Positive emotions, such as curiosity and interest, were noted alongside negative emotions, such as fear and suspicion. The study further elucidated that participants perceived that brand experience is enhanced by the hyper-personalization in these advertisements; positively influencing brand attraction, engagement, connection and loyalty.

The findings, in relation to the theme of brand connection and loyalty, align with Attachment Theory (Bowlby, 1979), which emphasizes that strong emotional bonds between consumers and brands promote loyalty and long-term relationships. The theory suggests that emotionally fulfilling interactions with a brand foster enduring attachments. In this study, participants’ feelings of being understood by the brand contributed to the development of emotional attachment, which may facilitate both increased loyalty and an enhanced brand experience. Relatedness emerged as a key driver of attachment strength, enabling the transition from attachment to loyalty through public engagement. This emotional connection with the brand may further enhance overall brand experience and loyalty (Loureiro et al., 2025). Furthermore, personalized advertising tailored to consumer preferences was found to reinforce emotional attachment and boost engagement (Syaputra and Azhar, 2025). These effects were even more significant when consumers were highly involved with the products (Sukoco and Hartawan, 2011).

The findings support Self-Congruity Theory (Sirgy, 1982), which asserts that consumers prefer brands reflecting their self-image. Participants demonstrated greater engagement with brands aligned to their values and lifestyle, suggesting that AI hyper-personalization strengthens identity alignment and emotional connection. This aligns with the theme of advanced targeted marketing, which proposes that personalization through sophisticated targeting enhances the match between consumers’ self-concept and the brand, deepening their emotional bond. Ultimately, consumers tend to choose brands that resonate with their self-concept, helping to enhance their self-image and move closer to their ideal self (Tooray and Oodith, 2017).

Additionally, the Elaboration Likelihood Model (Petty and Cacioppo, 1986) explains how consumers process advertisements through two routes of persuasion. The central route involves high elaboration, where consumers deeply engage with the advertisements’ content, carefully evaluating its merits and implications (Schumann et al., 2012). In this context, participants reported to meaningfully interact with relevant, tailored advertisements that foster brand connection and loyalty. Conversely, the peripheral route involves low elaboration, where consumers rely on simple cues such as the source’s attractiveness (Schumann et al., 2012). The present results show that this route engages participants through heuristic cues like visual appeal or endorsements, driving initial attraction and engagement. This dual activation enables Gen AI-driven, hyper-personalized advertisements to effectively engage participants, enhancing overall persuasion and brand engagement. Together, the theoretical framework offers strong support for the study’s conclusions. The key findings of the study are illustrated in the form of a conceptual model (Figure 3).

Figure 3

Flowchart illustrating the impact of AI-driven hyper-personalized advertisements. Central node is

Figure 3. Visual representation of the study’s conceptual framework.

5 Theoretical and practical implications

This research makes significant theoretical contributions and also provides practical insights that marketers and advertisers can employ to maximize Gen Z consumers’ interaction with a brand by leveraging Gen AI-driven, hyper-personalized advertisements.

Theoretically, this study identifies and addresses a gap in the existing literature on Gen AI-driven, hyper-personalized advertising. The gap pertains to the emotions associated with this novel form of advertising and its influence on brand interactions. The findings highlight the significance of Gen AI-driven, hyper-personalized advertisements in the marketing mix and emphasizes that personalization, in this case, individualized personalization using AI technologies, is an important part of marketing and is should be a core element of the marketing mix, alongside the traditional 4Ps – product, price, place, promotion and now, personalization. A similar thought was put for by Goldsmith (1999) in the pre-AI era for other forms of personalization.

Previous research has established that young consumers interact with advertisements based on how they appeal to their emotions (Garg and Farooqi, 2018; Rocha-Vilca et al., 2024). The more positive the emotions, the better the involvement with the brand (Wen et al., 2022). As the Conceptual Framework suggests, there are positive outcomes associated with the positive emotions of curiosity and interest, associated with Gen AI-driven, hyper-personalized advertising. They find these advertisements to be exciting and magical. Marketers and advertisers can leverage these interest-generation attributes of hyper-personalized advertisements to create excitement among young people (Bagozzi et al., 2022; Pieters et al., 2002; Zhang et al., 2007), when it comes to the launch of a new brand/a product or a product variant, or, to create a buzz around an existing brand. Variety and creativity in terms of content of Gen AI-generated hyper-personalized advertisements is recommended furthermore, as this would not only sustain interest among Gen Z consumers but would also accelerate the rate of adoption of this innovation (Scheuer, 2021) amid a diverse consumer base.

Moreover, Gen AI-driven, hyper-personalized advertising uses individual-centric demographic or psychographic details which makes young people feel good and special and this can be leveraged to help brands resonate and connect on a deeply personal level (Mogaji et al., 2021). The extreme levels of personalization in these advertisements are perceived to be helpful while searching for products/brands; and personalized search results has a positive effect on brand recall and reach (Trifts and Aghakhani, 2019; Wei et al., 2020).

Consumers want marketers to provide them with a brand experience that touches their hearts, excites or intrigues them (Schmitt, 2009). Subjectivity is an inherent part of the brand experience (Brakus et al., 2009). With Gen AI-driven, hyper-personalized advertisements, the entire process of advertising affords a very subjective brand experience. These advertisements affect emotions towards the brand positively by capturing the attention of the consumer and by encouraging consumers to engage more effectively with the brands. Numerous studies have found that a brand that engages with its consumers through personalized content, connects better and has a greater chance of having a loyal trail of consumers (Tanveer et al., 2023).

The present study has found that Gen AI-driven, hyper-personalized advertisements increase personalized brand connection. Personalization increases emotional connection and affords a deeply personal brand experience to the consumer (Paramita et al., 2021; Tran et al., 2020). When marketers and advertisers utilize the hyper-personalization features inherent in these advertisements to address individuals by name, recommend products according to their preferences and fine-tune advertising messages to suit individual tastes, moods and choices, they add that personal touch to advertising; augmenting the consumer’s personal connect with the brand and enhancing the brand experience. Personalized brand engagement through this advanced form of targeted marketing can be leveraged by the marketing and advertising industry to increase brand reach, recall and most importantly, loyalty.

On the flip side, there are negative emotions associated with these technology-driven advertisements as they are perceived with suspicion and fear. Gen Z find these advertisements to be annoying and creepy. Research has found that Gen AI technology use creates mistrust and diminishes brand authenticity (Brüns and Meißner, 2024). Concerns regarding privacy and data security are real even when consumers welcome the benefits of hyper-personalization, creating a very paradoxical situation (Hanson et al., 2020). AI literacy among Gen Z consumers would help mitigate several of these concerns and help them accept this advertising format seamlessly. Another aspect that can be focused upon is transparency in communication. Labelling advertisements specifically as Gen AI-driven, hyper-personalized advertisements with a link to a standardized data safety protocol would go a long way in easing fear and suspicion among Gen Z consumers - similar to the AI Info feature on Meta products like Instagram (Shivam, 2024). The Advertising Standard Council of India (ASCI) has a set of guidelines on AI use in advertising that recommends including appropriate disclaimers about AI use in marketing materials, a move that can be implemented to enhance transparency (ASCI, 2023). In terms of policy-making, it is recommended that the advertising industry develop and follow a set of standard operating procedures – a standardized data safety protocol - for the ethical use of consumer data for the creation of Gen AI-driven, hyper-personalized advertisements - a call to action based on UNESCO’s recommendation for appropriate level of data protection for micro-targeted advertising (UNESCO Digital Library, 2023).

6 Suggestions for future research

Despite the extensive efforts in this exploratory study, certain limitations suggest avenues for future research. This study was designed to explore participants experiences with Gen AI-driven, hyper-personalized advertisements, but in doing so has not considered specific advertising elements like the colors, fonts, messaging or other persuasion techniques. Future studies can employ structured methods to better differentiate emotional responses to Gen AI-driven, hyper-personalization from other advertising elements. Furthermore, sentiment analysis can be performed to understand the emotional undertones in-depth. Future studies can also delve deeper into the relationship between negative emotions related to this form of advertising and brand interactions, which has found limited scope in this study.

Future research could include advertising and marketing professionals as participants to gain deeper insights. Other factors like prior brand affinity, attitude towards advertising, attitude toward the brand and Generative AI could influence brand connection, emotional responses to such advertisements and may affect purchase decision and these factors warrant further exploration. A thorough investigation into Gen Z’s data privacy concerns is also suggested (e.g., Gupta et al., 2024).

Although the study’s sample is considered large for a qualitative exploration, it is not large enough to generalize the findings and the study remains exploratory. Future research could benefit from integrating mixed method or quantitative approaches with a larger sample, to gain a more comprehensive understanding of the phenomenon and generalize the findings. Furthermore, experimental research, stimulated recall methods and longitudinal studies could be valuable for measuring real-time as well as long-term effects, following exposure to these advertisements.

7 Conclusion

Gen AI-driven, hyper-personalized advertisements evoke diverse emotional responses among Gen Z young adults who perceive these advertisements as targeted marketing efforts that have the capability to improve brand engagement and build personal brand connections, thereby enabling brand loyalty. The potential inherent in Gen AI-driven, hyper-personalized advertising is undeniable and provide immense opportunities for advertisers and marketers to engage and connect with the Gen Z consumers, provided they diligently quell young people’s privacy-related apprehensions about this new dimension in advertising.

Data availability statement

The raw data supporting the conclusions of this paper will be made available on request by the authors.

Ethics statement

The study involving humans were approved by St Joseph’s Research and Innovation Council, St Joseph’s University, Bengaluru, India. The study was conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Confidentiality of recordings and transcripts was ensured.

Author contributions

RP: Conceptualization, Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing. VR: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. SL: Conceptualization, Formal analysis, Investigation, Methodology, Writing – original draft. AM: Data curation, Investigation, Writing – original draft, Writing – review & editing. KN: Data curation, Investigation, Visualization, Writing – review & editing. FY: Formal analysis, Investigation, Writing – original draft.

Funding

The author(s) declare that no financial support was received for the research and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Gen AI was used in the creation of this manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Abbasi, R., and Esmaili, M. (2024). Identifying the applications of artificial intelligence in online marketing. Smart and Sustainable Interactive Marketing, In S. Teixeira and J. Remondes. (Eds.), The use of artificial intelligence in digital marketing: Competitive strategies and tactics: IGI Global. 32–54. doi: 10.4018/979-8-3693-1339-8.ch003