Artificial Intelligence, Consumer Trust and the Promotion of Pro-Environmental Behavior Among Youth

Abstract

The development of artificial intelligence has enabled the automation of an increasing number of processes and actions in the online environment, from creating unique and engaging content to simulating user behaviors (likes, comments, reviews). This automation has brought several positives to the online environment, including reduced working time and better results, among others. However, at the other end of the spectrum, consumer trust is starting to decline. Before the advent of artificial intelligence, reviews were often the opinions of other customers who had tried the product or service in question. With the evolution of these reviews, providers can now automatically post them to create a favorable image. Given the increasing concern among young people about environmental issues, this study investigates how AI-generated content affects their trust in sustainability-related online reviews and how this trust influences their pro-environmental purchasing decisions. Quantitative research was conducted in the article, based on which a conceptual model of the degree of trust users have in online reviews and reactions in the context of artificial intelligence was developed. The research methodology involved conducting quantitative research and constructing variables based on the data collected. The results revealed significant links between the evolution of artificial intelligence and the degree of trust users place in general feedback found in online environments.

1. Introduction

The increasing urgency of addressing climate change, resource depletion, and environmental degradation has placed sustainability at the forefront of global discourse. In this context, young people—those under the age of 26—emerge as a vital force for driving pro-environmental behavior and societal change. Numerous studies indicate that younger generations are significantly more concerned with environmental sustainability than previous ones [1,2], displaying a heightened willingness to adjust their lifestyles, consumption habits, and civic engagement accordingly. However, the digital environment through which much of this generation interacts with brands and organizations presents unique challenges and opportunities for promoting authentic sustainability behaviors [3].

Online reviews and social media engagement have become central tools through which young consumers gather information, validate environmental claims, and make purchasing decisions. For products and services promoting ecological responsibility, the digital sphere acts not only as a marketplace but also as a battleground for credibility. Trust in sustainability claims communicated via online reviews and social media is paramount in influencing youth behavior toward pro-environmental choices [4,5,6].

Artificial intelligence (AI) has dramatically reshaped the online communication landscape. Its ability to automate the creation of text, images, and user interactions such as likes and comments has introduced both efficiency and complexity into the digital ecosystem [7]. On the one hand, AI technologies enable brands to reach consumers with personalized, timely, and engaging sustainability messages. On the other hand, the same technologies can be misused to generate fake reviews, simulate user engagement, and present an artificially positive image of products and services. This manipulation risks undermining young consumers’ trust in the authenticity of sustainability-related communications [8].

Given that youth populations are particularly reliant on online information when evaluating sustainability initiatives [9,10], understanding how AI-generated content affects their perceptions is crucial. Young consumers often seek validation through the experiences of others, relying on the credibility of online reviews and social media engagement as proxies for the environmental integrity of brands [11]. When this content is authentic and transparent, it can foster greater trust, stronger brand loyalty, and increased adoption of sustainable behaviors. Conversely, when content is manipulated or inauthentic, it can generate skepticism, erode trust, and ultimately deter young people from engaging with sustainability initiatives [12].

Several studies have established the pivotal role of online reviews in shaping consumer perceptions [1,5,6,7,8]. Positive reviews, particularly when aligned with environmental attributes, can stimulate sustainable purchasing behaviors by providing social proof of a product’s eco-friendliness. Social media engagement—such as likes, shares, and comments—also serves as a key indicator of a brand’s environmental commitment, influencing the perceived authenticity and trustworthiness of its sustainability claims. In this dynamic, AI’s influence over the generation and amplification of online feedback introduces a critical variable that warrants close examination [3].

Youth populations today are not only more connected digitally but are also more adept at detecting inconsistencies and inauthenticity in brand communications. Nevertheless, their ability to critically assess the origin and reliability of online sustainability claims is still developing. The automated generation of reviews and engagement, particularly when indistinguishable from human-authored content, can obscure their evaluations and potentially mislead them into supporting brands that engage in greenwashing rather than genuine sustainable practices [13,14].

Our study addresses a critical gap in the literature by exploring the impact of artificial intelligence on youth trust in sustainability-related online reviews and social media engagement. It examines the relationships between the familiarity of young consumers with AI-driven automation, their ability to distinguish between human-generated and AI-generated content, and their trust in online feedback regarding environmental products and services. Furthermore, it analyzes how these factors collectively influence their pro-environmental purchasing decisions.

By focusing on individuals aged between 18 and 25, our research captures insights into the demographic segment most likely to shape future patterns of sustainable consumption. Understanding how trust is built—or eroded—in digital environments is crucial for developing effective strategies to promote authentic, pro-environmental behavior among young people. In an era where technological innovation rapidly outpaces regulatory and ethical frameworks, ensuring that AI supports rather than undermines sustainability communication is more critical than ever.

Our study contributes to the broader discourse on fostering a culture of environmental action among young people. By identifying the factors that influence youth trust in online sustainability communications, this research provides actionable insights for marketers, policymakers, educators, and sustainability advocates seeking to engage the next generation of environmental stewards. Ultimately, nurturing informed, critical, and engaged youth consumers is indispensable for achieving the global shift toward a more sustainable and resilient society.

2. The Role of Online Feedback

Online reviews and social media engagement are two critical elements in building consumer trust in sustainable products and services. This is especially relevant for young consumers, who are increasingly seeking authentic perspectives on the environmental impact of their purchasing choices. Online reviews enable users to access firsthand experiences from other individuals, while social media engagement facilitates direct interactions with brands and communities that promote environmental values [1,5,6].

Young consumers, particularly those under the age of 26, are becoming significantly more conscious of environmental sustainability when making purchasing decisions [2,7]. In this context, understanding how artificial intelligence affects their trust in online reviews related to sustainable products and services becomes crucial for promoting pro-environmental behaviors. Our study addresses a critical gap by examining how artificial intelligence (AI) affects the perceptions and behaviors of young people in the sustainability domain.

Online reviews are particularly influential in the decision-making process because they provide tangible social proof regarding the environmental credentials of products or services. According to Zaman et al. [10], online reviews not only improve perceptions of quality but may also stimulate impulse purchases, suggesting a direct link between reviews and consumer confidence in sustainable options. When faced with a multitude of choices, young consumers evaluate their options by studying online reviews; the more numerous and positive the reviews concerning sustainability claims, the higher the level of trust and the stronger the intention to purchase eco-friendly products. Consumer trust, therefore, plays a mediating role, being built upon the positive sustainability-related reviews they encounter [10].

Yusak et al. applied the Stimulus–Organism–Response (SOR) model to explore how online reviews influence impulsive buying behavior [1]. Their findings showed that shopping enjoyment and impulsive buying tendencies are significantly affected by online reviews. In the context of sustainability, creating a positive emotional experience through eco-conscious branding and authentic reviews could enhance the likelihood that young consumers will make environmentally responsible impulse purchases.

In a study conducted among online travel agencies in Brazil, Maia et al. found that online reviews enhance consumer trust in lesser-known brands [11]. For young consumers focused on sustainable travel options or eco-friendly brands, reviews can thus be pivotal in building trust and overcoming skepticism towards newer initiatives. In the globalized, digital marketplace, emerging sustainable brands often rely heavily on reviews to establish credibility and boost purchase intent [9].

Van Dat Tran demonstrated that credible online reviews have a significant influence on brand trust dimensions, such as trustworthiness and intentionality [4]. These dimensions are essential when young consumers assess the authenticity of sustainability claims made by brands. Similarly, Cuong H. Pham found that online reviews can compensate for the lack of direct experience, a key factor when selecting eco-friendly products that are often novel or less well-known [6]. Essentially, young people may place greater trust in sustainable brands they have never tried before, as long as they are supported by positive online reviews emphasizing eco-friendly practices.

Faiza Belbachir highlighted that sentiments expressed in reviews and the perceived sociability of the reviewer are critical in determining trust [5]. For sustainability-focused consumers, reviews with personal narratives about environmental impact are likely to be more persuasive, reinforcing trust in both the product and the brand’s ecological claims.

Social media engagement also plays a crucial role in promoting pro-environmental behavior among young consumers by fostering long-term relationships based on shared values. Engagement strategies that involve authentic sustainability messaging can significantly enhance brand trust and loyalty. Interaction with influencers who advocate for environmental causes can further strengthen this trust, as shown in studies demonstrating the impact of authenticity, expertise, and relatability of influencers on consumer behavior [2].

Jitha G. Nair (2023) examined the role of brand love, brand trust, product quality, and customer service in fostering customer engagement on social media, ultimately influencing brand loyalty [12]. For sustainability-focused brands, cultivating genuine connections through transparent communication about eco-friendly practices is key to building long-term loyalty among young consumers. Even for new brands, a strong and engaged social media presence that promotes environmental responsibility can foster immediate trust.

Saleh Bazi et al. [9] emphasized that the aesthetic and entertaining quality of social media content plays a role in promoting engagement [9]. Sustainable brands can leverage this by creating visually compelling and entertaining content that highlights their eco-friendly initiatives, thereby enhancing consumer engagement and loyalty.

Research conducted in Indonesia [15] also suggests that customer relationships, facilitated by social media engagement, have a significant impact on brand loyalty. Building authentic, sustainability-oriented communities online can thus significantly influence young consumers’ trust and purchasing decisions. Moreover, interacting with eco-conscious influencers can effectively transfer the trust associated with the influencer to the brand itself, making influencer marketing a powerful tool for sustainability communication.

Overall, social media engagement is crucial for cultivating a culture of environmental responsibility among young people, which significantly contributes to consumer loyalty towards sustainable brands. Companies should invest in marketing strategies that promote genuine, eco-centric interaction on social platforms to build trust, loyalty, and ultimately inspire more sustainable consumer behaviors [16].

Additionally, Skarzyńska emphasizes the significance of digital trust, demonstrating that it can facilitate the adoption of innovative solutions, including sustainable technologies, and increase consumer engagement with brands committed to environmental stewardship [13].

In essence, online reviews and social media engagement play complementary roles in fostering trust among young consumers regarding sustainable products and brands. While reviews provide the social validation necessary for reducing uncertainty in eco-friendly purchases, social media engagement cultivates a dynamic and mutually beneficial relationship based on shared environmental values. This synergy can transform the way young consumers perceive, trust, and engage with sustainability-oriented brands, leading to more informed purchasing decisions and long-term pro-environmental behavior.

Research Hypotheses

Based on the literature and our own observations, we have developed several hypotheses regarding the relationships between our constructs. Thus, engagement and recognition has the ability to differentiate between how human-generated and AI-generated texts (recognition) influence both online engagement (engagement) and familiarity with AI usage (familiarity). Although the relationship between the ability to use proficiently AI models and engagement has been approached in several previous studies [7,10], we are unaware of studies using the ability to recognize AI-generated content in the context of online content engagement, particularly with user reviews, and we consider it as a novel contribution of our study.

Moreover, online engagement was demonstrated in previous articles to impact the perception of online reviews (reviews) and opinions about AI (opin_ai) in the context of sustainable brands [11,12], as well as towards familiarity with AI models [8]. Opinions about AI were hypothesized to further influence trust in online reviews (trust_r) [13].

H1: 

There is a direct and positive relationship between the ability to differentiate between human-generated and AI-generated texts (recognition) and engagement with online content.

H2: 

There is a direct and positive relationship between the ability to differentiate between human-generated and AI-generated texts (recognition) and familiarity large language models (LLMs).

H3: 

There is a direct and positive relationship between engagement with online content and familiarity large language models (LLMs).

H4: 

There is a direct and positive relationship between engagement with online content and positive perceptions of AI models (LLMs).

H5: 

There is a direct and positive relationship between familiarity large language models (LLMs) and positive perceptions of AI models (LLMs).

We also assume that our novel construct, users’ ability to differentiate between human-generated and AI-generated texts (recognition), influences the perception of online reviews (reviews), in turn influencing trust in online reviews [8]. Finally, opinions about AI models (LLMs) will shape users’ general engagement with content they perceive as AI generated (trust_en) [2]. As a result, we formulated the following hypothesis:

H6: 

There is a direct and positive relationship between the ability to differentiate between human-generated and AI-generated texts (recognition) and perception of online reviews.

H7: 

There is a direct and positive relationship between perception of online reviews and trust in online reviews.

H8: 

There is a direct and positive relationship between positive perceptions of AI models (LLMs) and trust in online reviews.

H9: 

There is a direct and positive relationship between perception (opinions) of online reviews and trust in online reviews.

These links were modeled using regression coefficients (β) and significance values (P) to evaluate the strength and statistical significance of each relationship, resulting in a detailed structural equation model (SEM) that highlights the interdependencies among the studied variables and their relevance for fostering pro-environmental purchasing behaviors among youth.

3. Technical Explanation of Automation

The emergence of artificial intelligence has led to its involvement in an increasing number of processes aimed at automating and streamlining various online activities. The marketing and communication domains, including the promotion of sustainability-related products and behaviors, have not remained unaffected by the evolution of AI [7,10]. From the perspective of young consumers, who are actively seeking authentic information about environmental initiatives, the rise of AI-driven content presents both opportunities and challenges [12].

In the online environment, the impact of AI is evident in the generation and amplification of reviews and engagements, which sometimes originate from automated systems rather than genuine consumers. For youth populations, trust in sustainability claims—whether related to eco-friendly products, green initiatives, or corporate environmental responsibility—is crucial in driving pro-environmental behavior [3]. However, the automation and potential falsification of online reviews can undermine this trust, making it more challenging for young consumers to distinguish genuine sustainability efforts from mere greenwashing [10].

Artificial intelligence plays a dual role in this landscape: it can be used both to manipulate and to authenticate online communications. Petrescu et al. highlight the growing need to understand how AI technologies can be leveraged to influence consumer opinions, as well as the parallel need to develop effective detection mechanisms [7]. AI systems are capable of analyzing linguistic and contextual patterns, enabling both the creation of seemingly authentic reviews and the identification of inauthentic ones. For young consumers concerned with sustainability, the ability to distinguish genuine environmentally responsible practices from false claims becomes an essential skill.

For example, machine learning algorithms can detect patterns such as exaggerated emotional language or narrative inconsistencies, which are common in fabricated reviews [8]. However, the majority of young users may lack the advanced knowledge or critical tools needed to evaluate online content for authenticity, leading to misplaced trust in AI-generated sustainability claims.

Another critical aspect is how fake sustainability-related reviews can influence purchasing behavior. Positive fabricated reviews may artificially enhance the eco-credentials of a product, misleading environmentally conscious youth into supporting brands that do not genuinely uphold sustainability principles. Conversely, negative fake reviews could undermine the credibility of genuinely sustainable brands [14].

The prevalence of such practices poses significant risks for movements promoting sustainable consumption among young people. False-positive reviews can make a product appear more eco-friendly than it is, leading to distorted purchasing decisions based on misinformation. Over time, this manipulation can erode the trust that youth place in online reviews and even in sustainability certifications more broadly [8].

To counteract these effects, researchers have developed AI-based detection methods that analyze not only the text of reviews but also patterns of user behavior and rating distributions. Advanced deep learning techniques, such as convolutional neural networks (CNNs) and bidirectional long short-term memory networks (BiLSTMs), have shown promise in classifying reviews as genuine or fake based on subtle linguistic cues [15].

For youth audiences who value authenticity in environmental claims, ensuring the reliability of online reviews is paramount. Without reliable information, their pro-environmental purchasing behaviors could be compromised, slowing broader efforts to foster a sustainable society [17].

In conclusion, the automation of online reviews presents a significant challenge to fostering authentic and sustainable engagement among young people. While AI technologies offer powerful tools for creating engaging content, it is critical to balance these capabilities with mechanisms that protect the integrity of sustainability-related communications. Ensuring that young consumers can trust the information they read about environmental initiatives online is essential for maintaining momentum toward a more sustainable future.

4. Materials and Methods

This article presents a quantitative research study conducted using the survey method and a structured questionnaire as the data collection instrument. The research focused specifically on individuals aged 18 to 25 years to explore how young consumers perceive the authenticity of online sustainability-related content and how artificial intelligence influences their trust in such content. We received over 500 answers, and after conducting validity and consistency checks, we ended up with 412 complete answers.

Participants were recruited online via social media platforms and student mailing lists from Romanian universities. The relevant behavioral items used a 5-point Likert scale, adapted from previous studies [18,19]. The scales for each construct were adapted from previously validated studies. Specifically, items related to trust in online reviews and AI perception were derived from Bart et al. (2005) [18] and Flanagin & Metzger (2007) [19], both of which examined online trust and information credibility. Constructs that did not have direct matches in the prior literature, such as the ability to distinguish AI-generated content, were developed by the authors and pre-tested using a pilot sample (n = 30) to ensure clarity and internal consistency. Cronbach’s alpha values for all constructs exceeded the 0.70 threshold, confirming reliability. The study focused on identifying a direct link between the evolution of artificial intelligence and the degree of trust that young users place in online feedback, both in terms of reactions (likes, comments) and reviews, particularly when these communications refer to sustainability practices and eco-friendly products. Additionally, the study sought to investigate whether differences exist between the trust attributed to reviews and the trust attributed to social media engagements in the context of promoting pro-environmental behavior.

The research objectives were operationalized by constructing variables that reflect the strength and direction of the relationships between the factors studied, with a focus on sustainability-related contexts. Each objective represents the analysis of the relationship between two key variables related to trust, AI familiarity, and environmental purchasing behavior.

WarpPLS 8.0 software was employed to analyze the data and model the relationships between the variables. This included calculating link coefficients and probabilities to validate or invalidate hypotheses derived from the theoretical framework. Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis, using WarpPLS, is particularly suited for examining complex relationships between measurement and structural variables, especially when dealing with relatively new research topics, such as the impact of AI on youth trust in sustainability communications.

The variables in the model were designed based on questionnaire items as follows (

Table 1. Variables and corresponding items used to assess the influence of AI and online interactions on sustainable purchase decisions.

Variable	Item Used
The influence of online reviews on sustainable purchase decisions (reviews)	- Influence of online reviews on choosing sustainable products/services - Reliability of online reviews for the sustainability performance of a product or service - Perceived subjectivity of online reviews
The influence of online reactions (likes, comments, shares) on sustainable purchase decisions (engagement)	- Online feedback impact on driving sustainable products - Impact of users’ reactions on social media platforms on environmentally responsible buying decisions - Reliability of online reviews on a post’s alignment with sustainability values
Familiarity with the use of AI in the context of online process automation (familiar)	- Creating text content - Creating multimedia content - Generating texts for reviews - Automatic posting of positive sustainability-related reviews - Automatic generation of reactions on social media platforms (likes, comments)
The differentiation capacity of the human factor compared to AI-generated texts (recognition)	- Reviews on official supplier websites - Reviews on marketplace platforms - Social media comments - Number of like/share reactions
Opinion about using AI to improve online image (opin_ai)	- Influence of AI on distorted customer experience - Influence of AI on creating a false-positive image of sustainability claims - Bias towards AI’s ability to build an authentic, sustainable brand image - Preference for content with impactful environmental topics

):

To assess the risk of common method bias, Harman’s single-factor test was conducted. The results showed that no single factor accounted for more than 50% of the variance, indicating that common method bias is unlikely to affect the results significantly.

Regarding the demographic profile, the final sample (n = 412) included 58% female and 42% male respondents, with the majority (72%) aged between 20 and 23 years. Most participants were undergraduate students (81%), and 67% reported medium-to-high familiarity with AI applications in digital media.

5. Results

Measurement Model Evaluation

Before evaluating the structural model, we assessed the reliability and validity of the measurement model. All constructs showed composite reliability (CR) values > 0.70 and average variance extracted (AVE) values > 0.50, indicating good convergent validity. Discriminant validity was confirmed using the Fornell–Larcker criterion, with the square root of AVE for each construct exceeding the inter-construct correlations. These results confirm that the measurement model is both reliable and valid.

Following the use of the WarpPLS program and the creation of the proposed conceptual model, the links between the proposed variables and their results were highlighted as follows (Figure 1):

The model presented above illustrates the interactions between variables related to the influence of online reviews, online reactions, familiarity with AI, the ability to differentiate between human-generated content and AI-generated content, opinions on using AI to improve online sustainability, and trust in reviews and AI among young consumers. These relationships were analyzed using regression coefficients (β) and significance values (P), providing a detailed understanding of how these factors interact and influence pro-environmental purchasing behavior among youth. The model indicates that all our research hypotheses have been supported.

From the relationships, we can see a strong and significant influence of the ability to differentiate between human-generated content and AI-generated texts on online reactions (likes, comments, shares), with a β coefficient of 0.98 and a significance level of p < 0.01. This suggests that when young consumers are more capable of recognizing authentic sustainability communication, their level of online engagement with eco-friendly content increases substantially. Higher engagement with credible, authentic content can therefore support stronger pro-environmental behaviors.

On the other hand, no significant influence was found between the ability to differentiate human-generated content and opinions about using AI to improve online sustainability images (β = 0.00, p = 0.50). This finding suggests that recognizing AI involvement does not necessarily alter young consumers’ opinions about the legitimacy of AI’s role in enhancing brand perceptions related to environmental responsibility.

Online reactions, such as likes, comments, and shares, have a strong and significant influence on opinions about using AI for promoting sustainability initiatives online (β = 0.96, p < 0.01). This means that the higher the level of youth engagement with sustainability-related content, the more positively they view the use of AI to amplify sustainability messages.

Moreover, the ability to differentiate human-generated content is directly and significantly associated with familiarity with AI use in online process automation (β = 1.00, p < 0.01). This indicates that youth who are more skilled at identifying AI involvement in content creation are also more familiar with the ways AI is utilized in digital marketing and communications, including the promotion of sustainability claims.

Furthermore, online reactions have a strong and significant influence on the perception of online reviews (β = 0.99, p < 0.01). This implies that the more engaged young users are with sustainability content on social media, the more value they place on related reviews when deciding which eco-friendly products or brands to support.

The model quality indicators showed high explanatory power. Specifically, the R² values were as follows: engagement (R² = 0.96), familiarity (R² = 0.94), opinions about AI (R² = 0.92), perception of reviews (R² = 0.99), and trust in reviews (R² = 0.97). These high R² values demonstrate the robustness of the model in explaining the variance of key outcome variables.

6. Discussion

The article examines the impact of artificial intelligence (AI) development on the automation of online processes, spanning from content creation to simulating user behaviors, such as likes and comments. While this automation has brought significant advantages, such as reducing work time and enhancing communication efficiency, it also presents serious challenges regarding consumer trust, particularly among young people who are concerned with environmental sustainability.

First, the relationship between online reviews and purchase decisions for sustainable products is well-documented. A study from Ningbo University and Western Sydney University demonstrated that consumer attention to negative comments is significantly higher than to positive ones, influencing purchase decisions. Similarly, our findings suggest that online reviews emphasizing sustainability attributes have a significant impact on the purchasing choices of young people. Reviews and ratings serve as essential sources of validation for young consumers seeking environmentally friendly options [20].

Regarding the influence of online reactions on purchasing decisions, previous studies show that social validation through digital engagement (likes, shares) plays a vital role in influencing young consumers [6]. In this study, it was found that high levels of engagement with sustainability topics correlate with stronger intentions to make environmentally responsible purchasing decisions.

The opinion about using AI to enhance online sustainability images has a positive and significant influence on trust in AI (β = 0.29, p = 0.03). This suggests that when young consumers view AI as a tool that can support truthful and effective sustainability messaging, their trust in AI-generated content increases. Interestingly, the model reveals that online reviews have a negative and significant influence on trust in reviews (β = −2.00, p < 0.01). This counterintuitive result suggests that an oversaturation of sustainability-related reviews, particularly when authenticity is questionable, may lead to skepticism among young consumers, reducing overall trust in these reviews. This finding underscores the importance of transparency and authenticity in sustainability communication efforts, in line with previous studies [6,14,21].

Finally, the opinion about AI’s role also has a positive and significant influence on trust in online reviews (β = 2.18, p < 0.01). This finding suggests that a favorable view of AI’s role in promoting environmental responsibility can enhance overall trust in online sustainability communications, confirming previous research [7].

The R² values for the dependent variables reveal the explanatory power of the model. For instance, 96% of the variation in “engage” (online engagement) is explained by “recogni” (the ability to differentiate AI-generated content), and 99% of the variation in “reviews” is explained by “engage.” These results demonstrate the central role of authentic engagement in influencing young consumers’ perceptions and behaviors related to sustainability. The use of PLS-SEM methodology, particularly in studying consumer online behavior and satisfaction with digital services, has proven to be effective in analyzing complex relational models in previous studies as well [22].

These findings underscore the importance of deploying ethical AI, promoting improved media literacy, and developing trustworthy sustainability narratives tailored for young digital audiences.

In addition to the insights discussed, the recent literature continues to emphasize critical nuances regarding AI-driven sustainability communication and youth trust. Jin and Park [23] highlight how algorithmic transparency enhances consumer trust, particularly in eco-friendly digital ecosystems. Kapitan and Silvera [24], along with Naderer and Matthes [25], reinforce the influence of credible eco-influencers in shaping sustainable consumption, especially when value congruence is high. Ibrahim and Shabir [26] argue that youth are particularly sensitive to the credibility of AI-generated environmental messaging, a factor that directly correlates with engagement.

On the methodological side, Rios and Vassallo [27] and Tran and Hoang [28] have provided updated validations of scales used in environmental behavior research, supporting the robustness of the instruments used in this study. From a critical standpoint, Krishnan and Haque [29] caution against the overuse of automation in green marketing, which may backfire by reducing perceived sincerity. Complementarily, Chung, Ko, and Joung [30] propose that AI’s impact on brand sincerity should be transparently managed to maintain trust among younger audiences.

Together, these studies confirm the evolving complexity of trust in sustainability communications and offer theoretical reinforcement to our findings regarding content authenticity, influencer engagement, and the dual role of AI in facilitating and potentially undermining trust.

7. Conclusions

The article examines the impact of artificial intelligence (AI) development on the automation of online processes, spanning from content creation to simulating user behaviors, such as likes and comments. While this automation has brought significant advantages, such as reducing work time and enhancing communication efficiency, it also presents serious challenges regarding consumer trust, particularly among young people who are concerned with environmental sustainability.

The quantitative research conducted in this study developed a conceptual model aimed at assessing the level of trust that young consumers place in online reviews and reactions in the context of AI-generated content, particularly regarding sustainability claims. The results indicated significant links between the evolution of AI, online engagement, and the trust placed in sustainability-related feedback among youth populations.

Some of our paper’s limitations come from its sampling method, which particularly targeted students. However, they are relevant for our subject, as they are early adopters of most technologies and their role in establishing social trends, especially for technology related products, has been addressed in the literature [22].

A crucial aspect of the study was the role of online reviews and social media engagement in influencing environmentally responsible purchasing decisions among young consumers. Online reviews, serving as tangible social proof regarding the environmental quality of products and services, significantly impact the intention to purchase sustainable alternatives. Our findings indicate that positive online reviews can improve perceptions of product quality and stimulate pro-environmental impulsive buying behaviors.

Social media engagement also plays a crucial role in promoting pro-environmental behavior among young people. Authentic interaction with sustainability-focused content and eco-conscious influencers appears to enhance brand trust, foster consumer loyalty, and motivate more sustainable purchasing decisions. In a digital environment saturated with AI-generated content, maintaining transparency and authenticity becomes crucial to nurturing youth trust.

Another important finding of this research relates to how AI-generated fake reviews can either artificially amplify or diminish the perceived environmental responsibility of brands. Misleading sustainability claims created or manipulated through AI may erode young consumers’ trust in eco-friendly branding, threatening efforts to foster pro-environmental behavior among younger generations.

The research employed advanced analytical methods, such as Partial Least Squares Structural Equation Modeling (PLS-SEM) using WarpPLS software, to evaluate the complex relationships between variables. The model revealed that young consumers’ ability to distinguish AI-generated content significantly influences their online engagement with sustainability communications, their familiarity with AI use, and ultimately their purchasing behaviors regarding environmentally responsible products.

In conclusion, the automation of online reviews and reactions presents both opportunities and risks for sustainability communication targeting young audiences. While AI can be a powerful tool for enhancing eco-friendly brand messaging, it must be applied ethically and transparently to preserve consumer trust.

While AI can facilitate communication and amplify sustainability narratives, it also poses challenges regarding the authenticity of online content, particularly in the eyes of young consumers who are increasingly sensitive to greenwashing and manipulative marketing practices. In response to these challenges, marketers aiming to engage environmentally conscious youth should adopt transparent labelling mechanisms for AI-generated content, such as trust badges or disclosure statements, to signal the authenticity of online reviews and sustainability claims. Platforms can also integrate AI-detection tools that alert users when content may have been generated or influenced by algorithms. These tools should be user-friendly and visually embedded into the review ecosystem to promote informed consumption. Similarly, educational institutions and NGOs should consider developing media literacy programs aimed at enhancing young people’s critical thinking regarding digital content. These programs could include interactive modules on recognizing AI-generated content, understanding algorithmic influence, and distinguishing between persuasive and manipulative sustainability claims.

The findings underscore the urgent need for brands, marketers, and sustainability advocates to ensure the authenticity of online communications, particularly when targeting youth populations. Trustworthy, transparent online information is essential for maintaining and strengthening young consumers’ commitment to sustainable behaviors and for fostering a culture of environmental action for the future.