Contemporary Journal on Business and Accounting (CjBA) Vol.
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Page 1-15 Audience Responses to Advertisements Using Artificial Intelligence: A Case Study on Film Promotion Ana Rimbasari1 Agniya Thahira2 Amalina Nur Arifah3 Universitas Siber Muhammadiyah1,2,3 Received 16 September 2025 Revised 20 April 2026 Accepted 26 April 2026 E-mail: anarimbasari@sibermu.
Correspondence Author
ABSTRACT
Purpose Ae This study examines audience responses to advertisements utilizing artificial intelligence (AI) in film promotion campaigns conducted via social media The advertisements employ AI technology to create interactive content for promotional purposes.
Design/methodology/approach Ae The research adopts a qualitative descriptive approach through a case study method, data were gathered via in-depth interviews and analyzed using triangulation techniques.
Findings Ae The findings indicate that the majority of audiences responded positively, perceiving the advertisements as innovative, engaging, and relevant to contemporary issues.
AI-driven advertisements were considered effective in clearly conveying the intended message.
However, some audiences faced difficulties in understanding the technical aspects of AI, with certain individuals unaware of its application in the advertisements.
The campaign successfully enhanced audience engagement and reinforced the brandAos image as an innovative Originality Ae This study offers insights into the effectiveness of AI in marketing communication strategies within the entertainment industry.
Keywords: Artificial Intelligence.
Audience Response.
Marketing Communication.
Film Advertising.
Social Media.
Paper Type Research Result
Contemporary Journal on Business and Accounting A Institut
Transparansi dan Akuntabilitas Publik
(INSPIRING)
Contemporary Journal on Business and Accounting (CjBA) Vol.
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INTRODUCTION
The rapid advancement of digital technologies has significantly reshaped the advertising landscape, particularly within the entertainment industry, where innovative strategies are critical for capturing audience attention and enhancing brand engagement.
Artificial intelligence (AI) has emerged as a transformative tool in marketing communications, enabling the creation of interactive and personalized content tailored to audience preferences (Choudhury & Harrigan.
In the context of film promotion.
AI-driven advertisements on social media platforms offer dynamic and engaging experiences, fostering stronger connections between brands and their audiences.
This technological evolution aligns with the principles of Integrated Marketing Communication (IMC), which emphasizes coordinated communication channels to deliver consistent and persuasive messages (Kotler & Armstrong, 2.
The integration of AI into social media advertising has revolutionized the creation and delivery of film promotions.
AI facilitates the analysis of large datasets, enabling marketers to predict audience preferences and develop tailored content that enhances engagement (Yusup et al.
, 2.
Social media platforms, such as Instagram, have become pivotal channels for disseminating AI-driven promotional content due to their extensive reach and interactive features, including stories and reels (Rahmadani et al.
, 2.
These platforms enable direct audience engagement, fostering a two-way communication dynamic that amplifies brand visibility and interaction.
Despite the benefits of AI in advertising, its application in film promotion raises questions about audience perception and comprehension.
While AI-driven content is often perceived as innovative, its technical complexity may not be fully understood by all audience segments, potentially impacting message effectiveness (Nuraini, 2.
Moreover, the use of AI in advertising, particularly in the Indonesian context, remains underexplored, with limited research examining audience responses to such campaigns.
This gap is significant, as understanding audience reactions is essential for evaluating the efficacy of AI-driven marketing strategies and their influence on brand perception and consumer behavior.
The integration of artificial intelligence (AI) into social media advertising has transformed film promotion strategies, offering innovative ways to engage audiences through interactive and personalized content (Choudhury & Harrigan.
However, despite the growing adoption of AI in marketing communications, there is a significant gap in understanding how audiences, particularly in the Indonesian context, perceive and respond to AI-driven advertisements for films (Nuraini, 2.
Existing research has primarily focused on the technical capabilities of AI in marketing or its application in other industries, such as news media (Nuraini, 2.
, but limited studies have explored audience reactions to AI-driven film promotion campaigns on social media This gap is critical, as audience perception directly influences the Contemporary Journal on Business and Accounting (CjBA) Vol.
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Furthermore, while AI-driven advertisements are often perceived as innovative, their technical complexity may pose challenges for audience comprehension, potentially limiting their impact (Nuraini, 2.
Some audiences may not recognize the use of AI in advertisements or understand its role in shaping the content, which could affect message clarity and engagement (Rahmadani et al.
Additionally, the lack of empirical studies on the effectiveness of AI-driven campaigns in the Indonesian entertainment industry underscores the need to investigate whether these advertisements successfully enhance audience engagement and strengthen brand image.
This study addresses the problem: How do audiences perceive and respond to AI-driven advertisements for film promotion on social media platforms, and what challenges arise in their comprehension of AI technology? The primary objective of this research is to analyze audience responses to AIdriven advertisements for film promotion on social media platforms, with a focus on their perceptions of innovation, engagement, and relevance to contemporary Specifically, the study aims to:
Identify the extent to which audiences perceive AI-driven advertisements as innovative and effective in conveying promotional messages.
Explore the challenges faced by audiences in understanding the technical aspects of AI used in these advertisements.
Evaluate the impact of AI-driven campaigns on audience engagement and brand perception within the entertainment industry.
The scope of this study is limited to analyzing audience responses to AIdriven film promotion advertisements on social media platforms, such as Instagram, within the Indonesian context.
The research employs a qualitative descriptive approach, using a case study method with data collected through indepth interviews, observations, and documentation of social media content (Rahmadani et al.
, 2.
The study focuses on audiences who are active social media users and have engaged with film promotion campaigns.
Limitations include the relatively small sample size of interviewees, which may not fully represent the diverse Indonesian audience, and the scarcity of recent theoretical studies on AI-driven advertising in Indonesia, which restricts the depth of comparative analysis (Nuraini, 2.
Additionally, the study does not examine other advertising channels, such as traditional media or physical promotions, to maintain a focused analysis on social media platforms.
LITERATURE REVIEW
Related Work The integration of artificial intelligence (AI) into marketing communications has been widely studied, particularly in the context of enhancing customer engagement and personalizing content.
Choudhury and Harrigan (Choudhury & Contemporary Journal on Business and Accounting (CjBA) Vol.
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explored the transition from traditional customer relationship management (CRM) to social CRM, highlighting how technologies like AI enable interactive and dynamic communication on social media platforms.
Their findings suggest that AI-driven tools improve audience engagement by analyzing user behavior and tailoring content, a principle applicable to film promotion campaigns on platforms like Instagram.
Similarly.
Kotler and Armstrong (Kotler & Armstrong, 2.
emphasized the role of Integrated Marketing Communication (IMC) in coordinating multiple channels to deliver consistent messages, noting that technology enhances the effectiveness of promotional strategies.
These studies provide a foundation for understanding how AI can amplify marketing efforts in the entertainment industry.
Several studies have investigated the impact of social media advertising on audience behavior.
Rahmadani et al.
(Rahmadani et al.
, 2.
analyzed the influence of NetflixAos Instagram campaigns on user interest, finding that visually appealing and interactive content significantly increases engagement.
Their study, however, did not explore the role of AI in creating such content, focusing instead on general promotional strategies.
In a related study.
Nirwana et al.
(Yusup et al.
examined AIAos role in digital marketing, identifying its ability to predict audience preferences and optimize content delivery as key advantages.
They noted that AI-driven advertisements are perceived as innovative but may alienate audiences unfamiliar with the technology, a finding relevant to this studyAos focus on audience comprehension.
Nuraini (Nuraini, 2.
conducted a case study on AI applications in Indonesian media, specifically analyzing audience responses to AI-generated news presenters.
The study found that while audiences appreciated the novelty of AI, many struggled to understand its technical aspects, leading to mixed perceptions of credibility and effectiveness.
This aligns with the current studyAos interest in audience comprehension of AI-driven advertisements but differs in context, as NurainiAos work focused on news media rather than entertainment.
Additionally.
Porcu et al.
(Porcu et al.
, 2.
argued that IMCAos success depends on aligning technological innovations with audience expectations, suggesting that AI-driven campaigns must balance innovation with clarity to maximize impact.
Beyond marketing, studies on audience behavior provide insights into how technological innovations are perceived.
Mehrabian and Russell (Mehrabian & Russell, 1.
proposed the Stimulus-Organism-Response (SOR) framework, which posits that environmental stimuli .
AI-driven advertisement.
influence emotional responses, which in turn affect behavioral outcomes like engagement.
This framework is relevant to understanding how AI content on social media elicits audience reactions.
Similarly.
Zeithaml et al.
(Zeithaml et al.
, 1.
found that perceived service quality, including the innovativeness of communication, positively influences consumer behavior, supporting the hypothesis that AIdriven advertisements can enhance brand perception if effectively implemented.
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First, while studies like Nirwana et al.
(Yusup et al.
, 2.
and Choudhury and Harrigan (Choudhury & Harrigan, 2.
highlight AIAos potential in digital marketing, they primarily focus on technical capabilities or broad applications, with limited attention to audience perceptions in specific industries like Rahmadani et al.
(Rahmadani et al.
, 2.
explored social media campaigns but did not address the role of AI, leaving a gap in understanding how AI-driven content influences audience engagement in film promotion.
Second, research on AI applications in Indonesian media, such as NurainiAos (Nuraini, 2.
study, focuses on contexts like news rather than entertainment, limiting its applicability to film advertising.
The entertainment industry, particularly film promotion, relies heavily on emotional and visual appeal, which may elicit different audience responses to AI compared to informational content.
Furthermore, the technical complexity of AI, as noted by Nuraini (Nuraini, 2.
and Nirwana et al.
(Yusup et al.
, 2.
, may pose comprehension challenges for audiences, yet few studies have explored this issue in the context of social media advertising for films.
Third, while the IMC framework (Kotler & Armstrong, 2024.
Porcu et al.
and SOR model (Mehrabian & Russell, 1.
provide theoretical lenses for understanding marketing communication and audience behavior, their application to AI-driven film promotion in Indonesia remains underexplored.
The lack of empirical studies on how Indonesian audiences perceive AI-driven advertisements, particularly on platforms like Instagram, underscores the need for this research.
This study addresses these gaps by examining audience responses to AI-driven film promotion campaigns on social media, focusing on perceptions of innovation, comprehension challenges, and impacts on engagement and brand
RESEARCH METHODOLOGY
This study adopts a qualitative descriptive approach with a case study method to explore audience responses to AI-driven advertisements for film promotion on social media platforms.
The qualitative design is selected to capture detailed insights into audience perceptions, emotions, and comprehension challenges, aligning with the research objectives of assessing innovation, engagement, and brand impact (Kotler & Armstrong, 2024.
Mehrabian & Russell.
The case study method enables an in-depth examination of a specific AIdriven film promotion campaign on Instagram, providing contextual depth to understand audience reactions in the Indonesian entertainment industry (Hollweck, 2.
By relying solely on in-depth interviews as the data source, the study prioritizes subjective experiences to address the research question.
This Contemporary Journal on Business and Accounting (CjBA) Vol.
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Data Collection Data were collected exclusively through in-depth, semi-structured interviews with five informants.
This method was chosen to obtain rich, qualitative data on audience perceptions of AI-driven advertisements, allowing for detailed exploration of individual experiences and opinions (Clarke & Braun, 2.
Interviews are well-suited to the studyAos objectives, as they enable informants to articulate their views on the innovation, effectiveness, and comprehension challenges of AI-driven content, providing nuanced insights into engagement and brand perception (Mehrabian & Russell, 1.
This sampling method ensures that informants are relevant to the studyAos focus on audience responses in the Indonesian context (Rahmadani et al.
, 2.
Five informants were deemed sufficient for a qualitative case study, as this number allows for in-depth analysis while achieving data saturation, where no new themes emerge (Hollweck, 2.
The interview guide included open-ended questions, such as AuHow do you perceive the use of technology in film promotion advertisements on Instagram?Ay and AuWhat challenges, if any, do you face in understanding these advertisements?Ay These questions were designed to elicit responses aligned with the objectives of evaluating perceived innovation, comprehension, and engagement.
Interviews were conducted in Bahasa Indonesia, audio-recorded with informantsAo consent, and transcribed verbatim to maintain data integrity.
Each interview lasted approximately 45Ae60 minutes, ensuring sufficient time to explore informantsAo perspectives thoroughly.
The exclusive use of interviews, rather than additional methods like observation or documentation, was chosen to focus on subjective audience experiences, which are central to understanding perceptions of AI-driven advertisements (Clarke & Braun, 2.
This approach aligns with the qualitative paradigm, where depth of insight is prioritized over breadth of data Analysis Techniques Data analysis was performed using qualitative thematic analysis to identify patterns and themes in audience responses.
Thematic analysis was selected for its flexibility in capturing recurring ideas related to perceived innovation, comprehension challenges, and engagement, directly addressing the research objectives (Clarke & Braun, 2.
This method is particularly suitable for interview data, as it allows for systematic exploration of informantsAo subjective experiences (Creswell, 1.
Transcribed interview data were coded iteratively using the following steps:
Open Coding: Initial codes were generated by reading transcripts line-by-line to identify concepts, such as Auinnovative visuals,Ay Auconfusion about AI,Ay or Contemporary Journal on Business and Accounting (CjBA) Vol.
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Ay This step ensured that analysis remained grounded in informantsAo words.
Axial Coding: Codes were grouped into broader themes, such as Auperceived innovation,Ay Aucomprehension difficulties,Ay and Aubrand engagement,Ay establishing relationships between categories.
For example, expressions of confusion about AI were linked to barriers in message clarity.
Selective Coding: Final themes were refined to focus on those most relevant to the research objectives, ensuring a coherent narrative of audience responses.
NVivo software was used to manage and organize codes, enhancing analytical efficiency and transparency.
The thematic analysis was guided by the StimulusOrganism-Response (SOR) framework (Mehrabian & Russell, 1.
, which posits that AI-driven advertisements .
influence audience emotions .
and behaviors .
, such as engagement.
This framework helped structure the analysis to align with the objective of evaluating campaign effectiveness.
The exclusive reliance on interview data required rigorous coding to ensure depth, making thematic analysis an appropriate choice for capturing the complexity of audience perceptions (Clarke & Braun, 2017.
Creswell, 1.
Validation To ensure the reliability and validity of findings derived solely from interview data, several validation strategies were implemented:
Member Checking: Interview transcripts and preliminary findings were shared with informants to verify accuracy and confirm that their responses were correctly interpreted.
This process enhanced credibility by ensuring that audience perspectives were faithfully represented (Clarke & Braun, 2.
Informants were given the opportunity to clarify or expand on their statements, reducing the risk of Peer Review: The coding process and thematic analysis were reviewed by a colleague with expertise in qualitative research to assess the consistency and logic of identified themes.
Feedback was incorporated to refine categories, ensuring analytical rigor and minimizing researcher bias (Hollweck, 2.
This step was particularly important given the single data source, as it provided an external perspective on the analysis.
Reflexivity: The researcher maintained a reflexive journal to document assumptions and potential biases during data collection and This practice enhanced transparency and ensured that interpretations remained grounded in the data rather than influenced by preconceptions (Creswell, 1.
These validation methods were chosen to address limitations inherent in using only interview data, such as potential selection bias in purposive sampling and the subjective nature of qualitative insights.
Member checking and peer review mitigated the risk of misinterpretation, while reflexivity ensured analytical However, the study acknowledges limitations, including the small sample size of five informants, which may not fully represent the diverse Contemporary Journal on Business and Accounting (CjBA) Vol.
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observation or documentatio.
, which could have provided additional context (Hollweck, 2.
Despite these constraints, the validation strategies ensure that findings are robust and aligned with the objectives of understanding audience perceptions of AI-driven film promotion on social media (Kotler & Armstrong.
Mehrabian & Russell, 1.
RESULT AND DISCUSSION
This section presents the findings from the thematic analysis of in-depth interviews conducted with five informants to explore audience responses to AIdriven advertisements for film promotion on social media platforms, specifically Instagram.
The analysis identified key themes related to perceptions of innovation, comprehension challenges, and engagement, aligning with the research objectives.
The findings are summarized in a table, followed by a detailed description of trends and patterns, and an interpretation of their significance.
Key findings The thematic analysis of interview data revealed three primary themes: .
perceived innovation, .
comprehension challenges, and .
engagement and brand perception.
Table 1 summarizes these themes, their descriptions, and the frequency of informant responses, highlighting the prevalence of each theme.
Table 1: Summary of Key Themes from Interview Analysis Theme Description Perceived Innovation Advertisements were viewed as creative, novel, and relevant to contemporary issues.
Comprehension Difficulties in understanding Challenges AIAos role.
some unaware of AI use in advertisements.
Engagement and Increased interest in the film and Brand Perception Informants Mentioning .
Perceived Innovation: Four out of five informants described the AI-driven advertisements as innovative, citing their use of interactive and visually appealing content on Instagram.
For example, informants noted that the advertisements featured dynamic visuals that adapted to user interactions, making them stand out compared to traditional promotions.
One informant stated.
AuThe ads felt fresh and modern, like they were made for todayAos audience.
Ay This perception was linked to Contemporary Journal on Business and Accounting (CjBA) Vol.
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Comprehension Challenges: Two informants reported difficulties understanding the technical aspects of AI in the advertisements.
One informant expressed confusion about how the content was generated, stating.
AuI didnAot know it was AI.
I thought it was just a fancy video.
Ay Another was unaware that AI was involved until prompted during the interview.
These challenges suggest that the technical complexity of AI may not be immediately apparent to all audiences, potentially affecting message clarity (Nuraini, 2.
Engagement and Brand Perception: Four informants reported increased engagement with the campaign, expressing heightened interest in the promoted film and a willingness to explore related content on Instagram.
They also perceived the brand as innovative, with one informant noting.
AuThis makes the company seem ahead of the game.
Ay The campaignAos ability to foster interaction, such as through likes or comments, was highlighted as a key driver of engagement, reinforcing positive brand associations (Rahmadani et al.
, 2.
The findings indicate a predominantly positive response to AI-driven advertisements, with most informants appreciating their creativity and engagement potential.
However, comprehension challenges among a minority suggest variability in audience understanding of AI technology.
Interpretation of Results The findings align with the research objectives of evaluating audience perceptions of innovation, comprehension challenges, and engagement in AIdriven film promotion campaigns on social media.
The high prevalence of perceived innovation .
/5 informant.
supports the notion that AI enhances the appeal of advertisements by offering novel and contextually relevant content (Choudhury & Harrigan, 2014.
Yusup et al.
, 2.
This aligns with the StimulusOrganism-Response (SOR) framework (Mehrabian & Russell, 1.
, where AIdriven visuals .
evoke positive emotional responses .
, such as excitement or curiosity, leading to engagement .
The relevance to contemporary issues further strengthens the campaignAos impact, as audiences value advertisements that reflect societal concerns (Kotler & Armstrong, 2.
The comprehension challenges reported by two informants highlight a critical barrier to the effectiveness of AI-driven campaigns.
As noted by Nuraini (Nuraini, 2.
, technical complexity can hinder audience understanding, particularly in contexts where AI is novel, such as Indonesian entertainment advertising.
This finding suggests that while AI enhances innovation, its implementation must be accompanied by clear communication to ensure accessibility.
The fact that some informants were unaware of AIAos role underscores the need for campaigns to balance technological sophistication with transparency, aligning with Integrated Marketing Communication (IMC) principles that emphasize message clarity (Porcu et al.
, 2.
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/5 informant.
indicate that AI-driven advertisements successfully achieve marketing objectives by fostering audience interaction and enhancing brand image (Rahmadani et al.
This supports Zeithaml et al.
Aos (Zeithaml et al.
, 1.
assertion that innovative communication strategies improve consumer behavior outcomes, such as interest and loyalty.
The campaignAos success on Instagram reflects the platformAos effectiveness as a channel for interactive content, corroborating Rahmadani et al.
Aos (Rahmadani et al.
, 2.
findings on social mediaAos role in audience engagement.
However, the small sample size limits generalizability, suggesting that broader studies are needed to confirm these trends across diverse audiences (Hollweck, 2.
These results contribute to the literature by addressing the gap in understanding audience responses to AI-driven film promotion in Indonesia (Nuraini, 2024.
Yusup et al.
, 2.
They highlight the dual nature of AI in advertising: its potential to drive innovation and engagement, and the challenge of ensuring audience comprehension.
The findings underscore the importance of integrating AI with clear messaging within an IMC framework to maximize campaign effectiveness (Kotler & Armstrong, 2024.
Porcu et al.
, 2.
DISCUSSION
This section interprets the implications of the studyAos findings on audience responses to AI-driven advertisements for film promotion on social media platforms, specifically Instagram, in the Indonesian context.
The findingsAi perceived innovation, comprehension challenges, and enhanced engagement and brand perceptionAiare analyzed in relation to existing literature, highlighting their significance in marketing communications.
Comparisons with prior studies are drawn to contextualize the results, followed by an acknowledgment of limitations and recommendations for future research.
Comparison with Prior Research The studyAos finding that four out of five informants perceived AI-driven advertisements as innovative aligns with prior research on AIAos role in marketing.
Choudhury and Harrigan (Choudhury & Harrigan, 2.
noted that AI enhances customer engagement through personalized and interactive content, a trend reflected in this studyAos observation of dynamic visuals on Instagram that captivated audiences.
Similarly.
Nirwana et al.
(Yusup et al.
, 2.
found that AIdriven marketing campaigns are perceived as novel, increasing their appeal, which corroborates the positive audience responses in this study.
The relevance of advertisements to contemporary issues, such as environmental or social themes, further supports Kotler and ArmstrongAos (Kotler & Armstrong, 2.
Integrated Marketing Communication (IMC) framework, which emphasizes the importance of contextually resonant messaging to strengthen campaign effectiveness.
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Nuraini (Nuraini, 2.
observed that audiences in Indonesia appreciated AIAos novelty in media but often struggled to understand its technical aspects, a finding mirrored in this study where some informants were unaware of AIAos role in advertisements.
This contrasts with Rahmadani et al.
Aos (Rahmadani et al.
, 2.
study, which reported high engagement with Instagram campaigns but did not address AI-specific comprehension issues, suggesting that AIAos technical complexity introduces unique challenges not present in traditional social media advertising.
The Stimulus-Organism-Response (SOR) framework (Mehrabian & Russell, 1.
provides a lens to explain this, as the stimulus (AI-driven conten.
may evoke mixed emotional responses .
, excitement or confusio.
depending on audience familiarity with technology.
The strong engagement and positive brand perception reported by four informants align with Zeithaml et al.
Aos (Zeithaml et al.
, 1.
assertion that innovative communication strategies enhance consumer behavior outcomes, such as interest and brand loyalty.
This study extends Rahmadani et al.
Aos (Rahmadani et al.
, 2.
findings by demonstrating that AI-driven campaigns on Instagram not only increase user interest but also position the brand as innovative, a critical factor in the competitive entertainment industry.
However, unlike Porcu et al.
Aos (Porcu et al.
, 2.
emphasis on seamless integration across multiple channels, this studyAos focus on a single platform (Instagra.
suggests that AIAos effectiveness can be significant even within a limited scope, provided the content is engaging and Limitations The study has several limitations that may affect the generalizability and depth of the findings.
First, the reliance on a small sample of five informants, while appropriate for a qualitative case study (Hollweck, 2.
, limits the representativeness of the findings across the diverse Indonesian audience.
The purposive sampling method, although aligned with the studyAos objectives, may introduce selection bias, as informants were primarily active Instagram users familiar with film promotions (Rahmadani et al.
, 2.
This may not capture perspectives from less tech-savvy or less engaged audiences.
Second, the exclusive use of in-depth interviews as the data source, while providing rich subjective insights, restricts the ability to corroborate findings with objective data, such as social media analytics or visual content analysis (Clarke & Braun, 2.
This limitation reduces the studyAos capacity to assess the broader impact of the campaign, such as actual engagement metrics .
, likes, comment.
Third, the scarcity of recent theoretical studies on AI-driven advertising in Indonesia, as noted by Nuraini (Nuraini, 2.
, constrained the depth of comparative analysis, limiting the studyAos ability to contextualize findings within a robust local framework.
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Future Research To address the limitations and build on the findings, several avenues for future research are proposed.
First, expanding the sample size and diversity of informants, including those with varying levels of social media engagement and technological literacy, would enhance the generalizability of findings (Hollweck.
Including audiences from different demographic groups .
, age, gender, urban vs.
could provide a more comprehensive understanding of AI-driven advertisement perceptions in Indonesia.
Second, incorporating additional data sources, such as social media analytics .
, engagement rate.
or content analysis of Instagram posts, would strengthen the studyAos findings by providing objective measures to complement subjective interview data (Clarke & Braun, 2.
This mixed-methods approach could validate the reported engagement and brand perception impacts.
Third, comparative studies examining AI-driven versus non-AI-driven film promotion campaigns on social media could clarify the unique contributions of AI to audience responses, addressing the gap noted in prior studies (Rahmadani et al.
, 2023.
Yusup et al.
, 2.
Finally, exploring AI-driven campaigns across multiple social media platforms .
Instagram.
TikTok.
Twitte.
would provide insights into channelspecific effects, aligning with the IMC frameworkAos emphasis on multi-channel integration (Porcu et al.
, 2.
Future research could also investigate the role of educational elements in campaigns to improve audience comprehension of AI, potentially mitigating the challenges observed in this study (Nuraini, 2.
These directions would contribute to a deeper understanding of AIAos role in marketing communications within the Indonesian entertainment industry.
CONCLUSION
This study investigated audience responses to AI-driven advertisements for film promotion on social media platforms, specifically Instagram, addressing the research question: How do audiences perceive and respond to AI-driven advertisements for film promotion on social media platforms? The research was motivated by the increasing adoption of artificial intelligence (AI) in marketing and the lack of empirical studies on audience perceptions in the Indonesian entertainment industry (Nuraini, 2024.
Yusup et al.
, 2.
Using a qualitative descriptive approach with a case study method, data were collected through indepth interviews with five purposively selected informants who were active Instagram users familiar with film promotions (Hollweck, 2016.
Rahmadani et al.
Thematic analysis revealed three key findings: .
most informants .
perceived the advertisements as innovative due to their interactive and contextually relevant content, .
faced comprehension challenges Contemporary Journal on Business and Accounting (CjBA) Vol.
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the majority .
reported increased engagement and a positive brand image, viewing the brand as innovative (Mehrabian & Russell, 1974.
Zeithaml et al.
, 1.
The findings indicate that AI-driven advertisements effectively enhance audience engagement and brand perception by leveraging novel, interactive content that resonates with contemporary issues (Choudhury & Harrigan, 2014.
Kotler & Armstrong, 2.
However, comprehension challenges highlight the need for clearer communication about AIAos role to ensure accessibility (Nuraini, 2.
These results align with the Stimulus-Organism-Response (SOR) framework, where AI-driven content .
evokes positive emotional responses .
leading to engagement .
(Mehrabian & Russell, 1.
, and support the Integrated Marketing Communication (IMC) frameworkAos emphasis on impactful messaging (Kotler & Armstrong, 2024.
Porcu et al.
, 2.
The study contributes to the field by providing empirical insights into audience responses to AI-driven film promotion in Indonesia, addressing a gap in the literature on localized applications of AI in marketing (Nuraini, 2024.
Yusup et al.
, 2.
underscores AIAos potential to transform entertainment advertising while highlighting the importance of addressing comprehension barriers to maximize campaign effectiveness.
Recommendation Based on the studyAos findings, this section offers practical and research recommendations to enhance the application of AI-driven advertisements in film promotion on social media platforms.
The research addressed the problem of limited understanding of audience responses to AI-driven film promotion campaigns on Instagram in Indonesia, driven by the growing use of AI in marketing and the need to evaluate its effectiveness (Nuraini, 2024.
Yusup et al.
A qualitative case study approach was employed, with data collected through in-depth interviews with five active Instagram users and analyzed using thematic analysis (Clarke & Braun, 2017.
Hollweck, 2.
Key findings revealed that AI-driven advertisements were perceived as innovative .
/5 informant.
, faced comprehension challenges .
/5 informant.
, and increased engagement and positive brand perception .
/5 informant.
(Mehrabian & Russell, 1974.
Rahmadani et al.
, 2.
These findings suggest that AI enhances marketing outcomes but requires careful implementation to overcome technical comprehension barriers (Nuraini, 2024.
Zeithaml et al.
, 1.
Practical Recommendations Enhance Transparency in AI Use: Brands should incorporate brief explanations or visual cues in advertisements to clarify AIAos role, addressing comprehension challenges observed in the study (Nuraini, 2.
For example.
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Leverage Interactive Features:
Given the positive response to interactive content, brands should further utilize InstagramAos features .
, polls, storie.
to enhance engagement, aligning with the SOR frameworkAos emphasis on evoking positive responses (Mehrabian & Russell.
Target Contextual Relevance: Advertisements should continue to align with contemporary issues .
, environmental or social theme.
to maintain audience resonance, as supported by the IMC framework (Kotler & Armstrong, 2024.
Porcu et al.
, 2.
Research Recommendations Expand Sample Diversity: Future studies should include a larger and more diverse sample, incorporating varied demographics .
, age, gender, technological literac.
to improve generalizability (Hollweck, 2.
Incorporate Mixed Methods: Combining interview data with social media analytics .
engagement metric.
would provide a more comprehensive understanding of AIdriven campaign impacts, addressing the limitation of relying solely on interviews (Clarke & Braun, 2.
Compare AI and Non-AI Campaigns: Comparative studies of AI-driven versus traditional advertisements could clarify AIAos unique contributions, building on the gap identified in prior research (Rahmadani et al.
Yusup et al.
, 2.
This study contributes to marketing communications by demonstrating AIAos potential to drive innovation and engagement in film promotion while highlighting the need for clear communication to mitigate comprehension These findings and recommendations provide a foundation for brands and researchers to optimize AI-driven advertising strategies in the Indonesian entertainment industry, enhancing both practical applications and theoretical understanding (Choudhury & Harrigan, 2014.
Nuraini, 2.
Contemporary Journal on Business and Accounting (CjBA) Vol.
6 No.
1 (Apri.
Page 1-15
REFERENCES