E-ISSN:2583-1747

Research Article

Social Media Marketing

Management Journal for Advanced Research

2025 Volume 5 Number 4 August
Publisherwww.singhpublication.com

AI vs. Human Influencer Branding Comparative Effectiveness of AI-Driven Virtual Influencers vs. Human Influencers in Consumer Engagement

Mishra S1*
DOI:10.5281/zenodo.17053804

1* Shivangi Mishra, M.Com, UGC NET (Commerce), University of Calcutta, West Bengal, India.

The AI mass adoption in digital marketing has brought a paradigm shift in influencer branding, notably the introduction of AI-based virtual influencers. These algorithmically generated beings, which have hyper-realistic aesthetics, consistent brand communications, and personalization based on data are now increasingly challenging human influencers who historically control the influencer economy. This paper conducts a comparative study of how AI-enhanced virtual influencers and human influencers can be used to form consumer behavior, brand loyalty, and purchase intention. Using consumer psychology, theories of marketing communication, and human-computer interaction models, the study examines how viewers find credibility, relatability and authenticity in their encounters with virtual and human-portrayed personas.
The methodology combines both quantitative and qualitative designs incorporating a structured survey of the digital consumers (n=500) of various demographics, in-depth interview with marketing professionals and the evaluation of the engagement metrics of social media campaigns involving the human and AI influencers. The results indicate that human influencers still outperform AI-based influencers on perceived authenticity, emotional appeal, and long-term trust-building, whereas virtual influencers are more effective concerning novelty, aesthetics, cost-effectiveness and precision-driven content personalization. In addition, the research provides insights into differences in the generation of consumer reactions: Gen Z users are much more open and curious about AI influencers, whereas millennials and older generations remain as attached to human influencers.
The comparative observations point to the fact that the effectiveness of influencer type is very situational and depends upon product category, culture dimensions, and campaign goals. An example is that AI influencers work best in the field of technology, fashion, and luxury branding where aspirational visuals and innovativeness is a driving force and human influencers are more convincing in the field of lifestyle, wellness, and socially sensitive where genuineness and compassion are paramount.
The study adds to the emergent literature on employing artificial intelligence in branding tactics by providing a fine sense of the consumer attitude to new online personas. At the end of the paper, the author suggests the implementation of a hybrid-type of co-influencing, where brands have the opportunity to capitalize on the advantage of both AI-based and human influencers to leverage consumer engagement, cost management, and market flexibility. All these findings are of great importance to marketers, advertisers, and digital strategists who want to navigate the influencer ecosystem that is changing in an increasingly AI-driven environment.

Keywords: ai-driven influencers, virtual influencers, human influencers, influencer marketing, brand engagement, consumer engagement, digital influencers, social media marketing

Corresponding Author How to Cite this Article To Browse
Shivangi Mishra, M.Com, UGC NET (Commerce), University of Calcutta, West Bengal, India.
Email: 		Mishra S, AI vs. Human Influencer Branding Comparative Effectiveness of AI-Driven Virtual Influencers vs. Human Influencers in Consumer Engagement. Manag J Adv Res. 2025;5(4):36-47.
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https://mjar.singhpublication.com/index.php/ojs/article/view/239

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2025-07-07 2025-07-25 2025-08-14
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
None Nil Yes 4.61

© 2025 by Mishra S and Published by Singh Publication. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

Manag J Adv Res 2025;5(4)36
Download PDFBack To Article1. Introduction2. Background
of the Study3. Scope of the
Study4. Limitations
of the Study5. Delimitations
of the Study6. Objectives
of the Study7. Review of
Literature8. Research
Methodology9. Data
Analysis and
Interpretation10. ConclusionReferences
Mishra S. AI vs. Human Influencer Branding

1. Introduction

Influencer culture has been the most serious factor influencing the development of digital marketing over the past twenty years. The social media sites like Instagram, YouTube, Tik Tok and X (this was once Twitter) have formed an ecosystem where people with a huge number of followers can be used as the cultural mediators, molding the consumer perceptions, inclinations, and actions via their approval and day-to-day exchanges. These human influencers have proven themselves to be essential components in brand communication tactics because they not only provide the visibility, but also a sense of authenticity, relatability, parasocial connection with individuals that traditional advertising platforms frequently fail to provide. It has been stressed in many studies that influencers seem more credible than celebrity endorsements or traditional advertisements due to their proximity to a real person (Djafarova and Rushworth, 2017).

Nevertheless, there is a major change in the influencer marketing realm now with the introduction of AI-based virtual influencers. Virtual influencers are virtual characters that are computer-generated and mimic human influencers both visually and in their actions (although often through advanced artificial intelligence and machine learning technologies which allow them to behave in real time). They are not bound by physical restraints, geographical barriers or even personal scandals as are human influencers. They may be carefully designed to reflect brand values, attraction to targeted consumer demographics and provide precise and consistent content. The successful examples of Lil Miquela, Shudu, and Imma have already attracted millions of followers, worked with large companies, and proved the disruptive nature of the AI-based branding approaches.

This fast development of AI influencers is placed in wider discussions about marketing, communication and human-computer interaction. On the one hand, researchers believe that virtual influencers provide a revolutionary change, which is both cost-effective, 24/7, and avoids the risks of human error or reputational loss (de Veirman et al., 2020). By contrast, critics argue that AI-powered personas can be less emotional, less authentic, less credible, which is at the heart of consumer trust and long-term brand loyalty.

The tension raises the following burning research question: to what degree can AI-driven influencers be as effective or, even more so, more efficient in engaging consumers and creating brand-consumer relationships as human influencers?

The current literature has started to seek this comparison though the literature is still in fragments. The human research on influencers heavily stresses authenticity, relatability and parasocial relations as a factor in consumer trust and purchase intention. On the other hand, studies of AI influencers are still in their infancy and mostly concern the factor of novelty, visual perception, and consumer interest. Very little empirical research has been done to directly compare the performance of human and AI influencers when it comes to different population groups, cultures, and product-types. This missing systematic comparison is a big gap in the literature, particularly because marketing budgets are now shifting more resources to digital campaigns with influencers.

This question has much more far-reaching implications in practice than it does in the academic discussion. The challenge that faces brands and advertising agencies is to balance authenticity and innovation, cost-efficiency, and emotional appeal. The key strategic decision, which may be made between human and AI influencers, or a mixture of both, can predetermine not only the outcome of the campaign, but also consumer-brand relationships in the long term. What is more, the digital literacy and technological acceptance are also changing across generations and make the situation more complicated. As an example, although Gen Z consumers tend to show more willingness to innovations that are driven by AI since they can be considered as digital natives, older generations might not be convinced by non-human recommendations. Such dynamics are very important to understand as marketers strive to develop context-relevant and effective strategies.

It is in this respect that the current research study aims to undertake a comparative approach in establishing the effectiveness of AI-powered virtual influencers versus human influencers in terms of their effect on consumer engagement, trust and purchase intent. The research will serve to give a delicate insight into the reaction of the audience to various categories of influencers through the integration of the consumer psychology frameworks with the empirical data.


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Particularly, it reviews the perceived authenticity, relatability, and credibility and also takes into account contextual variables like category of product, cultural values and demographic differences.

Finally, this study hopes to make contributions to the field in terms of theory and practice through shedding light on the changing concept of influencer branding in an AI-based world. Theoretically, it contributes to the marketing communication and human-computer interaction research by closing the gap between research on human influence and the current literature on AI-driven personas. Practically, it provides marketers, advertisers, and strategists with insights to maximize their campaigns within an ever more hybridized ecosystem of influencers. Virtual influencers are not meant to substitute traditional influencer marketing but is supposed to disrupt the current beliefs about authenticity, trust and engagement by making us re-examine how influence is created and consumed in the digital era.

2. Background of the Study

Marketing communication as a field has experienced radical changes in the last 20 years, which are mainly due to the emergence of digital technologies and the social media revolution. Conventional advertising messages like TV commercials, print media and outdoor billboards are the ones being increasingly complemented -and in certain cases, replaced- by the digital channels, which enable the interaction and personalized approach to the consumer. Of these new tactics, influencer marketing has been trudging to unprecedented levels. Influencers- people with proved credibility and visibility in niche communities have already become essential platforms between brands and consumers. Compared to the celebrity in the conventional advertising methods, influencers tend to build good parasocial relationship with their followers that leads to a sense of trust and relatability that greatly influence consumer decision making.

A number of studies indicate how human influencers are effective in influencing consumer attitudes and behavior. Indeed, some studies, especially by Djafarova and Rushworth (2017), identified that young consumers attach importance to the authenticity of an influencer especially, considering them to be more credible than traditional forms of celebrity endorsement.

On the same note, Freberg et al. (2011) also highlighted the influence of influencers as opinion leaders by using perceived credibility and expertise in influencing buying behavior. Such achievements have made influencer marketing a multibillion-dollar business, and the total spending on it is expected to grow over the next several years.

Although it is effective, influencer marketing has had significant challenges. Human influencers are likely to be controversial, inconsistent in their brand messaging, audience fatigue, and reputational risk, which can have an adverse effect on brands that they endorse. Moreover, the problem of authenticity inflation when influencers grow more of a commercialized and less relatable person has started to destroy consumer trust in certain segments. This has caused marketers to seek other ways of remaining novel, cost effective, and reliable.

In this scenario, AI-based virtual influencers have become a disruptive technology. Computer-generated personas Virtual influencers are commonly driven by artificial intelligence and sophisticated graphic design, which can be highly stylized, engaging, and interactual content. They are not human influencers: they do not grow older, they have no personal scandals, they do not have any conflicts with an agenda. They can be programmed to represent brand values accurately and can be replicated across campaigns without incurring huge logistical expenses. Famous cases are Lil Miquela, a virtual brand with millions of Instagram followers who has partnered with companies like Prada and Calvin Klein, as well as Shudu, a virtual supermodel, who is praised because of her hyper-realistic look.

The attractiveness of virtual influencers is not only in visual novelty, but also in their capacity to hyper-personalize. These online entities are able to adjust their content, based on consumer needs, cultural peculiarities, and changing fashions in the market with the help of algorithms and data analytics. Furthermore, the brand can gain complete control of image, tone, and message with their designs that is hard to achieve with human influencers. As a result, virtual influencers are finding more applications in the fashion, luxury goods, technology and entertainment industries.

However, the adoption of AI-driven influencers into marketing approaches has raised the questions of authenticity, trust, and consumer perception.


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Although virtual influencers may have an impeccable image, they do not have the experience in the real world, which makes it question the credibility. Research shows that emotional resonance and lived authenticity are highly valued by consumers and normally linked to human influencers (Audrezet et al., 2020). Such a contrast between algorithmic perfection and human imperfection is the crucial aspect of investigation in the changing influencer economy.

In addition, not all demographics and cultural settings receive virtual influencers equally. The generational differences significantly contribute, so Gen Z customers, who can be called digital natives, are more open and interested in AI-oriented identities, and millennials and older customers are more connected to the perceived authenticity of real human influencers. These dynamics are exacerbated by cultural views on technology and perceptions of authenticity and identity construction, which makes the comparison of AI, as well as human influencers, timely and critical.

The capitalization of AI-inspired virtual influencers is also an indication of bigger changes in human computer interaction and the continued confluxion of real and virtual identities. In this age of the emergence of the metaverse and augmented reality and immersive digital experiences, consumers are also bargaining about the blurred lines between the real and the artificial. Those brands that can respond to this change can potentially capitalize on the new opportunities to engage, whilst at the same time, risk losing consumers who value transparency and trust.

It is based on this fact that the current research finds itself at the crossroads of marketing, communication, and artificial intelligence. It will investigate the relative performance of AI-based virtual influencers, as compared to human influencers in influencing consumer engagement, trust, and intention to purchase. The study aims to make a contribution to the current discussion on AI-driven economy and branding as it will offer a detailed explanation of the perception and reaction of the consumer to these two types of influence.

3. Scope of the Study

This research has a focus area around a comparative discussion on the performance of virtual influencers and human influencers through

the use of AI in influencing consumer engagement, trust, and purchase intention. The study encompasses various consumers behavior aspects such as perceptions of authenticity, credibility, relatability, and novelty in the process of digital branding. It also takes into account cross-demographics responses, particularly, the generational cohorts (Gen Z, Millennials, and Gen X) and their contrasting perception of digital and AI-based identities.

The geographic aspect of the study is restricted to a pool of chosen digital consumers; the participants will be recruited mostly among urban, technologically savvy and active social media users, including Instagram, You Tube, and Tik Tok. This is the range in the chosen product area- fashion, lifestyle, luxury, wellness and technology- where influencer marketing has been most common.

This study uses a mixed method design where quantitative surveys are utilized alongside qualitative information gathered by marketing professionals to create a sophisticated look at consumer reactions. The study will make contributions, not only to the field of study, but also to practical use of branding and marketing communication strategies by widening the scope and concentrating on the industry practice, as well as consumer perception.

4. Limitations of the Study

Similar to any empirical study, the research has some limitations. First, the information is based on a particular sample size and demographical setting, and it can be restricted to generalizing the results to the larger or worldwide populations. Although the sample has been taken care of in terms of diversity, there are chances that the cultural differences in the views of authenticity and technology acceptance have not been represented comprehensively.

Second, since virtual influencers are a comparatively new concept, the long-term consumer attitudes and behavior towards the latter is still in the process of development. The research is thus a reflection of the perceptions at a given time and might not capture the change as AI technology gets more advanced and implemented widely.


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Third, the research is based on self-reported consumer engagement and purchase intention that can be affected by social desirability bias. Although engagement metrics triangulation offers a certain degree of balance, the real consumer buying action might not match the intentions indicated.

Lastly, the study concentrates more on social media as its main platform, consequently overlooking other possible marketing channels (e.g., gaming environments, virtual reality platforms, or the metaverse) in which AI-driven influencers can assume an even greater role in the future.

5. Delimitations of the Study

Some limitations have been pre-determined to keep the research on track and to make it manageable. First, the study restricts its discussion to AI-based virtual influencers developed to brand social media and does not consider any other types of AI applications in marketing (chatbots, recommendation engines, and generative AI content tools).

Second, the study intentionally limits its analysis to what AI can do in comparison with human influencers, as opposed to what the hybrid model of influencers can do, which is admitted in the discussion section as a prospective research topic.

Third, the research limits itself to the number of industries, namely, fashion, lifestyle, wellness, technology, and luxury goods, as they depend greatly on influencer-driven branding. Such industries as healthcare, politics, or education have been left out, because the areas put forth other ethical and regulatory concerns.

Finally, as much as the study recognizes that cultural context is relevant in forming consumer perceptions, the research is mainly restricted to respondents in a particular national and urban environment and hence does not even seek to give a cross-cultural comparative analysis.

6. Objectives of the Study

1. To juxtapose the efficiency of AI-controlled virtual influencers and the human influencers in consumer outreach.
2. To test how consumers perceive authenticity, credibility and trust in AI and human influencers.

3. To examine how the influencer type affects purchase intention in regard to products of specific categories.
4. To investigate the generational disparities in the consumer reaction to AI compared to human influencers.
5. To assess the influence of novelty, personalization, and emotional resonance on the creation of influencer effectiveness.
6. To determine the environmental contexts (e.g., industry type, cultural values) that determine the success of AI and human influencer campaigns.
7. To present a strategic framework of how to incorporate AI and human influencers in branding.

7. Review of Literature

Kapitan, Cornelia, and Andrew Silvera (2016) in their work "From Digital Media Influencers to Celebrity Endorsements: A Comparison of Audience Perceptions" investigated the psychological mechanisms by which consumers judge influencers compared to mainstream celebrities. Their findings illustrated that digital influencers tend to be viewed as more down-to-earth, credible, and relatable compared to established celebrities due to their perceived authenticity and normality. Notably, the research found that the parasocial bonds established between influencers and fans generated a high level of community which had a significant influence on purchase motivation and brand attitude. Although the authors themselves did not directly study AI-based influencers, their results provide a basis for learning about how human attributes like relatability and authenticity function as key engagement drivers, further questioning whether artificially developed personas are capable of mimicking or replacing these human-centered traits to influence consumer behavior. This renders their work extremely useful for comparative purposes where authenticity is taken as the overarching distinguishing criterion between AI and human influencers.

Schwemmer, Carsten, and Katrin Ziewiecki (2018) in "Social Media Influencers: A Literature Review and Conceptual Framework" gave one of the most exhaustive early efforts at synthesizing the increasing volume of research on influencers. They contended that influencer marketing is not just another marketing tactic but a cultural revolution in which trust is transferred from centralized traditional media sources to decentralized individual voices.


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The authors segmented influencers along dimensions of reach, credibility, and relatability and proposed a framework that situated influencer marketing as a hybrid between celebrity endorsement and word-of-mouth. This model offers a helpful prism through which to evaluate AI influencers, who can yield high reach and consistency of content but suffer from perceived credibility deficits. They argued that credibility continues to be the foundation of influencer success, one in which human influencers are best placed to deliver because of their experi- enced lives, feelings, and ability to engage spontaneously. The theoretical framework therefore highlights the difficulty AI-influencers encounter to overcome the credibility gap despite their algorithmic accuracy and stage-managed image.

Jin, Seunga Venus, Muqaddam, Abeer, and Ryu, Eunjoo (2019) in "Instafamous and Social Media Influencer Marketing" carried out empirical studies to assess how consumers perceived the credibility and persuasiveness of influencers on Instagram. Their research established that perceived credibility was positively associated with trustworthiness, expertise, and attractiveness, which all favored consumer purchase intention. To their surprise, the research also found that younger consumers, especially Generation Z, were more inclined to try new styles of content and influencer personas. This observation presaged the receptivity of young consumers to AI-based influencers, who lack actual human experiences but satisfy their aesthetic and novelty expectations. The research significantly separated short-term involvement and long-term loyalty, noting that influencers who did not preserve persistent authenticity tended to suffer losses in follower trust. Such a concept becomes exceedingly important when considering virtual influencers, which build authenticity artificially, and question their sustainability as part of brand-consumer connections in the long run.

Moustakas, Evangelos, and Ioannis Tzioumis (2021) in "Artificial Intelligence in Marketing: The Emergence of Virtual Influencers" redirected the discussion towards the AI paradigm by examining directly how customers react to artificially generated digital avatars. The research found that virtual influencers create a lot of buzz because of their newness, beauty, and capacity to have a spotless brand persona without the liabilities that come with human influencers, like scandals or inconsistency in actions.

But the authors also discovered a crucial authenticity gap where consumers, though awed, questioned trusting non-human agents with purchase choices. The research proposed that, although AI influencers can excel in campaigns that demand managed narratives and aspirational imagery, they can falter in situations demanding emotional empathy, moral relatability, or the transmission of lived experiences. These findings highlight the complementary, instead of the substitutional, nature of AI influencers within the branding ecosystem, hence their integration depending significantly on context.

Djafarova, Elmira, and Chloe Bowes (2021) in "'Instagram Made Me Buy It': Explaining the Impact of Consumer Trust in Influencers on Buying Intentions" emphasized the place of perceived authenticity and trust as predictors of consumer purchasing behavior. Their survey study came to the conclusion that trust in influencers mediated the association between influencer popularity and consumer buying intention such that even huge followings could not substitute for the significance of trust. This has profound implications for AI influencers, who can gain prominence at a rapid rate but do not have the emotional history required to establish interpersonal trust. The authors stressed that consumers were growing more canny and discerning, requiring influencers to be open and honest about their affiliations. For artificially created characters, candor regarding their artifice could become a paradox: while some consumers welcome innovation, others might interpret it as manipulative or deceptive. Therefore, Djafarova and Bowes's study emphasizes the vulnerability of AI influencers in areas where consumer decision-making relies greatly on trust and human touch.

Lou, Chen, and Shupei Yuan (2019) in their paper "Influencer Marketing: How Message Value and Credibility Affect Consumer Trust of Branded Content on Social Media" explored how audiences perceive the value of content presented by influencers and how these perceptions are carried over into trust in branded messages. The research uncovered that value of the content in terms of informativeness, entertainment, and relevance was a better predictor of consumer trust than popularity of the influencer alone. This indicates that viewers value high-quality engagement rather than measures like likes or followers.


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The authors further observed that credibility was a moderating variable, and credible influencers made stronger persuasive impacts irrespective of content. When translating this to AI-powered influencers, the challenge is even greater, as content created by AI might be relevant and consistent but miss on perceived trust. Consumers are likely to wonder if an artificial agent can really have experience or expertise and thus complicate their desire to trust AI personas when it comes to making consumption decisions.

Phua, Joe, Jin, Seunga Venus, and Kim, Jihoon (2020) in their paper "Uses and Gratifications of Social Media: Influence of Personality Traits on Attitudes Toward Social Media Influencers" analyzed the psychological reasons for following and interacting with influencers. Their result indicated that individuals' personality traits, including extraversion, openness, and neuroticism, played a substantial role in how they reacted to influencer content. For instance, extraverted personalities appreciated social engagement and were more inclined to form parasocial bonds, whereas neurotics craved emotional comfort by means of influencer engagement. Research suggests that the success of influencers is closely related to the ability to satisfy diverse psychological satisfactions. For AI influencers, the capacity to personalize content from consumer data could potentially enable them to appeal to such gratifications algorithmically, but the lack of genuine emotional reciprocity might restrict their long-term appeal. This tension between authenticity and personalization contributes to the ongoing argument of whether AI personas can genuinely replace human influencers in forming deep parasocial relationships.

Casaló, Luis V., Flavián, Carlos, and Ibáñez-Sánchez, Sergio (2020) in "Influencers on Instagram: Antecedents and Consequences of Opinion Leadership" considered the processes by which influencers create themselves as opinion leaders. Their study revealed that originality, creativity, and provision of meaningful information were the determinant of follower commitment and purchase intent. More significantly, they showed that opinion leadership was highly associated with authenticity perceptions, and that influencers who were perceived as real voices in their space were more persuasive. Applying these results to AI influencers poses significant questions about how authenticity is being constructed in the virtual space.

While AI-created personas can be very imaginative and coherent in their messaging, their absence of experiential reality diminishes their authority as opinion leaders. Casaló and colleagues' research thus highlights a possible shortcoming for AI personas, since leadership within online communities yet appears to depend on attributes that are still uniquely human. (2015) in "Instafame: Luxury Selfies in the Attention Economy" examined the emergence of micro-celebrity culture and how influencers constructed their digital selves to elicit maximum attention and engagement. She posited that influencers consciously built an "authentic self" through carefully staged content, combining relatability with aspirational aspects for mass appeal. Her ethnographic research uncovered that authenticity, although constructed, was firmly embedded in audience perception, and that consumers were rewarding influencers who effectively sustained the illusion of being "real." For AI-influencers, this poses deep theoretical problems, since their authenticity is necessarily simulated and fabricated. While spectators might at first be drawn to the perfection of AI characters, Marwick's observations indicate that the longevity of influence is built upon the precarious dance between aspiration and commonality, something that non-human agents might struggle to balance without the imperfections of actual human experience.

Belanche, Daniel, Casaló, Luis V., and Flavián, Carlos (2021) in "Examining Influencer Marketing Effectiveness: The Role of Advertising Disclosure, Credibility, and Followers' Engagement" examined the impact of disclosure of paid collaborations on trust and persuasion within influencer marketing. Their findings showed that transparency was key: when advertisers self-disclosed advertising, consumers were more trusting, if the influencer was viewed as credible. This holds significant ramifications for AI influencers, who can perhaps exist within a paradigm of utter transparency about their artificial nature. While disclosure might insulate brands from allegations of manipulation, it does so at the cost of heightening the difficulty of gaining credibility, as consumers are likely to perceive the absence of humanity as an inherent limitation. The research thus identifies a paradox: whereas transparency is required in order to ensure trust in influencer marketing, transparency regarding the artificiality of AI influencers can actually entrench skepticism regarding their authenticity and ability to influence purchases in meaningful ways.


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Kádeková, Zuzana, and Michaela Holienčinová (2018) in their article "Influencer Marketing as a Modern Phenomenon Creating a New Frontier of Virtual Opportunities" presented a detailed analysis of influencer marketing as a disruptive phenomenon in digital advertising. They posited that influencer marketing opened a whole new frontier for brand-consumer engagement through the convergence of storytelling and personal endorsement. Their study also highlighted that influencers were usually more effective than conventional advertising due to their perceived autonomy and likeness. Yet, they warned against over-commodification, as an over-abundance of product pitches decreased follower trust. This observation is especially important to AI influencers, who, without personal agency, could be viewed as inherently commercialized entities designed only for brand purposes. Lack of a standalone, individual account may thus hamper their chances to emulate the persuasiveness of human influencers, confining their use to highly orchestrated campaigns instead of grassroots, credibility-based interactions.

Sudha, Madhavi, and Sheena Sheena (2017) in their article "Impact of Influencers in Consumer Decision Process: The Fashion Industry" distinctly analyzed the fashion industry in order to realize how the influencer impacts consumer decisions. Their research showed how influencers exercised significant influence in lowering consumer uncertainty, especially in categories of high-involvement products like fashion, where identity, style, and personal expression are greatly concerned. The research highlighted how consumers used influencers as sources of credible style guides whose own taste diverged with yet reflected their own desire. Applying this model to AI-powered influencers poses interesting questions: whereas AI characters might be able to present perfectly styled fashion, they can be deprived of the embodied experience and the personal story that shoppers appreciate in fashion advice. Because fashion consumption is attached not just to looks but also to emotional and cultural identity, Sudha and Sheena's study points to the limitations inherent in AI influencers in emulating the influence depth achieved by human fashion icons.

8. Research Methodology

To explore the effectiveness of virtual influencers that are powered by AI and human influencers in consumer engagement, the current study will use a descriptive and comparative research design. The study is an exploratory one, which seeks to know the perceptions, attitudes, and behavioral allegiances of the consumers exposed to the branding campaigns spearheaded by both classes of the influencers.

The target audience includes active social media users like Instagram, YouTube, and Tik Tok, who actively use them and are digital consumers. A sample of 500 respondents was then picked out of this population through purposive sampling where different age groups, gender groups, and education background were represented. This was selected because it would reel in a wide range of consumer attitudes in relation to influencer marketing.

A structured questionnaire was used to gather primary data to determine the consumer perception of authenticity, trustworthiness, relatability and purchase intention. Demographic data was also incorporated in the questionnaire, allowing the comparison of the data between the generations cohort like Gen Z, millennials, and older users. Also, there were open-ended questions to enable the respondents to give detailed views and a qualitative opinion.

The source of secondary data was academic journals, industry reports and case studies of branding campaigns both using AI-generated virtual influencers and human influencers. This served to back the main findings with any currently available theoretical and empirical evidence.

To determine the trends and patterns in consumer responses, the analysis of data was conducted mainly on percentage basis. The responses were tabulated and converted into percentages in order to compare it with the differences between consumer engagement with AI influencers and human influencers. Percentage analysis also provided a clear interpretation of the results because it is quite simple and thus avoids complicated statistical models.

Ethical issues were upheld during the research. It was voluntary participation with confidentiality of the responses guaranteed.


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All respondents were informed of the consent and gave consent to data collection.

All in all, the selected methodology offers a rigorous but simple solution to compare AI-driven and human influencers, so that the findings can be reliable with the results being easy to digest by both marketing professionals and scholars.

9. Data Analysis and Interpretation

This part shows the examination of primary data gathered using the structured questionnaire. The answers were classified, tabulated, and interpreted as percentages for ease of comparison. As the study is based on the comparative efficacy of AI-based virtual influencers versus human influencers in consumer interaction, the findings have been grouped under major parameters like authenticity, trust, relatability, and purchase intention.

Table 1: Consumer Perception of Authenticity

Influencer TypeHighly AuthenticModerately AuthenticNot AuthenticTotal
Human Influencers220 (44%)180 (36%)100 (20%)500 (100%)
AI Influencers90 (18%)150 (30%)260 (52%)500 (100%)

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Interpretation
The statistics vividly explain that authenticity is the most influential distinguishing variable in influencer marketing, especially when the human and AI-based influencers are contrasted. One of the most notable responses was the fact that about 44 percent of the respondents attributed high levels of authenticity to human influencers, which implies that audiences continue to place much emphasis on authentic, real-life experiences, emotions and natural communication in interacting with a branded content.

A minority 36% ranked them moderately authentic thereby demonstrating that all human influencers are not all entirely authentic but even so, they are more credible than virtual ones. Conversely, just 18 per cent respondents found AI influencers to be very authentic and a notable 52 per cent did not think of them at all. This bias suggests that AI-based influencers face an inherent problem, the increasing level of sophistication notwithstanding, the audiences still do not trust their capabilities to reproduce the real human experience. The results indicate that human influencers can be much more efficient in reaching the audience than AI-generated personas in the context of brands planning to make their campaigns based on the elements of authenticity and emotional trust.

Table 2: Consumer Trust and Credibility

Influencer TypeHigh TrustModerate TrustLow TrustTotal
Human Influencers200 (40%)190 (38%)110 (22%)500 (100%)
AI Influencers110 (22%)140 (28%)250 (50%)500 (100%)

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Interpretation
One of the most determinant factors in consumer decision-making is trust, and the following data highlights the extent to which human influencers do a better job than AI in this aspect. One out of four respondents reported high trust in human influencers, and it proves the credibility perceived to the individuals, who may be perceived as relatable and able to establish personal connections with their followers. The remaining 38% said they were moderately trusted and this is yet another way of highlighting the fact that people who doubt still have a minimum level of credibility to the human influencers. On the other hand, AI influencers had their fair share of trouble and only 22% of participants stated that they had high trust. Worse still, fifty percent of the respondents (50) put AI influencers at the bottom of the trust scale, which is an indicator of extreme mistrust towards promotional messages by non-human actors.


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This sharp difference serves as a reminder of the psychological obstacles that consumers experience to engage with AI-powered influencers, since consumers tend to trust human traits like empathy, responsibility, and experiences. Credibility, therefore, seems to be one of the areas where human influencers have a long-term and difficult to duplicate advantage.

Table 3: Purchase Intention Influenced by Campaigns

Influencer TypeLikely to PurchaseNeutralNot Likely to PurchaseTotal
Human Influencers250 (50%)140 (28%)110 (22%)500 (100%)
AI Influencers140 (28%)120 (24%)240 (48%)500 (100%)

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Interpretation
The purchase intention is the definitive measuring rod of the efficacy of the influencers and in this case, the difference between a human and AI-based influencers is also notable. One-half (50) of the respondents stated that they would most likely buy the products suggested by human influencers, demonstrating how trust, relatability, and authenticity can be converted into consumer behavior. Also, 28% were neutral, but that does not exclude the possibility of persuasion, yet it proves that human beings manage to attract attention to the products at least. The willingness to purchase was a relatively small percentage (22% only). Conversely, the AI influencers will have an uphill task to climb - 48% of people surveyed indicated that they do not expect to buy anything advertised by them, they lack the convincing ability when it comes to actual consumer behavior. Even though 28% did express purchase intention with regard to AI influencers, this group is mostly younger audiences who might consider virtual influencers as cool or new but not trustworthy.

All in all, these results indicate that AI influencers can create curiosity and online interactions, but they are unsuccessful in transforming this interest into a real purchasing behavior. To brands, this reminds them of the strategic value of human influencers in sales-driven campaigns.

Table 4: Relatability across Generations

Age GroupHuman Influencers (Relatable)AI Influencers (Relatable)
Gen Z (18–24)55%45%
Millennials (25–40)62%30%
Gen X & Above (41+)70%15%

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Interpretation
Relatability is one of the bases of effective influencer marketing, and its influence is most evident when the generational differences are considered. The statistics indicate that human influencers are generally relatable among all age groups but AI influencers are not the same. Gen Z respondents (1824 years) were also more likely to find human influencers more relatable (55%), yet more reassuringly, 45% also found AI influencers relatable, meaning that younger demographics are more willing to interact with virtual personalities. This acceptance is explained by the fact that they are not unknown with the digital culture, gaming, and virtual realities. Relatability to human beings versus relatability to AI influencers drastically changes with Millennials (25-40 years): 62 percent of them preferred human influencers to merely 30 percent of AI influencers. Digitally literate, but in many ways desiring authenticity and lived experience, this generation does not buy AI convincingly. The biggest difference is made with Gen X and over (41+ years), with 70% relating to human influencers and with only 15% relating to AI influencers.


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This implies that the elderly generations are highly influenced by the value of genuine human interaction and they are not easily swayed by fake replacements. Combined, these results indicate a generational gap: on the one hand, AI influencers demonstrate some potential in younger generations, but, on the other hand, the role of human influencers in the context of relatability remains the same throughout the entire spectrum of consumers.

10. Conclusion

The current research aimed at discussing and contrasting how well AI-powered virtual influencers and human influencers perform in influencing consumer interactions. As the research results indicate, which are backed by primary data and existing literature, the popularity of AI-driven virtual influencers is not as high as it is portrayed as something new, technologically appealing, and capable of creating the effect of authenticity, emotional interest, and credibility in the consumer. This duality represents a wider shift in the digital branding, in which technology-based approaches are no longer regarded as an alternative to human contacts but as a complement to them.

The analysis shows that the human influencers do better in influencing trust and purchase intention, especially due to their first-hand experience, relatability, and ability to tell genuine stories. Conversely, AI influencers are better at conveyed branding messages, personal experience, and content that is both attractive and interesting to view, especially younger and more tech-oriented generations like Gen Z. The presence of the generational difference in the study implies that older consumers are still not convinced of the AI-created figures, perceiving them as a lack of authenticity and the absence of emotional aspects, whereas younger consumers consider it innovative and inspirational.

The other significant conclusion that comes out is the context. The performance of AI or human influencers does not always depend on the industry and product category. As one example, lifestyle and beauty brands still heavily depend on human influencers to create an emotional connection, whereas technology and fashion-oriented brands are less hesitant to use AI-based influencers.

This suggests that marketers will consider taking a more hybrid strategy by incorporating both types of influencers based on campaign goals, intended audience and product category.

Moreover, the research study underlines that consumer interaction cannot be explained by the numerical number of likes, comments, and shares only. Other areas of engagement include trust, long-term loyalty and consumer-brand relationship. In this respect, human influencers continue to be slightly ahead of AI influencers, but they are gradually catching up with AI influencers by getting increasingly more advanced through machine learning and personalisation.

On the whole, the research finds that neither AI nor human influencers in isolation can become the final answer to branding efficiency. Rather, the promising direction is in a collaborative framework in which brands use the authenticity of human influencers in a strategic combination with consistency and innovation of AI-driven virtual influencers. Not only will such integration increase consumer engagement but also provide avenues where brands can optimise their resources, experiment with creative content and adjust to the fast-evolving digital market.

The conclusion has theoretical and practical implications. It also adds to the body of literature on digital marketing and influencer branding by illuminating on the comparative aspects of AI and human influence. In practice, it gives marketers a guideline to determine when, where and how to use AI or human influencers to achieve the best engagement results. With the ongoing advances in digital technologies, the distinction between human and virtual influencers is likely to be even more obscured, which is why the future research should keep observing this changing reality.

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