Consumer Awareness and Trust on AI-Generated Marketing Messages

Abstract

Trust in AI-based marketing systems held by consumers is different from trust created using regular marketing processes. Whereas conventional trust building process relies on brand familiarity, consistency in the provision of products/services, and interaction reliability, trust building in AI-based marketing considers psychological and behavioral issues. These include consumers\' understanding of automation in the marketing processes, independence of AI system in decision-making, credibility of results generated by AI, reliability of recommendations made to customers, and the degree to which consumers perceive themselves to be in control. It is, therefore, important for organizations to understand the unique features of consumer trust in order to successfully conduct AI-based marketing activities. The present study aimed to know the association between demographic forces and, consumer awareness and trust on AI-generated marketing messages In Kozhikode district of Kerala. 100 respondents in Kozhikode District were chosen by convenience sampling method and interview schedule was applied in the study to collect primary data. Through Artificial Intelligence (AI), organisations have been able to transform their marketing environment through the creation of personalized, automatic, and real-time marketing messages. The use of AI-generated marketing messages is common in advertisements, product descriptions, marketing emails, social media posts, chatbots, and personalized marketing recommendations. Although these tools have many advantages like efficiency, consistency, personalization, and fast content creation, there are also some disadvantages such as the validity of the messages, transparency, accuracy, privacy, and whether or not the messages were created by humans. These issues can affect the awareness and trust of consumers towards marketing messages.

Introduction

The text examines consumer awareness and trust in AI-generated marketing messages, focusing on how the rapid development of artificial intelligence has changed the creation and delivery of marketing communication.

AI is increasingly used for advertising, product descriptions, promotions, email marketing, social media content, product recommendations, chatbots, and customer interactions. By analyzing large amounts of consumer data, AI can generate personalized messages quickly and efficiently. This improves speed, consistency, personalization, and cost-effectiveness, but it also raises concerns about accuracy, transparency, privacy, manipulation, and trust.

Consumer awareness and trust

The study emphasizes two important factors:

• Consumer awareness refers to consumers' understanding that AI is being used to create marketing messages, personalize content, and automate marketing decisions. Greater awareness may help consumers evaluate marketing messages more critically.

• Consumer trust refers to consumers' perceptions of the reliability, accuracy, credibility, and dependability of AI-generated marketing communication. Trust can increase when AI provides relevant, consistent, transparent, and dependable information.

However, consumers may distrust AI-generated messages because of privacy concerns, excessive personalization, inaccurate information, lack of transparency, data misuse, manipulation, and uncertainty about whether content was created by humans or AI.

Research problem and objective

The rapid adoption of AI in marketing has created a need to understand how consumers perceive and trust AI-generated marketing communication. The study particularly focuses on the relationship between demographic characteristics, consumer awareness, and trust in AI-generated marketing messages in Kozhikode district, Kerala.

Methodology

The study used a descriptive research design and collected both primary and secondary data.

• 100 respondents from Kozhikode district participated.

• Primary data were collected through an interview schedule.

• Convenience sampling was used.

• Multiple regression analysis was employed to identify factors associated with consumer trust in AI-generated marketing messages.

Key findings

The regression analysis found a strong relationship between the selected variables and consumer trust:

• R = 0.763, indicating a strong overall relationship.

• R² = 0.582, meaning that 58.2% of the variation in consumer trust was explained by the twelve variables included in the model.

• Adjusted R² = 0.525, meaning that 52.5% remained explained after adjusting for the number of predictors.

• The overall regression model was statistically significant (F = 10.105, p < 0.001).

Four variables had statistically significant individual relationships with consumer trust:

• Gender — significant at the 5% level.

• Educational qualification — significant at the 1% level.

• Occupation — significant at the 5% level.

• Experience in online shopping — significant at the 1% level.

The analysis found that online shopping experience had a positive coefficient, suggesting that respondents with greater online shopping experience tended to have higher predicted trust scores, holding other variables constant.

The negative coefficients for gender and educational qualification should not be interpreted as inherently negative effects because their meaning depends on how the categories were numerically coded.

The following variables were not statistically significant individually at the 5% level:

• Age

• Marital status

• Family size a substantial portion of differences in consumer trust, while other factors not included in the study account for the remaining

• Family type

• Income level

• Online shopping frequency

• Acceptance of AI-generated messages

• Purchasing based on AI-generated messages

Conclusion

AI generated messages are currently utilized for making product recommendations, personalized advertisements, promotional communication, product descriptions, and customer interaction online. However, although the use of such technologies can contribute to more efficient, consistent, and accurate marketing communication, the awareness of consumers about such technologies is a critical issue. Businesses should disclose whether the marketing content is AI generated or assisted to some extent. This disclosure will enable consumers to know the origin of the message and be able to make an informed choice. Despite the efficiency of AI in creating marketing messages, human intervention should be considered to detect mistakes, irrelevant content, inflated claims and communications that might harm consumer confidence. AI-generated marketing messages should be well-vetted prior to publication. Businesses should confirm that the product descriptions, price, offers, specifications among other content provided are truthful and do not contain misleading information. Marketers should carry out awareness campaigns on how AI is being used in marketing communications through social media, websites, advertisements and consumer education initiatives. Organizations utilizing AI for personalized marketing communications should provide a detailed explanation of how consumers\' data are collected, analyzed and utilized. Privacy and data protection measures should be considered to instill consumer confidence. The messages from AI should be relevant recommendations without getting overly personalized. Consumers should have control over their personalized marketing communications. Therefore, it is essential that organisations concentrate their attention on using AI for marketing communications in an open, precise, accountable and consumer-centred way. Human supervision, accurate information, protection of privacy, and proper disclosure of AI-created material may help in creating a credible AI-assisted marketing environment.

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Copyright

Copyright © 2026 Dr. V. K. Veerakumar, Muhammad Dilshad Salam A. V.. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.